miR-433 Inhibits Glioblastoma Progression by Suppressing the PI3K/Akt Signaling Pathway Through Direct Targeting of ERBB4.

Glioblastoma multiforme (GBM) is a highly malignant brain tumor where new biomarkers and drug targets are much needed in the oncology clinic. miR-433 was identified as a tumor-suppressing miRNA in several different types of human cancer. However, the integrative biology of miR-433 in GBM is still largely unknown. By analyzing the expression profiles of miR-433 in 198 patients with glioma at The Cancer Genome Atlas, we found that the miR-433 expression was decreased in glioma whereas the low expression of miR-433 was significantly associated with shorter overall survival. We then conducted in vitro studies and demonstrated that increased expression of miR-433 suppressed the proliferation, migration, and invasion of LN229 and T98G cells, two representative glioma cell lines. Further, using in vivo mouse model, we found that upregulation of miR-433 inhibited the tumor growth of glioma cells. To situate the integrative biology understanding of the action of miR-433 in glioma, we identified ERBB4 as a gene targeted directly by miR-433 in LN229 and T98G cells. Overexpressed ERBB4 rescued the phenotype caused by overexpression of miR-433. Finally, we showed that miR-433 suppressed the PI3K/Akt pathway in glioma cells. In conclusion, our study demonstrated that miR-433 could potentially act as a tumor suppressor for GBM and may serve as a potential therapeutic target for GBM. Further integrative biology and clinical translational research are warranted to evaluate miR-433 in GBM.

Immunological Findings in a Group of Individuals Who Were Poor or Non-Responders to Standard Two-Dose SARS-CoV-2 Vaccines.

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a pandemic. However, data on the poor or non-responders to SARS-CoV-2 vaccines in the general population are limited. The objective of this study was to comprehensively compare the immunological characteristics of poor or non-responders to SARS-CoV-2 vaccines in the 18-59-year group with those in the ≥60-year group using internationally recognized cut-off values. The main outcome was effective seroconversion characterized by an anti-SARS-CoV-2 spike IgG level of at least a four-fold increase from baseline. Profiling of naïve immune cells was analyzed prior to vaccination to demonstrate baseline immunity. The outcomes of effective seroconversion in patients aged 18-59 years with those in patients aged ≥60 years were compared. The quantitative level of anti-spike IgG was significantly lower in individuals aged ≥60 and men aged 18-59 years. There were 7.5% of poor or non-responders among the 18-59 years and 11.7% of poor or non-responders in the ≥60 years using a four-fold increase parameter. There were 37.0-58.1% with low lymphocyte count (<1000/mm3), 33.3-45.2% with low CD4 cell counts (<500/mm3), and 74.1-96.8% with low B cell counts (<100/mm3) in the non-seroconversion group. An individual with an anti-SARS-CoV-2 spike IgG titer below 50 BAU/mL might be considered a poor or non-responder between 14 and 90 days after the last vaccine dose. Booster vaccination or additional protective measures should be recommended to poor or non-responders as soon as possible to reduce disease severity and mortality.

Comparison of immune response to SARS-COV-2 vaccine in COVID-recovered versus non-infected Individuals.

To determine the antibody levels at 6 months in SARS-CoV-2 vaccinated individuals in COVID-recovered versus non-infected groups to determine the need to administer booster COVID vaccine in each group. Prospective longitudinal study. Pathology Department, Combined Military Hospital, Lahore for a period of eight months from July 2021 to February 2022. Two hundred and thirty three study participants in both COVID recovered and non-infected groups (105 participants in infected group, 128 participants in non-infected group) were subjected to blood sampling at 6 months post-vaccination. Anti-SARS-CoV-2 IgG antibody test was done using Chemiluminescence method. Comparison of antibody levels between COVID-recovered and non-infected groups was made. Results were compiled and statistically analyzed using SPSS version 21. Out of 233 study participants, males were 183 (78%) while females were 50 (22%), mean age being 35.93 years ± 8.298. Mean Anti-SARS-CoV-2 S IgG levels among COVID-recovered group was 1342 U/ml and among non-infected group was 828 U/ml at 6 months post-vaccination. Mean antibody titers in COVID-19 recovered group are higher than in non-infected group at 6 months post-vaccination in both groups.

Multi-Omics and Artificial Intelligence-Guided Data Integration in Chronic Liver Disease: Prospects and Challenges for Precision Medicine.

