Comprehensive Analysis and Identification of an Immune-Related Gene Signature with Prognostic Value for Prostate Cancer

Plasma cell signatures predict prognosis and treatment efficacy for lung adenocarcinoma

PURPOSE

This study aims to identify key genes regulating tumor infiltrating plasma cells (PC) and provide new insights for innovative immunotherapy.

METHODS

Key genes related to PC were identified using machine learning in lung adenocarcinoma (LUAD) patients. A prognostic model called PC scores was developed using TCGA data and validated with GEO cohorts. We assessed the molecular background, immune features, and drug sensitivity of the high PC scores group. Real-time PCR was utilized to assess the expression of hub genes in both localized LUAD patients and LUAD cell lines.

RESULTS

We constructed PC scores based on seventeen PC-related hub genes (ELOVL6, MFI2, FURIN, DOK1, ERO1LB, CLEC7A, ZNF431, KIAA1324, NUCB2, TXNDC11, ICAM3, CR2, CLIC6, CARNS1, P2RY13, KLF15, and SLC24A4). Higher age, TNM stage, and PC scores independently predicted shorter overall survival. The AUC value of PC scores for one year, three years, and five years of overall survival were 0.713, 0.716, and 0.690, separately. The nomogram model that integrated age, stage, and PC scores showed significantly higher predictive value than stage alone (P < 0.01). High PC scores group exhibited an immune suppressing microenvironment with lower B, CD8 + T, CD4 + T, and dendritic cell infiltration. Docetaxel, gefitinib, and erlotinib had lower IC50 in high PC groups (P < 0.001). After validation through the local cohort and in vitro experiments, we ultimately confirmed three key potential targets: MFI2, KLF15, and CLEC7A.

CONCLUSION

We proposed a prediction mode which can effectively identify high-risk LUAD patients and found three novel genes closely correlated with PC tumor infiltration.

Unlocking the Potential of Therapy-Induced Cytokine Responses: Illuminating New Pathways in Cancer Precision Medicine

Precision cancer medicine primarily aims to identify individual patient genomic variations and exploit vulnerabilities in cancer cells to select suitable patients for specific drugs. These genomic features are commonly determined by gene sequencing prior to therapy, to identify individuals who would be most responsive. This precision approach in cancer therapeutics remains a powerful tool that benefits a smaller pool of patients, sparing others from unnecessary treatments. A limitation of this approach is that proteins, not genes, are the ultimate effectors of biological functions, and therefore the targets of therapeutics. An additional dimension in precision medicine that considers an individual's cytokine response to cancer therapeutics is proposed. Cytokine responses to therapy are multifactorial and vary among individuals. Thus, precision is dictated by the nature and magnitude of cytokine responses in the tumor microenvironment exposed to therapy. This review highlights cytokine responses as modules for precision medicine in cancer therapy, including potential challenges. For solid tumors, both detectability of cytokines in tissue fluids and their being amenable to routine sensitive analyses could address the difficulty of specimen collection for diagnosis and monitoring. Therefore, in precision cancer medicine, cytokines offer rational targets that can be utilized to enhance the efficacy of cancer therapy.

Transcriptome Analysis Identifies Tumor Immune Microenvironment Signaling Networks Supporting Metastatic Castration-Resistant Prostate Cancer

Prostate cancer (PCa) is the second most common cause of cancer death in American men. Metastatic castration-resistant prostate cancer (mCRPC) is the most lethal form of PCa and preferentially metastasizes to the bones through incompletely understood molecular mechanisms. Herein, we processed RNA sequencing data from patients with mCRPC (n = 60) and identified 14 gene clusters (modules) highly correlated with mCRPC bone metastasis. We used a novel combination of weighted gene co-expression network analysis (WGCNA) and upstream regulator and gene ontology analyses of clinically annotated transcriptomes to identify the genes. The cyan module (M14) had the strongest positive correlation (0.81, p = 4 × 10-15) with mCRPC bone metastasis. It was associated with two significant biological pathways through KEGG enrichment analysis (parathyroid hormone synthesis, secretion, and action and protein digestion and absorption). In particular, we identified 10 hub genes (ALPL, PHEX, RUNX2, ENPP1, PHOSPHO1, PTH1R, COL11A1, COL24A1, COL22A1, and COL13A1) using cytoHubba of Cytoscape. We also found high gene expression for collagen formation, degradation, absorption, cell-signaling peptides, and bone regulation processes through Gene Ontology (GO) enrichment analysis.

