Development and application of bioinformatics tools for discovery disease markers and disease targeting antibodies

Ph.DDOCTOR OF PHILOSOPH

Changes in inflammatory responses and autophagy during apheresis platelet preservation and their correlation with platelet transfusion refractoriness in patients with acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is a common hematopoietic malignancy, and platelet transfusion plays a crucial role in its treatment. This study aimed to investigate the changes in inflammatory response and autophagy during the preservation of apheresis platelets (AP) and their correlation with platelet transfusion refractoriness (PTR) in ALL. ALL patients were included, and APs were categorized based on the preservation period (day 0, day 1, days 2-3, and days 4-5). The activation factors procaspase-activating compound 1 (PAC-1) and P-selectin (CD62P), AP aggregation function, inflammation levels (interleukin 1 beta [IL-1β], interleukin 6 [IL-6], tumor necrosis factor alpha [TNF-α] and NOD-like receptor thermal protein domain associated protein 3 [NLRP3]), and autophagy-related genes (p62) during AP preservation were assessed. Following co-culturing APs with peripheral blood mononuclear cells (PBMCs), specific activation markers were studied to observe APs influence on immune cells activation. The effectiveness of platelet transfusion was assessed, and risk factors for PTR were analyzed. As the storage duration of AP increased, the activation factors, coagulation factor activity, inflammation levels, and the activation of immune cells in AP increased, while fibrinogen levels and AP aggregation function decreased. The expression levels of autophagy-related genes (the autophagy marker light chain 3B gene [LC3B] and Beclin 1 gene) decreased with prolongation preservation. The effective rate of AP transfusion in ALL patients was 68.21%. AP preservation time, IL-6, p62, and Beclin 1 were identified as independent risk factors affecting PTR in ALL patients. In conclusion, during AP preservation, inflammation, autophagy, and activation of immune cells were observed to increase. AP preservation time, IL-6, p62, and Beclin 1 were independent risk factors for PTR

A Balanced Feed Filtering Antenna With Novel Coupling Structure for Low-Sidelobe Radar Applications

A fourth-order filtering patch antenna with a novel coupling structure is presented in this paper. Using the proposed coupling structure, both the balanced coupling feed and cross-coupling are realized. Two identical slots etched on the ground plane are utilized to excite the radiating patch with the reduced cross-polarization level. A short slot etched on the ground plane is employed for cross-coupling, which introduces two controllable radiation nulls with a steep roll-off rate. In addition, owing to the split-ring resonators and hairpin resonators, the improved impedance bandwidth is achieved with the fourth-order filtering response. To demonstrate the proposed design techniques, both the filtering antenna element and the low-sidelobe array are designed, fabricated, and measured. The measured results show that the proposed antenna has the impedance bandwidth of 12% (4.78–5.39 GHz) with the total height of 0.06?0 , the cross-polarization level lower than ?31 dB, and two radiation nulls with the suppression higher than 31 dB. For the low-sidelobe antenna array, wide impedance bandwidth is also obtained with the sidelobe level below ?28.7 dB, the cross-polarization level below ?34 dB, and the out-of-band suppression better than 25 dB

Increased CK5/CK8-Positive Intermediate Cells with Stromal Smooth Muscle Cell Atrophy in the Mice Lacking Prostate Epithelial Androgen Receptor

Results from tissue recombination experiments documented well that stromal androgen receptor (AR) plays essential roles in prostate development, but epithelial AR has little roles in prostate development. Using cell specific knockout AR strategy, we generated pes-ARKO mouse with knock out of AR only in the prostate epithelial cells and demonstrated that epithelial AR might also play important roles in the development of prostate gland. We found mice lacking the prostate epithelial AR have increased apoptosis in epithelial CK8-positive luminal cells and increased proliferation in epithelial CK5-positive basal cells. The consequences of these two contrasting results could then lead to the expansion of CK5/CK8-positive intermediate cells, accompanied by stromal atrophy and impaired ductal morphogenesis. Molecular mechanism dissection found AR target gene, TGF-β1, might play important roles in this epithelial AR-to-stromal morphogenesis modulation. Collectively, these results provided novel information relevant to epithelial AR functions in epithelial-stromal interactions during the development of normal prostate, and suggested AR could also function as suppressor in selective cells within prostate