Chronic liver disease (CLD) is a significant planetary health burden. CLD includes a broad range of liver pathologies from different causes, for example, hepatitis B virus infection, fatty liver disease, hepatocellular carcinoma, and nonalcoholic fatty liver disease or the metabolic associated fatty liver disease. Biomarker and diagnostic discovery, and new molecular targets for precision treatments are timely and sorely needed in CLD. In this context, multi-omics data integration is increasingly being facilitated by artificial intelligence (AI) and attendant digital transformation of systems science. While the digital transformation of multi-omics integrative analyses is still in its infancy, there are noteworthy prospects, hope, and challenges for diagnostic and therapeutic innovation in CLD. This expert review aims at the emerging knowledge frontiers as well as gaps in multi-omics data integration at bulk tissue levels, and those including single cell-level data, gut microbiome data, and finally, those incorporating tissue-specific information. We refer to AI and related digital transformation of the CLD research and development field whenever possible. This review of the emerging frontiers at the intersection of systems science and digital transformation informs future roadmaps to bridge digital technology discovery and clinical omics applications to benefit planetary health and patients with CLD.

Digital Transformation in Personalized Medicine with Artificial Intelligence and the Internet of Medical Things.

Digital transformation is impacting every facet of science and society, not least because there is a growing need for digital services and products with the COVID-19 pandemic. But the need for digital transformation in diagnostics and personalized medicine field cuts deeper. In the past, personalized/precision medicine initiatives have been unable to capture the patients' experiences and clinical outcomes in real-time and in real-world settings. The availability of wearable smart sensors, wireless connectivity, artificial intelligence, and the Internet of Medical Things is changing the personalized/precision medicine research and implementation landscape. Digital transformation in poised to accelerate personalized/precision medicine and systems science in multiple fronts such as deep real-time phenotyping with patient-reported outcomes, high-throughput association studies between omics and highly granular phenotypic variation, digital clinical trials, among others. The present expert review offers an analysis of these systems science frontiers with a view to future applications at the intersection of digital health and personalized medicine, or put in other words, signaling the rise of "digital personalized medicine."

Expression of 5-methylcytosine regulators is highly associated with the clinical phenotypes of prostate cancer and DNMTs expression predicts biochemical recurrence.

In patients with prostate cancer (PCa), there is a high rate of overdiagnosis and frequent overtreatment. Therefore, there is an urgent need for more accurate prediction of biochemical recurrence (BCR). DNA methylation regulation patterns play crucial roles in tumorigenicity, progression, and treatment efficacy in PCa. However, the global relationship between epigenetic alterations, changes in mRNA levels, and pathologic phenotypes of PCa remain largely undefined. Here, we conducted a systematic analysis to identify global coexpression and comethylation modules in PCa. We identified coregulated methylation and expression modules and the relationships between epigenetic modifications, tumor progression, and the corresponding immune microenvironment in PCa. Our results show that DNA methyltransferases (DNMTs) are strongly associated with pathologic phenotypes and immune infiltration patterns in PCa. We built a two-factor predictive model using the expression features of DNMT3B and DNMT1. The model was used to predict the BCR status of patients with PCa and achieved area under the receiver operating characteristic curve values of 0.70 and 0.88 in the training and independent testing datasets, respectively.

Exome sequencing identified six copy number variations as a prediction model for recurrence of primary prostate cancers with distinctive prognosis.

BACKGROUND: Prostate cancer (PCa) is a common type of malignancy, which represents one of the leading causes of death among men worldwide. Copy number variations (CNVs) and gene fusions play important roles in PCa and may serve as markers for the prognosis of this condition. METHODS: We have presently conducted an analysis of CNVs and gene fusions in PCa, using whole exome sequencing (WES) data of primary tumors. For this, a cohort of 74 PCa patients, including 30 recurrent and 44 non-recurrent cases, were assessed during 5 years of follow-up. RESULTS: We have identified 66 CNVs that were specific to the primary tumor tissues from the recurrent PCa group. Most of duplicated genomic regions were located in 8q2, suggesting that this chromosomal region could be important for the prognosis of PCa. Meanwhile, we have developed a random forest model, using six selected CNVs, with an accuracy near 90% for predicting PCa recurrence according to a 10-fold cross validation. In addition, we have detected 16 recurrent oncogenic gene fusions in PCa. Among these, ALK (ALK receptor tyrosine kinase)-involved fusions were the most common type of gene fusion (n=7). Four of these fusions (i.e., EML4-ALK, STRN-ALK, CLTC-ALK, ETV6-ALK) were previously identified in other cancer types, while the remaining three gene fusions (FRYL-ALK, ABL1-ALK, and BCR-ALK) were here identified. CONCLUSIONS: Our findings expand the current understanding in regard to prostate carcinogenesis. Current data might be further used for assay development as well as to predict PCa recurrence, using primary tissues.