Integrating transcriptomics and network analysis-based multiplexed drug repurposing to screen drug candidates for M2 macrophage-associated castration-resistant prostate cancer bone metastases

Metastatic castration-resistant prostate cancer (CRPC) has long been considered to be associated with patient mortality. Among metastatic organs, bone is the most common metastatic site, with more than 90% of advanced patients developing bone metastases (BMs) before 24 months of death. Although patients were recommended to use bone-targeted drugs represented by bisphosphonates to treat BMs of CRPC, there was no significant improvement in patient survival. In addition, the use of immunotherapy and androgen deprivation therapy is limited due to the immunosuppressed state and resistance to antiandrogen agents in patients with bone metastases. Therefore, it is still essential to develop a safe and effective therapeutic schedule for CRPC patients with BMs. To this end, we propose a multiplex drug repurposing scheme targeting differences in patient immune cell composition. The identified drug candidates were ranked from the perspective of M2 macrophages by integrating transcriptome and network-based analysis. Meanwhile, computational chemistry and clinical trials were used to generate a comprehensive drug candidate list for the BMs of CRPC by drug redundancy structure filtering. In addition to docetaxel, which has been approved for clinical trials, the list includes norethindrone, testosterone, menthol and foretinib. This study provides a new scheme for BMs of CRPC from the perspective of M2 macrophages. It is undeniable that this multiplex drug repurposing scheme specifically for immune cell-related bone metastases can be used for drug screening of any immune-related disease, helping clinicians find promising therapeutic schedules more quickly, and providing reference information for drug R&D and clinical trials.

Downregulated PRNP Facilitates Cell Proliferation and Invasion and Has Effect on the Immune Regulation in Ovarian Cancer

Background. Ovarian cancer (OC) seriously threatens women’s life. Ferroptosis plays an essential role in the initiation and development of OC. However, more molecular targets and mechanisms for ferroptosis in OC remain to be further elucidated. Methods. Several OC datasets were integrated in this study and three candidate genes including PRNP were further screened out as the ferroptosis-related gene which was differentially expressed in OC. Then, comprehensive evaluations concerning gene expression, clinical implication, in vitro validation of expression and functional experiments, prediction of downstream molecules and related signal pathways, and immune-modulating function were performed. Results. PRNP was the only downregulated ferroptosis-related gene with prognostic value for OC patients. The decreased mRNA and protein expression was verified in OC tissues and cell lines. PRNP was significantly correlated with cancer stages, primary therapy outcomes, and age in OC patients. Moreover, we found that overexpression of PRNP inhibited the proliferation, migration, and invasion ability of OC cells through in vitro experiments. PRNP was enriched to the Ras signaling pathway. PRNP expression was positively correlated with the infiltration of immune cells, such as mast cells, T effector memory cells, plasmacytoid DC cells, NK cells, and eosinophils. In addition, the association of PRNP with other immune signatures was also found. Conclusion. This study demonstrated for the first time showed that ferroptosis-related gene PRNP exerted a tumor suppressive role in OC and the aberrant expression and function of PRNP making it a potential novel biomarker for OC diagnosis, prognosis, and response to immunotherapies.

COL11A1 serves as a biomarker for poor prognosis and correlates with immune infiltration in breast cancer

