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1.
Int J Mol Sci ; 25(6)2024 Mar 14.
Artículo en Inglés | MEDLINE | ID: mdl-38542265

RESUMEN

Prostate cancer is the second leading cause of death in males in America, with advanced prostate cancers exhibiting a 5-year survival rate of only 32%. Castration resistance often develops during the course of treatment, but its pathogenesis is poorly understood. This study explores the human microbiome for its implications in castration resistance and metastasis in prostate cancer. RNA sequencing data were downloaded for the bone and soft tissue biopsies of patients with metastatic castration-resistant prostate cancer. These included both metastatic and adjacent normal biopsies. These sequences were mapped to bacterial sequences, yielding species-level counts. A vast majority of species were found to be significantly underabundant in the CRPC samples. Of these, numerous were found to correlate with the expression of known markers of castration resistance, including AR, PI3K, and AKT. Castration resistance-associated signaling pathways were also enriched with these species, including PI3K-AKT signaling and endocrine resistance. For their implications in cancer aggression and metastasis, cancer stem cell markers were further explored for a relation to these species. EGFR and SLC3A2 were widely downregulated, with a greater abundance of most species. Our results suggest that the microbiome is heavily associated with castration resistance and stemness in prostate cancer. By considering the microbiome's importance in these factors, we may better understand the highly aggressive and highly invasive nature of castration-resistant prostate cancer, allowing for the needed improvements in the treatment of this disease.


Asunto(s)
Neoplasias de la Próstata Resistentes a la Castración , Masculino , Humanos , Neoplasias de la Próstata Resistentes a la Castración/patología , Proteínas Proto-Oncogénicas c-akt/metabolismo , Fosfatidilinositol 3-Quinasas , Disbiosis , Castración , Receptores Androgénicos/metabolismo
2.
Cancers (Basel) ; 16(2)2024 Jan 17.
Artículo en Inglés | MEDLINE | ID: mdl-38254883

RESUMEN

There are a total of 82,290 new cases and 16,710 deaths estimated for bladder cancer in the United States in 2023. Currently, urine cytology tests are widely used for bladder cancer diagnosis, though they suffer from variable sensitivity, ranging from 45 to 97%. More recently, the microbiome has become increasingly recognized for its role in human diseases, including cancers. This study attempts to characterize urinary microbiome bladder cancer-specific dysbiosis to explore its diagnostic potential. RNA-sequencing data of urine samples from patients with bladder cancer (n = 18) and matched controls (n = 12) were mapped to bacterial sequences to yield species-level abundance approximations. Urine samples were analyzed at both the population and species level to reveal dysbiosis associated with bladder cancer. A panel of 35 differentially abundant species was discovered, which may be useful as urinary biomarkers for this disease. We further assessed whether these species were of similar significance in a validation dataset (n = 81), revealing that the genera Escherichia, Acinetobacter, and Enterobacter were consistently differentially abundant. We discovered distinct patterns of microbial-associated immune modulation in these samples. Several immune pathways were found to be significantly enriched with respect to the abundance of these species, including antigen processing and presentation, cytosolic DNA sensing, and leukocyte transendothelial migration. Differential cytokine activity was similarly observed, suggesting the urinary microbiome's correlation to immune modulation. The adherens junction and WNT signaling pathways, both implicated in the development and progression of bladder cancer, were also enriched with these species. Our findings indicate that the urinary microbiome may reflect both microbial and immune dysregulations of the tumor microenvironment in bladder cancer. Given the potential biomarker species identified, the urinary microbiome may provide a non-invasive, more sensitive, and more specific diagnostic tool, allowing for the earlier diagnosis of patients with bladder cancer.

3.
Cancers (Basel) ; 14(24)2022 Dec 15.
Artículo en Inglés | MEDLINE | ID: mdl-36551675

RESUMEN

Human Papilloma Virus (HPV) is highly prevalent within the U.S., with studies estimating that over 80% of individuals will contract the virus in their lifetime. HPV is considered a primary risk factor for the development and progression of oropharyngeal cancers. The impact of the HPV virus's E6 and E7 oncoproteins on cellular signaling pathways and genomic integration has been extensively characterized. Indirect genomic effects; however, remain relatively unidentified. In this study, we analyzed 83 HPV+ Head and Neck Squamous Cell Carcinoma (HNSCC) patients of varying HPV types. Expression counts of the HPV E6 and E7 oncogenes were estimated across samples and correlated with genomic mutational classes. High expression of E6 and E7 oncoproteins was associated with a greater number of total point mutations, especially on chromosomes 1, 11, and 17, which have been implicated in HPV-mediated cancers in previous studies. Samples with high E6 and E7 expression also exhibited more frequent non-clustered structural variation and a lack of clustered variation altogether. Copy number segments were present with fewer number of repeats in high E6 and E7 expression samples, which is known to correlate with decreased expression of affected genes. E6 and E7 expression was associated with increased activity of several cellular pathways associated in oncogenesis and telomere maintenance. In comprehensively characterizing the effects of the HPV oncoproteins on the human genome, potential mechanisms of HNSCC pathogenesis may be further elucidated.

