Search

Because the incidence of breast cancer increases decades after ionizing radiation exposure, aging has been implicated in the evolution of the tumor microenvironment and tumor progression. Here, we investigated radiation-induced carcinogenesis using a model in which the mammary glands of 10-month-old BALB/c mice were transplanted with Trp53-null mammary tissue 3 days after exposure to low doses of sparsely ionizing γ-radiation or densely ionizing particle radiation. Mammary transplants in aged, irradiated hosts gave rise to significantly more tumors that grew more rapidly than those in sham-irradiated mice, with the most pronounced effects seen in mice irradiated with densely ionizing particle radiation. Tumor transcriptomes identified a characteristic immune signature of these aggressive cancers. Consistent with this, fast-growing tumors exhibited an immunosuppressive tumor microenvironment with few infiltrating lymphocytes, abundant immunosuppressive myeloid cells, and high COX-2 and TGFβ. Only irradiated hosts gave rise to tumors lacking cytotoxic CD8+ lymphocytes (defined here as immune desert), which also occurred in younger irradiated hosts. These data suggest that host irradiation may promote immunosuppression. To test this, young chimera mice were fed chow containing a honeybee-derived compound with anti-inflammatory and immunomodulatory properties, caffeic acid phenethyl ester (CAPE). CAPE prevented the detrimental effects of host irradiation on tumor growth rate, immune signature, and immunosuppression. These data indicated that low-dose radiation, particularly densely ionizing exposure of aged mice, promoted more aggressive cancers by suppressing antitumor immunity. Dietary intervention with a nontoxic immunomodulatory agent could prevent systemic effects of radiation that fuel carcinogenesis, supporting the potential of this strategy for cancer prevention.

Prostate cancer is the most common non-skin related cancer affecting 1 in 7 men in the United States. Treatment of patients with prostate cancer still remains a difficult decision-making process that requires physicians to balance clinical benefits, life expectancy, comorbidities, and treatment-related side effects. Gleason score (a sum of the primary and secondary Gleason patterns) solely based on morphological prostate glandular architecture has shown as one of the best predictors of prostate cancer outcome. Significant progress has been made on molecular subtyping prostate cancer delineated through the increasing use of gene sequencing. Prostate cancer patients with Gleason score of 7 show heterogeneity in recurrence and survival outcomes. Therefore, we propose to assess the correlation between histopathology images and genomic data with disease recurrence in prostate tumors with a Gleason 7 score to identify prognostic markers. In the study, we identify image biomarkers within tissue WSIs by modeling the spatial relationship from automatically created patches as a sequence within WSI by adopting a recurrence network model, namely long short-term memory (LSTM). Our preliminary results demonstrate that integrating image biomarkers from CNN with LSTM and genomic pathway scores, is more strongly correlated with patients recurrence of disease compared to standard clinical markers and engineered image texture features. The study further demonstrates that prostate cancer patients with Gleason score of 4+3 have a higher risk of disease progression and recurrence compared to prostate cancer patients with Gleason score of 3+4.

Low selenium levels have been linked to a higher incidence of cancer and other diseases, including Keshan, Chagas, and Kashin-Beck, and insulin resistance. Additionally, muscle and cardiovascular disorders, immune dysfunction, cancer, neurological disorders, and endocrine function have been associated with mutations in genes encoding for selenoproteins. Selenium biology is complex, and a systems biology approach to study global metabolomics, genomics, and/or proteomics may provide important clues to examining selenium-responsive markers in circulation. In the current investigation, we applied a global proteomics approach on plasma samples collected from a previously conducted, double-blinded placebo controlled clinical study, where men were supplemented with selenized-yeast (Se-Yeast; 300 μg/day, 3.8 μmol/day) or placebo-yeast for 48 weeks. Proteomic analysis was performed by iTRAQ on 8 plasma samples from each arm at baseline and 48 weeks. A total of 161 plasma proteins were identified in both arms. Twenty-two proteins were significantly altered following Se-Yeast supplementation and thirteen proteins were significantly changed after placebo-yeast supplementation in healthy men. The differentially expressed proteins were involved in complement and coagulation pathways, immune functions, lipid metabolism, and insulin resistance. Reconstruction and analysis of protein-protein interaction network around selected proteins revealed several hub proteins. One of the interactions suggested by our analysis, PHLD-APOA4, which is involved in insulin resistance, was subsequently validated by Western blot analysis. Our systems approach illustrates a viable platform for investigating responsive proteomic profile in 'before and after' condition following Se-Yeast supplementation. The nature of proteins identified suggests that selenium may play an important role in complement and coagulation pathways, and insulin resistance.

Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention data integration across omics-es. In the present study, transcriptomics data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with protein-protein interaction data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active protein-protein interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.

Triple negative breast cancer (TNBC) represents approximately 15% of breast cancers and is characterized by lack of expression of both estrogen receptor (ER) and progesterone receptor (PR), together with absence of human epidermal growth factor 2 (HER2). TNBC has attracted considerable attention due to its aggressiveness such as large tumor size, high proliferation rate, and metastasis. The absence of clinically efficient molecular targets is of great concern in treatment of patients with TNBC. In light of the complexity of TNBC, we applied a systematic and integrative transcriptomics and interactomics approach utilizing transcriptional regulatory and protein-protein interaction networks to discover putative transcriptional control mechanisms of TNBC. To this end, we identified TNBC-driven molecular pathways such as the Janus kinase-signal transducers, and activators of transcription (JAK-STAT) and tumor necrosis factor (TNF) signaling pathways. The multi-omics molecular target and biomarker discovery approach presented here can offer ways forward on novel diagnostics and potentially help to design personalized therapeutics for TNBC in the future.