Anoikis in phenotypic reprogramming of the prostate tumor microenvironment

Identification of anoikis-related gene signatures and construction of the prognosis model in prostate cancer

Background

One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated.

Methods

Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub).

Results

113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa.

Conclusion

We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.

Combating anoikis resistance: bioactive compounds transforming prostate cancer therapy

The study aims to discuss the challenges associated with treating prostate cancer (PCa), which is known for its complexity and drug resistance. It attempts to find differentially expressed genes (DEGs), such as those linked to anoikis resistance and circulating tumor cells, in PCa samples. This study involves analyzing the functional roles of these DEGs using gene enrichment analysis, and then screening of 102 bioactive compounds to identify a combination that can control the expression of the identified DEGs. In this study, 53 DEGs were identified from PCa samples including anoikis-resistant PCa cells and circulating tumor cells in PCa. Gene enrichment analysis with regards to functional enrichment of DEGs was performed. An inclusive screening process was carried out among 102 bioactive compounds to identify a combination capable of affecting and regulating the expression of selected DEGs. Eventually, gastrodin, nitidine chloride, chenodeoxycholic acid, and bilobalide were selected, as their combination demonstrated ability to modulate expression of 50 out of the 53 genes targeted. The subsequent analysis focused on investigating the biological pathways and processes influenced by this combination. The findings revealed a multifaceted and multidimensional approach to tumor regression. The combination of bioactive compounds exhibited effects on various genes including those related to production of inflammatory cytokines, cell proliferation, autophagy, apoptosis, angiogenesis, and metastasis. The current study has made a valuable contribution to the development of a combination of bioactive natural compounds that can significantly impede the development of treatment resistance in prostate tumor while countering the tumors' evasion of the immune system. The implications of this study are highly significant as it suggests the creation of an enhanced immunotherapeutic, natural therapeutic concoction with combinatorial potential.

Clinical value of molecular subtypes identification based on anoikis-related lncRNAs in castration-resistant prostate cancer

BACKGROUND

Anoikis is a distinctive type of apoptosis. It is involved in tumor progression and metastasis. But its function in castration-resistant prostate cancer (CRPC) remains veiled. We aimed to develop a prognostic indicator based on anoikis-related long non-coding RNAs (arlncRNAs) and to investigate their biological function in CRPC.

MATERIAL AND METHOD

Differentially expressed anoikis-related genes were extracted from two CRPC datasets, GSE51873, and GSE78201. Four lncRNAs associated with the anoikis-related genes were selected. A risk model based on these lncRNAs was developed and validated in The Cancer Genome Atlas (TCGA) and the Memorial Sloan-Kettering Cancer Center (MSKCC) prostate cancer cohorts. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, immune infiltration, immune checkpoints expression, and drug susceptibility were performed based on the model. To identify the biofunction of anoikis-related lncRNA, CCK-8 assays, colony formation assays, and flow cytometry were used.

RESULT

Twenty-nine anoikis-related genes were differentially expressed in the CRPC datasets. And 36 prognostic arlncRNAs were selected for the LASSO Cox analysis. Patients were subsequently classified into two subtypes by constructing an anoikis-related lncRNA based prognostic index (ARPI). The accuracy of this index was validated. KEGG enrichment analysis revealed that the high-ARPI group was enriched in cancer-related and immune-related pathways. Immune infiltration analysis has indicated a positive association between high-ARPI groups and increased immune infiltration. Fulvestrant, OSI-027, Lapatinib, Dabrafenib, and Palbociclib were identified as potential sensitive drugs for high-ARPI patients. In vitro experiments exhibited that silencing LINC01138 dampened the proliferation, migration and enzalutamide resistance in CRPC. Furthermore, it stimulated apoptosis and inhibited the eithelial-mesenchymal transition process.