Whole Exome Sequencing Identifies Putative Predictors of Recurrent Prostate Cancer with High Accuracy.

Prostate cancer (PCa) is a highly common cancer among men but lacks robust diagnostics that can predict disease recurrence after initial treatment, for example, with radical prostatectomy. Recent advances in genomics and next-generation sequencing heralded the discovery of biomarkers such as the androgen receptor gene (AR) splice events, the TMPRSS2:EGR gene fusion, long noncoding RNA MALAT-1 and SCHLAP1 for PCa prognosis. Still, the question of why some patients experience recurrence, whereas others do not introduce marked uncertainty for both patients and physicians. We report here the whole exome sequencing of 30 recurrent and 44 nonrecurrent PCa patients. We identified 72 and 34 specific somatic single nucleotide variations in the recurrent and the nonrecurrent group, respectively, and developed a classification model to forecast PCa recurrence using a random forest model. The model displayed a sensitivity and specificity of 87.8% and 94.4%, respectively, for identifying the patients with recurrent PCa. These observations warrant further research in independent and larger clinical samples so as to inform future diagnostics innovation for PCa prognosis and recurrence.

Novel Serum Biomarkers for Noninvasive Diagnosis and Screening of Nonalcoholic Fatty Liver Disease-Related Hepatic Fibrosis.

Nonalcoholic fatty liver disease (NAFLD) is a growing global public health concern and becoming the leading cause of liver disease worldwide. The estimated global prevalence of NAFLD is ∼25% depending on the country and the assessment method used to establish the diagnosis. Meta-analyses suggest that the highest prevalence is in the Middle East (31.8%) and South America (30.4%), and the lowest in Africa (13.5%). In the United States, between 75 and 100 million individuals were estimated to have NAFLD. This important disease is associated with increased incidence of liver-related deaths, hepatocarcinoma, and overall mortality. Fibrosis stage, among other histological characteristics, is the most critical factor in predicting all-cause and disease-specific mortality in NAFLD. The ability to detect fibrosis early in NAFLD patients is critical in controlling mortality associated with this highly prevalent disease. We present here an expert review on recent advances in novel blood biomarkers, for example, the Wisteria floribunda agglutinin-positive mac-2 binding protein (WFA+-M2BP), type IV collagen 7S, chitinase 3 like 1 (CHI3L1; YKL-40), and insulin-like growth factor-1 (IGF-1). Algorithms using multiple biomarkers such as alpha-2-macroglobulin, mir34a, YKL-40, and hemoglobin A1c (HbA1c; NIS4), enhanced liver fibrosis (ELF), Hepascore, FibroMeter, FibroTest, FIBROSpect, FIB-C3, and ADPAPT are highlighted. Novel technologies such as tandem mass spectrometry to directly measure protein turnover rate of the key proteins involved in hepatic fibrosis, as an indicator of fibrogenesis, are also discussed. In conclusion, NAFLD is a growing global health problem that warrants long-term funding, research, and training of scholars across the fields of public health diagnostics, systems sciences, nutrition, hepatology, and clinical oncology.

CHI3L1 promotes tumor progression by activating TGF-ß signaling pathway in hepatocellular carcinoma.

CHI3L1 (YKL40) is a secreted glycoprotein and elevated serum CHI3L1 level has been proved to be associated with poor prognosis in many human cancers. However, the mechanism of how CHI3L1 causes poor prognosis in cancers is still unknown. Here, considering that CHI3L1 is a liver specific/enriched protein, we use hepatocellular carcinoma as a model to study the function of CHI3L1. We showed that, both in vivo and in vitro, overexpression of CHI3L1 could promote liver cancer cells growth, migration and invasion. We then used RNA-seq to analyze the expression profiles of CHI3L1 overexpressed in two HCC cell lines and found that CHI3L1 overexpression affected genes that were involved in cell-cell adhesion, extracellular exosome and adherens junction. Western blot analysis further revealed that CHI3L1 could activate TGF-ß signal pathways. Our data added new understanding of the mechanism of CHI3L1's action. 1) CHI3L1 promoted cancer cell proliferation by regulating cell cycles; 2) CHI3L1 promoted cancer cell invasion and metastasis; 3) CHI3L1 regulate liver cancer potentially by regulating the TGF-ß signaling pathways; 4) CHI3L1 has direct kinase activities or activate kinase to phosphorylate SMAD2, SMAD3.