Neural protection by naturopathic compounds—an example of tetramethylpyrazine from retina to brain

Given the advantages of being stable in the ambient environment, being permeable to the blood–brain and/or blood–eye barriers and being convenient for administration, naturopathic compounds have growingly become promising therapeutic candidates for neural protection. Extracted from one of the most common Chinese herbal medicines, tetramethylpyrazine (TMP), also designated as ligustrazine, has been suggested to be neuroprotective in the central nervous system as well as the peripheral nerve network. Although the detailed molecular mechanisms of its efficacy for neural protection are understood limitedly, accumulating evidence suggests that antioxidative stress, antagonism for calcium, and suppression of pro-inflammatory factors contribute significantly to its neuroprotection. In animal studies, systemic administration of TMP (subcutaneous injection, 50 mg/kg) significantly blocked neuronal degeneration in hippocampus as well as the other vulnerable regions in brains of Sprague–Dawley rats following kainate-induced prolonged seizures. Results from us and others also demonstrated potent neuroprotective efficacy of TMP for retinal cells and robust benefits for brain in Alzheimer’s disease or other brain injury. These results suggest a promising prospect for TMP to be used as a treatment of specific neurodegenerative diseases. Given the assessment of the distribution, metabolism, excretion, and toxicity information that is already available on most neuroprotective naturopathic compounds such as TMP, it would not take much preclinical data to justify bringing such therapeutic compounds to clinical trials in humans

Identification of common oncogenic and early developmental pathways in the ovarian carcinomas controlling by distinct prognostically significant microRNA subsets

Abstract Background High-grade serous ovarian carcinoma (HG-SOC) is the dominant tumor histologic type in epithelial ovarian cancers, exhibiting highly aberrant microRNA expression profiles and diverse pathways that collectively determine the disease aggressiveness and clinical outcomes. However, the functional relationships between microRNAs, the common pathways controlled by the microRNAs and their prognostic and therapeutic significance remain poorly understood. Methods We investigated the gene expression patterns of microRNAs in the tumors of 582 HG-SOC patients to identify prognosis signatures and pathways controlled by tumor miRNAs. We developed a variable selection and prognostic method, which performs a robust selection of small-sized subsets of the predictive features (e.g., expressed microRNAs) that collectively serves as the biomarkers of cancer risk and progression stratification system, interconnecting these features with common cancer-related pathways. Results Across different cohorts, our meta-analysis revealed two robust and unbiased miRNA-based prognostic classifiers. Each classifier reproducibly discriminates HG-SOC patients into high-confidence low-, intermediate- or high-prognostic risk subgroups with essentially different 5-year overall survival rates of 51.6-85%, 20-38.1%, and 0-10%, respectively. Significant correlations of the risk subgroup’s stratification with chemotherapy treatment response were observed. We predicted specific target genes involved in nine cancer-related and two oocyte maturation pathways (neurotrophin and progesterone-mediated oocyte maturation), where each gene can be controlled by more than one miRNA species of the distinct miRNA HG-SOC prognostic classifiers. Conclusions We identified robust and reproducible miRNA-based prognostic subsets of the of HG-SOC classifiers. The miRNAs of these classifiers could control nine oncogenic and two developmental pathways, highlighting common underlying pathologic mechanisms and perspective targets for the further development of a personalized prognosis assay(s) and the development of miRNA-interconnected pathway-centric and multi-agent therapeutic intervention