CONCLUSION

Four arlncRNAs were identified and a risk model was established to predict the prognosis of patients with prostate cancer. Immune infiltration and drug susceptibility analysis revealed a potential therapeutic strategy for patients with castration-resistant prostate cancer.

Exploring the Role of the Gut and Intratumoral Microbiomes in Tumor Progression and Metastasis

Cancer cell dissemination involves invasion, migration, resistance to stressors in the circulation, extravasation, colonization, and other functions responsible for macroscopic metastases. By enhancing invasiveness, motility, and intravasation, the epithelial-to-mesenchymal transition (EMT) process promotes the generation of circulating tumor cells and their collective migration. Preclinical and clinical studies have documented intensive crosstalk between the gut microbiome, host organism, and immune system. According to the findings, polymorphic microbes might play diverse roles in tumorigenesis, cancer progression, and therapy response. Microbial imbalances and changes in the levels of bacterial metabolites and toxins promote cancer progression via EMT and angiogenesis. In contrast, a favorable microbial composition, together with microbiota-derived metabolites, such as short-chain fatty acids (SCFAs), can attenuate the processes of tumor initiation, disease progression, and the formation of distant metastases. In this review, we highlight the role of the intratumoral and gut microbiomes in cancer cell invasion, migration, and metastatic ability and outline the potential options for microbiota modulation. As shown in murine models, probiotics inhibited tumor development, reduced tumor volume, and suppressed angiogenesis and metastasis. Moreover, modulation of an unfavorable microbiome might improve efficacy and reduce treatment-related toxicities, bringing clinical benefit to patients with metastatic cancer.

The Prognosis of Cancer Depends on the Interplay of Autophagy, Apoptosis, and Anoikis within the Tumor Microenvironment

Within the tumor microenvironment, the fight between the immune system and cancer influences tumor transformation. Metastasis formation is an important stage in the progression of cancer. This process is aided by cellular detachment and resistance to anoikis, which are achieved by altering intercellular signaling. Autophagy, specifically pro-survival autophagy, aids cancer cells in developing treatment resistance. Numerous studies have shown that autophagy promotes tumor growth and resistance to anoikis. To regulate protective autophagy, cancer-related genes phosphorylate both pro- and anti-apoptotic proteins. Apoptosis, a type of controlled cell death, eliminates damaged or unwanted cells. Anoikis is a type of programmed cell death in which cells lose contact with the extracellular matrix. The dysregulation of these cellular pathways promotes tumor growth and spread. Apoptosis, anoikis, and autophagy interact meticulously and differently depending on the cellular circumstances. For instance, autophagy can protect cancer cells from apoptosis by removing cellular components that are damaged and might otherwise trigger apoptotic pathways. Similarly, anoikis dysregulation can trigger autophagy by causing cellular harm and metabolic stress. In order to prevent or treat metastatic disease, specifically, targeting these cellular mechanisms may present a promising prospect for cancer therapy. This review discourses the state of our understanding of the molecular and cellular mechanisms underlying tumor transformation and the establishment of metastatic tumors. To enhance the prognosis for cancer, we highlight and discuss potential therapeutic approaches that target these processes and genes involved in them.

Microbiota and the landscape of the prostate tumor microenvironment

Prostate cancer remains one of the most common causes of cancer-related death in men globally. Progression of prostate cancer to lethal metastatic disease is mediated by multiple contributors. The role of prostate microbiota and their metabolites in metastasis, therapeutic resistance to castration resistant prostate cancer (CRPC), and tumor relapse has yet to be fully investigated. Characterization of microflora can provide new mechanistic insights into the functional significance in the emergence of therapeutic resistance, identification of novel effective targeted therapies, and development of biomarkers during prostate cancer progression. The tumor microenvironment (TME) and its components work concurrently with the prostate microbiota in promoting prostate cancer development and progression to metastasis. In this article, we discuss the growing evidence on the functional contribution of microbiota to the phenotypic landscape of the TME and its effect on prostate cancer therapeutic targeting and recurrent disease.