The comparison genomics analysis with glioblastoma multiforme (GBM) cells under 3D and 2D cell culture conditions.

GBM, the most common and aggressive malignant primary brain tumors which needs new research approach to reveal the underline molecular mechanism of tumor progression. The 3D in vitro tumor model can be a simple and effective way to study tumor characteristics with ability to replicate of the tumor milieu. In the current study, we adopted the DNA microarray to analyze the gene expression of GBM tumor cells cultured under 2D cell culture flasks and 3D PLA porous scaffolds for 4,7 and 14 days. For 14 day old cultures, 8117 and 3060 genes expression were upregulated and downregulated respectively. Further KEGG pathway analysis revealed, the upregulated genes were mainly enriched/involved in PPAR and PI3K-Akt signaling pathways whereas the downregulated genes were mainly contributed in metabolism, ECM related and TGF-beta pathways. Thus, our approach of establishing 3D in vitro tumor model provides realistic results and proves itself a powerful tool for understanding the inner nature of GBM and can be considered as potential platform for drug screening.

An androgen response element driven reporter assay for the detection of androgen receptor activity in prostate cells.

The androgen receptor (AR) transcription factor plays a key role in the development and progression of prostate cancer, as is evident from the efficacy of androgen-deprivation therapy, AR is also the most frequently mutated gene, in castration resistant prostate cancer (CRPC). AR has therefore become an even more attractive therapeutic target in aggressive and disseminated prostate cancer. To investigate mechanisms of AR and AR target gene activation in different subpopulations of prostate cancer cells, a toolkit of AR expressor and androgen response element (ARE) reporter vectors were developed. Three ARE reporter vectors were constructed with different ARE consensus sequences in promoters linked to either fluorescence or luciferase reporter genes in lentiviral vector backbones. Cell lines transduced with the different vectors expressed the reporters in an androgen-dependent way according to fluorescence microscopy, flow cytometry and multi-well fluorescent and luminescence assays. Interestingly, the background reporter activity in androgen-depleted medium was significantly higher in LNCaP cells compared to the prostate transit amplifying epithelial cell lines, EP156T-AR and 957E/hTERT-AR with exogenous AR. The androgen-induced signal to background was much higher in the latter benign prostate cells than in LNCaP cells. Androgen-independent nuclear localization of AR was seen in LNCaP cells and reduced ARE-signaling was seen following treatment with abiraterone, an androgen synthesis inhibitor. The ARE reporter activity was significantly stronger when stimulated by androgens than by ß-estradiol, progesterone and dexamethasone in all tested cell types. Finally, no androgen-induced ARE reporter activity was observed in tumorigenic mesenchymal progeny cells of EP156T cells following epithelial to mesenchymal transition. This underscores the observation that expression of the classical luminal differentiation transcriptome is restricted in mesenchymal type cells with or without AR expression, and presence of androgen.

Whole genome sequencing of matched tumor, adjacent non-tumor tissues and corresponding normal blood samples of hepatocellular carcinoma patients revealed dynamic changes of the mutations profiles during hepatocarcinogenesis.

