Highly robust model of transcription regulator activity predicts breast cancer overall survival

Background: While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes. Methods: Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome. Result: We built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients. Conclusion: Our findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression

Corrigendum: eIF3a Regulation of NHEJ Repair Protein Synthesis and Cellular Response to Ionizing Radiation

[This corrects the article DOI: 10.3389/fcell.2020.00753.]

Combinatorial analyses reveal cellular composition changes have different impacts on transcriptomic changes of cell type specific genes in Alzheimer’s Disease

Alzheimer’s disease (AD) brains are characterized by progressive neuron loss and gliosis. Previous studies of gene expression using bulk tissue samples often fail to consider changes in cell-type composition when comparing AD versus control, which can lead to differences in expression levels that are not due to transcriptional regulation. We mined five large transcriptomic AD datasets for conserved gene co-expression module, then analyzed differential expression and differential co-expression within the modules between AD samples and controls. We performed cell-type deconvolution analysis to determine whether the observed differential expression was due to changes in cell-type proportions in the samples or to transcriptional regulation. Our findings were validated using four additional datasets. We discovered that the increased expression of microglia modules in the AD samples can be explained by increased microglia proportions in the AD samples. In contrast, decreased expression and perturbed co-expression within neuron modules in the AD samples was likely due in part to altered regulation of neuronal pathways. Several transcription factors that are differentially expressed in AD might account for such altered gene regulation. Similarly, changes in gene expression and co-expression within astrocyte modules could be attributed to combined effects of astrogliosis and astrocyte gene activation. Gene expression in the astrocyte modules was also strongly correlated with clinicopathological biomarkers. Through this work, we demonstrated that combinatorial analysis can delineate the origins of transcriptomic changes in bulk tissue data and shed light on key genes and pathways involved in AD

eIF3a Regulation of NHEJ Repair Protein Synthesis and Cellular Response to Ionizing Radiation

Translation initiation in protein synthesis regulated by eukaryotic initiation factors (eIFs) is a crucial step in controlling gene expression. eIF3a has been shown to regulate protein synthesis and cellular response to treatments by anticancer agents including cisplatin by regulating nucleotide excision repair. In this study, we tested the hypothesis that eIF3a regulates the synthesis of proteins important for the repair of double-strand DNA breaks induced by ionizing radiation (IR). We found that eIF3a upregulation sensitized cellular response to IR while its downregulation caused resistance to IR. eIF3a increases IR-induced DNA damages and decreases non-homologous end joining (NHEJ) activity by suppressing the synthesis of NHEJ repair proteins. Furthermore, analysis of existing patient database shows that eIF3a expression associates with better overall survival of breast, gastric, lung, and ovarian cancer patients. These findings together suggest that eIF3a plays an important role in cellular response to DNA-damaging treatments by regulating the synthesis of DNA repair proteins and, thus, eIIF3a likely contributes to the outcome of cancer patients treated with DNA-damaging strategies including IR

Targeted immunotherapy for HER2-low breast cancer with 17p loss

The clinical challenge for treating HER2 (human epidermal growth factor receptor 2)-low breast cancer is the paucity of actionable drug targets. HER2-targeted therapy often has poor clinical efficacy for this disease due to the low level of HER2 protein on the cancer cell surface. We analyzed breast cancer genomics in the search for potential drug targets. Heterozygous loss of chromosome 17p is one of the most frequent genomic events in breast cancer, and 17p loss involves a massive deletion of genes including the tumor suppressor TP53 Our analyses revealed that 17p loss leads to global gene expression changes and reduced tumor infiltration and cytotoxicity of T cells, resulting in immune evasion during breast tumor progression. The 17p deletion region also includes POLR2A, a gene encoding the catalytic subunit of RNA polymerase II that is essential for cell survival. Therefore, breast cancer cells with heterozygous loss of 17p are extremely sensitive to the inhibition of POLR2A via a specific small-molecule inhibitor, α-amanitin. Here, we demonstrate that α-amanitin-conjugated trastuzumab (T-Ama) potentiated the HER2-targeted therapy and exhibited superior efficacy in treating HER2-low breast cancer with 17p loss. Moreover, treatment with T-Ama induced immunogenic cell death in breast cancer cells and, thereby, delivered greater efficacy in combination with immune checkpoint blockade therapy in preclinical HER2-low breast cancer models. Collectively, 17p loss not only drives breast tumorigenesis but also confers therapeutic vulnerabilities that may be used to develop targeted precision immunotherapy

MAL2 drives immune evasion in breast cancer by suppressing tumor antigen presentation