4.
Int J Mol Sci ; 23(21)2022 Oct 31.
Artículo en Inglés | MEDLINE | ID: mdl-36362038

RESUMEN

Head and neck squamous cell carcinoma (HNSCC) tumor phenotypes and clinical outcomes are significantly influenced by etiological agents, such as HPV infection, smoking, and alcohol consumption. Accordingly, the intratumor microbiome has been increasingly implicated in cancer progression and metastasis. However, few studies characterize the intratumor microbial landscape of HNSCC with respect to these etiological agents. In this study, we aimed to investigate the bacterial and fungal landscape of HNSCC in association with HPV infection, smoking, and alcohol consumption. RNA-sequencing data were extracted from The Cancer Genome Atlas (TCGA) regarding 449 tissue samples and 44 normal samples. Pathoscope 2.0 was used to extract the microbial reads. Microbe abundance was compared to clinical variables, oncogenic signatures, and immune-associated pathways. Our results demonstrated that a similar number of dysregulated microbes was overabundant in smokers and nonsmokers, while heavy drinkers were characterized by an underabundance of dysregulated microbes. Conversely, the majority of dysregulated microbes were overabundant in HPV+ tumor samples when compared to HPV- tumor samples. Moreover, we observed that many dysregulated microbes were associated with oncogenic and metastatic pathways, suggesting their roles in influencing carcinogenesis. These microbes provide insights regarding potential mechanisms for tumor pathogenesis and progression with respect to the three etiological agents.


Asunto(s)
Neoplasias de Cabeza y Cuello , Micobioma , Infecciones por Papillomavirus , Humanos , Carcinoma de Células Escamosas de Cabeza y Cuello/complicaciones , Papillomaviridae/genética , Neoplasias de Cabeza y Cuello/complicaciones , Fumar/efectos adversos , Consumo de Bebidas Alcohólicas/efectos adversos
5.
Int J Mol Sci ; 23(19)2022 Sep 30.
Artículo en Inglés | MEDLINE | ID: mdl-36232866

RESUMEN

The human microbiome is a vast collection of microbial species that exist throughout the human body and regulate various bodily functions and phenomena. Of the microbial species that exist in the human microbiome, those within the archaea domain have not been characterized to the extent of those in more common domains, despite their potential for unique metabolic interaction with host cells. Research has correlated tumoral presence of bacterial microbial species to the development and progression of lung cancer; however, the impacts and influences of archaea in the microbiome remain heavily unexplored. Within the United States lung cancer remains highly fatal, responsible for over 100,000 deaths every year with a 5-year survival rate of roughly 22.9%. This project attempts to investigate specific archaeal species' correlation to lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) incidence, patient staging, death rates across individuals of varying ages, races, genders, and smoking-statuses, and potential molecular targets associated with archaea microbiome. Archaeal species abundance was assessed across lung tissue samples of 527 LUAD patients, 479 LUSC patients, and 99 healthy individuals. Nine archaeal species were found to be of significantly altered abundance in cancerous samples as compared to normal counterparts, 6 of which are common to both LUAD and LUSC subgroups. Several of these species are of the taxonomic class Thermoprotei or the phylum Euryarchaeota, both known to contain metabolic processes distinct from most bacterial species. Host-microbe metabolic interactions may be responsible for the observed correlation of these species' abundance with cancer incidence. Significant microbes were correlated to patient gene expression to reveal genes of altered abundance with respect to high and low archaeal presence. With these genes, cellular oncogenic signaling pathways were analyzed for enrichment across cancer and normal samples. In comparing gene expression between LUAD and adjacent normal samples, 2 gene sets were found to be significantly enriched in cancers. In LUSC comparison, 6 sets were significantly enriched in cancer, and 34 were enriched in normals. Microbial counts across healthy and cancerous patients were then used to develop a machine-learning based predictive algorithm, capable of distinguishing lung cancer patients from healthy normal with 99% accuracy.


Asunto(s)
Adenocarcinoma del Pulmón , Carcinoma de Pulmón de Células no Pequeñas , Carcinoma de Células Escamosas , Neoplasias Pulmonares , Microbiota , Adenocarcinoma del Pulmón/patología , Archaea/genética , Carcinoma de Pulmón de Células no Pequeñas/genética , Carcinoma de Células Escamosas/patología , Femenino , Humanos , Neoplasias Pulmonares/patología , Masculino , Microbiota/genética
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