Breast cancer is the malignant tumor with the highest incidence rate at present, and its incidence rate ranks first in the female population. COL11A1 is an important component of collagen XI and is considered to play an important role in a variety of connective tissue diseases. Recent studies have shown that COL11A1 is associated with the occurrence and development of many kinds of malignant tumors. However, its prognostic value in breast cancer and its correlation with immune cell infiltration in tumor tissue are not clear. In this paper, we reveal the prognostic value of COL11A1 in breast cancer and its tumor immune-related function through in-depth bioinformatics analysis. The expression of COL11A1 is abnormally upregulated in breast cancer and is significantly related to the poor prognosis of breast cancer. In the analysis of the clinical characteristics of the patients, we found that the expression level of COLL11A1 was closely related to lymph node metastasis, PAM50 (Prediction Analysis of Microarray 50) expression, clinical stage and so on. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) all suggest that COL11A1 is related to tumor immunity. Further study found that the COL11A1 expression was significantly correlated with the degree of immune infiltration and the expression of a variety of immune cell markers in tumor tissue. More importantly, COL11A1 can affect the prognosis of breast cancer patients by participating in the regulation of tumor immune infiltration. Therefore, we believe that COL11A1 is a very potential target for diagnosis and treatment of breast cancer.

Predictive value of collagen in cancer

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.

Hsa_circRNA_0040462: a sensor of cells' response to CAP treatment with double-edged roles on breast cancer malignancy

Cold atmospheric plasma (CAP) represents a novel onco-therapeutic approach that has demonstrated its efficacy in many types of tumors. The efficacy of CAP is dose-dependent that determines the panel of tumors feasible for receiving CAP treatment under a certain parameter configuration. Identifying markers for easy and fast prognosis of tumors' sensitivity in response to CAP exposure is of critical value towards optimized therapeutic outcome, the lack of which has largely limited the translation of CAP into clinics. Circular RNAs represent a novel type of biomarkers for disease diagnosis that is featured by easy detection and stability. Through whole transcriptome sequencing, followed by in vitro validations, computational predictions and preliminary functional studies, we identified hsa_circRNA_0040462 as a sensor of breast cancer cells' response to CAP treatment. Yet we warrant the use of hsa_circRNA_0040462 as an onco-therapeutic target given its double-edged roles on breast cancer progression, i.e., suppressive on the growth and promotive on the migrative ability of triple negative breast cancer cells. Our study for the first time focused on markers prognostic of CAP's efficacy and tumors' sensitivity to CAP treatment under a certain parameter configuration, and reported hsa_circRNA_0040462 as a sensor of cells' response to CAP treatment. Also, the uncovered dual roles of hsa_circRNA_0040462 further advanced our knowledge on the complex yet critical regulatory functionalities of circular RNAs in cancer progression.

Solute carrier family 16 member 5 downregulation and its methylation might serve as a prognostic indicator of prostate cancer

Prostate cancer (PCa), characterized by high invasion, metastasis, and recurrence, is the most prevalent malignant tumor in men worldwide. A clear understanding of the underlying molecular mechanisms and their role during PCa tumorigenesis can help develop prognostic and targeted therapies. We analyzed datasets from public databases, including the Cancer Genome Atlas (TCGA) and Oncomine and Gene Expression Profiling Interactive Analysis for differential expression of solute carrier family 16 member 5 (SLC16A5). We further investigated its relationship with clinical stage, pathological grade, and prognosis of PCa. The promoter methylation level of SLC16A5 in PCa was also investigated by UALCAN. We also utilized datasets from UCSC Xena to explore the prognostic role of SLC16A5 methylation levels and CpG site. Correlations between SLC16A5 and immune infiltration were discovered through TIMER. We observed significantly lower levels of SLC16A5 mRNA in PCa relative to normal tissues across six datasets from Oncomine database (p < .001) and 498 cases from TCGA database (p < .0001). SLC16A5 is strongly negatively regulated by its DNA methylation, with a Spearman of -0.81 and Pearson of -0.80 (p < .001). The aberrant SLC16A5 expression resulted in a significant relationship with clinical stage, pathological grade, and lower SLC16A5 mRNA expression, and its hypermethylation was related to a poorer PCa prognosis. SLC16A5 acted as an important factor for PCa diagnosis, with an AUC of 0.9038 (95% CI: 0.8597-0.9479; p < .0001). Besides, the aberrant SLC16A5 expression revealed close correlations with multiple immune cells. Overall, these results indicate that decreased SLC16A5 expression might be a potential biomarker for determining prognosis and immune infiltration in PCa. The positive SLC16A5 modulation might be a promising therapeutic target for PCa.