Immune evasion is a pivotal event in tumor progression. To eliminate human cancer cells, current immune checkpoint therapy is set to boost CD8+ T cell-mediated cytotoxicity. However, this action is eventually dependent on the efficient recognition of tumor-specific antigens via T cell receptors. One primary mechanism by which tumor cells evade immune surveillance is to downregulate their antigen presentation. Little progress has been made toward harnessing potential therapeutic targets for enhancing antigen presentation on the tumor cell. Here, we identified MAL2 as a key player that determines the turnover of the antigen-loaded MHC-I complex and reduces the antigen presentation on tumor cells. MAL2 promotes the endocytosis of tumor antigens via direct interaction with the MHC-I complex and endosome-associated RAB proteins. In preclinical models, depletion of MAL2 in breast tumor cells profoundly enhanced the cytotoxicity of tumor-infiltrating CD8+ T cells and suppressed breast tumor growth, suggesting that MAL2 is a potential therapeutic target for breast cancer immunotherapy

A Machine Learning-Based Histopathological Image Analysis Reveals Cancer Stemness in TNBCs with 17p Loss

Indiana University-Purdue University Indianapolis (IUPUI)Artificial intelligence and machine learning based methods have incorporated scientific research into clinical decision, leading to great improvement in clinical diagnosis and therapeutics. Here we developed a Convolutional Neural Network based model to identify cancer stem-like cells (CSCs) on H&E-stained histopathological images. Combined with cancer genomics profiles, our analysis revealed that triple negative breast cancers (TNBCs) with heterozygous deletion of chromosome 17p (17p-loss) correlate with higher cancer stemness potential compared to TNBCs with neural copy numbers of 17p (17p-intact). 17p-loss TNBC cells also have an increased percentage of CSCs and are resistant to chemotherapies compared with the 17p-intact TNBC cells. Moreover, we built a bioinformatics pipeline to screen compounds that target the stemness of 17p-loss cancer cells, one of which is FK866. FK866 promoted the antitumor activity of doxorubicin in the treatment of 17p-loss TNBCs. Our study provides a powerful computational tool for cancer image analysis as well as a feasible approach for precision cancer medicine.2024-05-2

Preparation and characterization of immunoglobulin yolk against the venom of <i style="">Naja naja atra</i>

778-785 Chinese Cobra (Naja naja atra) bite is one of the leading causes of snake-bite mortality in China. The traditional anti-cobra venom serum therapy was found to be expensive and with high frequency of side effects. Therefore attempts were made to generate a high titer immunoglobulin from egg yolk (IgY) of crude cobra-venom immunized Leghorn hens, and to standardize an effective method for producing avian antivenom in relatively pure form. The IgY was isolated first by water dilution method to remove the lipid, then extracted by ammonium sulfate precipitation, and purified through anion exchange chromatogram. The different purities of IgY from different isolating stages were submitted to enzyme-linked immunosorbent assay and SDS-PAGE to determine their titers. Immunoblotting showed that the purified IgY (ion exchange chromatography fraction, IECF) recognized several antigenic fractions of cobra venom, and presented with the character of polyclonal antibody. IECF on SDS-PAGE under reducing conditions migrated as a 65 kDa heavy chain and a 35 kDa light chain, respectively. The LD50 of the N. naja atra venom was 0.62 mg/kg body weight in mice. Four times the LD50 dose of venom was selected as challenge dose, and the ED50 of IgY was 3.04 mg IECF/mg venom. The results indicate that the activity of anti-snake venom IgY could be obviously elevated by ion exchange chromatography, thus possessing therapeutic significance for snakebite envenomation. </smarttagtype

Metabolic interventions: A new insight into the cancer immunotherapy

Metabolic reprogramming confers cancer cells plasticity and viability under harsh conditions. Such active alterations lead to cell metabolic dependency, which can be exploited as an attractive target in development of effective antitumor therapies. Similar to cancer cells, activated T cells also execute global metabolic reprogramming for their proliferation and effector functions when recruited to the tumor microenvironment (TME). However, the high metabolic activity of rapidly proliferating cancer cells can compete for nutrients with immune cells in the TME, and consequently, suppressing their anti-tumor functions. Thus, therapeutic strategies could aim to restore T cell metabolism and anti-tumor responses in the TME by targeting the metabolic dependence of cancer cells. In this review, we highlight current research progress on metabolic reprogramming and the interplay between cancer cells and immune cells. We also discuss potential therapeutic intervention strategies for targeting metabolic pathways to improve cancer immunotherapy efficacy

Thiodiketopiperazines from the Marine-Derived Fungus <i>Phoma</i> sp. OUCMDZ-1847

Three new thiodiketopiperazines, named phomazines A–C (<b>1</b>–<b>3</b>), along with 10 known analogues (<b>4</b>–<b>13</b>), were isolated from the fermentation broth of an endophytic fungus, <i>Phoma</i> sp. OUCMDZ-1847, associated with the mangrove plant <i>Kandelia candel</i>. The structures including the absolute configurations of the new compounds were unambiguously elucidated by spectroscopic, X-ray crystallographic, and Mosher’s methods along with quantum ECD and ¹³C NMR calculations. Compounds <b>2</b>, <b>4</b>, <b>5</b>, <b>11</b>, and <b>12</b> showed cytotoxicities against the HL-60, HCT-116, K562, MGC-803, and A549 cell lines with IC₅₀ values in the range 0.05 to 8.5 μM