Big data and computational biology strategy for personalized prognosis

The era of big data and precision medicine has led to accumulation of massive datasets of gene expression data and clinical information of patients. For a new patient, we propose that identification of a highly similar reference patient from an existing patient database via similarity matching of both clinical and expression data could be useful for predicting the prognostic risk or therapeutic efficacy.Here, we propose a novel methodology to predict disease/treatment outcome via analysis of the similarity between any pair of patients who are each characterized by a certain set of pre-defined biological variables (biomarkers or clinical features) represented initially as a prognostic binary variable vector (PBVV) and subsequently transformed to a prognostic signature vector (PSV). Our analyses revealed that Euclidean distance rather correlation distance measure was effective in defining an unbiased similarity measure calculated between two PSVs.We implemented our methods to high-grade serous ovarian cancer (HGSC) based on a 36-mRNA predictor that was previously shown to stratify patients into 3 distinct prognostic subgroups. We studied and revealed that patient's age, when converted into binary variable, was positively correlated with the overall risk of succumbing to the disease. When applied to an independent testing dataset, the inclusion of age into the molecular predictor provided more robust personalized prognosis of overall survival correlated with the therapeutic response of HGSC and provided benefit for treatment targeting of the tumors in HGSC patients.Finally, our method can be generalized and implemented in many other diseases to accurately predict personalized patients' outcomes.ASTAR (Agency for Sci., Tech. and Research, S’pore)Published versio

Additional file 3: Figure S1. of Identification of common oncogenic and early developmental pathways in the ovarian carcinomas controlling by distinct prognostically significant microRNA subsets

Three data-driven patient grouping methods. A: DDSS-1D method with a single cut-off value of a single prognostic variable (miRNA-222). It is an example of patient separation into relatively low- and high- risk subgroups; the cut-off value of miRNA-222 expression levels is defined at a minimum of the Wald statistics log (P-value) (left panel) for two K-M functions (right panel). This cut-off value separates patients into statistically significant survival subgroups. High expression level of the miRNA-222 (at cut-off value >5.56) corresponding to the relatively poor prognosis of the patient subgroup (red K-M curve; right panel). B: The DDSS-1D method uses two cut-off values within dynamic range of a single prognostic variable (miRNA-148b expression). The method uses 2 similar strongest minima of the log (P-value) function (left panel) separating patients into three statistically significant prognostic subgroups (right panel). C: A schema of the DDSS-2D method of patient’s grouping, using one cut-off value for each predictive variable in its domain. The method provides ‘the most significant/optimal’ patient’s grouping (at the smallest Wald statistics P-value) for the paired variables (miRNA pairs). The cut-off value for each of the miRNA is optimized via selection of the most significant/optimal variant of patient’s grouping. Seven possible grouping models of the paired data within the 2D domain can be indicated. D: The expression levels of the miRNA pair (let-7a and mir-130a) which separates the HG-SOC patients into two subgroups with grouping design 2. Figure S2. Cross validation analysis of the data-driven survival stratification system. Venn diagram analysis of the miRNA from three prognostic models: DDSS-SWV (SWVg, used 84 miRNAs, input data from DDSS-1D; Additional file 2: Table S2), DDSS-1D_10CV (DDSS-1D with ten-fold cross validation robustness, 25 miRNAs; Additional file 2: Table S3) and DDSS-2D (DDSS-2D, used top 52 miRNAs, having at least 50 synergistic miRNA pairs; Additional file 2: Table S4). The subset, which was common across these miRNA sets includes 19 miRNAs. This miRNA subset was used by SWVg to construct the19-miRNA prognostic signature. Figure S3. Correlation between two prognostic signatures: 19-miRNA prognostic classifier and 21-miRNA prognostic classifier. Figure S4. Significant canonical pathways using the algorithm of transcription regulation that was generated from the 19-miRNA and 31-miRNA prognostic signatures. Pathway data was generated using MetaCore, GeneGo, Inc. The detailed legend of the symbols can be found at https://portal.genego.com/legends/network_legend.html . A: Gene interconnection subnetwork putatively regulated by the miRNAs included into the 19-miRNA prognostic signature. B: Gene interconnection subnetwork formed by the miRNAs included into the 31-miRNA prognostic signature. Figure S5. Typical skewed frequency distribution of the number of miRNA:mRNA links. Data for the neurotrophin signaling pathway are presented. (PDF 606 kb