Hepatocellular carcinoma (HCC) has become the third most deadly disease worldwide and HBV is the major factor in Asia and Africa. We conducted 9 WGS (whole genome sequencing) analyses for matched samples of tumor, adjacent non-tumor tissues and normal blood samples of HCC patients from three HBV positive patients. We then validated the mutations identified in a larger cohort of 177 HCC patients. We found that the number of the unique somatic mutations (average of 59,136) in tumor samples is significantly less than that in adjacent non-tumor tissues (average 83, 633). We discovered that the TP53 R249S mutation occurred in 7.7% of the HCC patients, and it was significantly associated with poor diagnosis. In addition, we found that the L104P mutation in the VCX gene (Variable charge, X-linked) was absent in white blood cell samples, but present at 11.1% frequency in the adjacent tissues and increased to 14.6% in HCC tissues, suggesting that this mutation might be a tumor driver gene driving HCC carcinogenesis. Finally, we identified a TK1-RNU7 fusion, which would result in a deletion of 103 amino acids from its C-terminal. The frequencies of this fusion event decreased from the adjacent tissues (29.2%) to the tumors (16.7%), suggesting that a truncated thymidine Kinase1 (TK1) caused by the fusion event might be deleterious and be selected against during tumor progression. The three-way comparisons allow the identification of potential driver mutations of carcinogenesis. Furthermore, our dataset provides the research community a valuable dataset for identifying dynamic changes of mutation profiles and driver mutations for HCC.

Axitinib blocks Wnt/ß-catenin signaling and directs asymmetric cell division in cancer.

Oncogenic mutations of the Wnt (wingless)/ß-catenin pathway are frequently observed in major cancer types. Thus far, however, no therapeutic agent targeting Wnt/ß-catenin signaling is available for clinical use. Here we demonstrate that axitinib, a clinically approved drug, strikingly blocks Wnt/ß-catenin signaling in cancer cells, zebrafish, and Apc(min/+) mice. Notably, axitinib dramatically induces Wnt asymmetry and nonrandom DNA segregation in cancer cells by promoting nuclear ß-catenin degradation independent of the GSK3ß (glycogen synthase kinase3ß)/APC (adenomatous polyposis coli) complex. Using a DARTS (drug affinity-responsive target stability) assay coupled to 2D-DIGE (2D difference in gel electrophoresis) and mass spectrometry, we have identified the E3 ubiquitin ligase SHPRH (SNF2, histone-linker, PHD and RING finger domain-containing helicase) as the direct target of axitinib in blocking Wnt/ß-catenin signaling. Treatment with axitinib stabilizes SHPRH and thereby increases the ubiquitination and degradation of ß-catenin. Our findings suggest a previously unreported mechanism of nuclear ß-catenin regulation and indicate that axitinib, a clinically approved drug, would provide therapeutic benefits for cancer patients with aberrant nuclear ß-catenin activation.

Context dependent regulatory patterns of the androgen receptor and androgen receptor target genes.

BACKGROUND: Expression of the androgen receptor (AR) is associated with androgen-dependent proliferation arrest and terminal differentiation of normal prostate epithelial cells. Additionally, activation of the AR is required for survival of benign luminal epithelial cells and primary cancer cells, thus androgen deprivation therapy (ADT) leads to apoptosis in both benign and cancerous tissue. Escape from ADT is known as castration-resistant prostate cancer (CRPC). In the course of CRPC development the AR typically switches from being a cell-intrinsic inhibitor of normal prostate epithelial cell proliferation to becoming an oncogene that is critical for prostate cancer cell proliferation. A clearer understanding of the context dependent activation of the AR and its target genes is therefore desirable. METHODS: Immortalized human prostate basal epithelial EP156T cells and progeny cells that underwent epithelial to mesenchymal transition (EMT), primary prostate epithelial cells (PrECs) and prostate cancer cell lines LNCaP, VCaP and 22Rv1 were used to examine context dependent restriction and activation of the AR and classical target genes, such as KLK3. Genome-wide gene expression analyses and single cell protein analyses were applied to study the effect of different contexts. RESULTS: A variety of growth conditions were tested and found unable to activate AR expression and transcription of classical androgen-dependent AR target genes, such as KLK3, in prostate epithelial cells with basal cell features or in mesenchymal type prostate cells. The restriction of androgen- and AR-dependent transcription of classical target genes in prostate basal epithelial cells was at the level of AR expression. Exogenous AR expression was sufficient for androgen-dependent transcription of AR target genes in prostate basal epithelial cells, but did not exert a positive feedback on endogenous AR expression. Treatment of basal prostate epithelial cells with inhibitors of epigenetic gene silencing was not efficient in inducing androgen-dependent transcription of AR target genes, suggesting the importance of missing cofactor(s). CONCLUSIONS: Regulatory mechanisms of AR and androgen-dependent AR target gene transcription are insufficiently understood and may be critical for prostate cancer initiation, progression and escape from standard therapy. The present model is useful for the study of context dependent activation of the AR and its transcriptome.