Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review.

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

Clustering of HR + /HER2- breast cancer in an Asian cohort is driven by immune phenotypes.

Breast cancer exhibits significant heterogeneity, manifesting in various subtypes that are critical in guiding treatment decisions. This study aimed to investigate the existence of distinct subtypes of breast cancer within the Asian population, by analysing the transcriptomic profiles of 934 breast cancer patients from a Malaysian cohort. Our findings reveal that the HR + /HER2- breast cancer samples display a distinct clustering pattern based on immune phenotypes, rather than conforming to the conventional luminal A-luminal B paradigm previously reported in breast cancers from women of European descent. This suggests that the activation of the immune system may play a more important role in Asian HR + /HER2- breast cancer than has been previously recognized. Analysis of somatic mutations by whole exome sequencing showed that counter-intuitively, the cluster of HR + /HER2- samples exhibiting higher immune scores was associated with lower tumour mutational burden, lower homologous recombination deficiency scores, and fewer copy number aberrations, implicating the involvement of non-canonical tumour immune pathways. Further investigations are warranted to determine the underlying mechanisms of these pathways, with the potential to develop innovative immunotherapeutic approaches tailored to this specific patient population.

Breast conserving surgery versus mastectomy: the effect of surgery on quality of life in breast cancer survivors in Malaysia.

BACKGROUND: In the competitive health care environment, patient satisfaction and quality of life (QoL) have become the subject of interest to evaluate the efficacy of therapeutic interventions as we experience improved breast cancer survival in modern times. The knowledge of the long-term effects of surgery on the QoL in breast cancer patients is currently limited in the Asian setting. The purpose of this longitudinal study is to evaluate the QoL of early-stage breast cancer patients undergoing mastectomy and breast-conserving surgery (BCS). METHODS: In this prospective cohort study, the QoL of 208 patients who underwent mastectomy and the BCS treatment were assessed, using the European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire. The questionnaire was administered at the baseline, 6 and 12 months following diagnosis. One-way ANCOVA was used for statistical analysis. RESULTS: A total of 208 female survivors of Stage 0-II breast cancer were included, among them 47.1% underwent BCS and 52.9% underwent mastectomy. Older (63.3%), Chinese women (63.6%), and patients with primary education (71.7%) were more likely to undergo mastectomy. At baseline, no significant differences were observed for QoL in both treatment groups. At 6 months, patients who underwent BCS had better social functioning scales( P = 0.006) and worse symptom scales for dyspnoea (P = 0.031), compared to mastectomy patients. One year after diagnosis, the role functioning score of the mastectomy group was significantly higher than the BCS group, specifically among patients who had undergone chemotherapy (P = 0.034). CONCLUSION: Patients who underwent BCS had better social functioning and worse dyspnoea symptoms compared to patients undergoing mastectomy at six months. During one year, there were only significant improvements in the role functioning among the mastectomy groups compared to the BCS groups. After further stratification, only mastectomy patients who received chemotherapy exhibited improved role functioning compared to patients those who did not undergo chemotherapy. Providing social and physical support postoperatively and monitoring patients for cancer worry, or other symptoms in the long-term survivorship period would be important to ensure optimal QoL.

The "Know Your Lemons" Tools: A strategy to improve breast cancer warning signs recognition in Malaysia.

BACKGROUND: Breast cancer (BC) is the most common cancer in Malaysia, with many diagnosed at late stages. The "Know Your Lemons" (KYL) visual educational tools were developed by KYL Foundation. This study aimed to evaluate participants' confidence levels and perceived knowledge in identifying BC symptoms before and after exposure to KYL tools. MATERIALS AND METHODS: A cross-sectional study was carried out among 788 participants in three KYL health campaigns from 2017 to 2020. Perceived knowledge (a 5-item Likert scale was used, zero means "very poor" and 4 means "excellent knowledge") and confidence in identifying BC symptoms were studied. A Wilcoxon Matched-Paired Signed-Rank Test was performed to assess the perceived knowledge. RESULTS: There was a significant improvement in the perceived knowledge Mean (±SD) score (2.84 ± 1.02) versus (4.31 ± 0.66) before and after the campaign (P < 0.01). About 95.6% agreed that the language used in KYL materials was clear and understandable, 89.8% agreed it is acceptable in Malaysian culture, and 80% felt more confident in identifying BC symptoms. Therefore, 90.8% had the intention of breast self-examination and 90.8% would consult a doctor if symptomatic. The majority (92.7%) agreed that the KYL tools clarified the BC tests needed. CONCLUSION: The KYL tools enhanced perceived BC symptom recognition knowledge and confidence levels.

Reliability and Validity of the Malay BREAST-Q in Women Undergoing Breast Cancer Surgery in Malaysia.

This study aims to translate the BREAST-Q into Malay and validate it in breast cancer patients undergoing surgery. The English BREAST-Q was translated to Malay using the back-translation method. A total of 144 newly diagnosed breast cancer patients were sampled conveniently between December 2015 and November 2016. Test-retest was done after two to three weeks. Data were analyzed using SPSS and AMOS software. Content experts agreed the items in the Malay BREAST-Q were measuring the constructs appropriately. Internal consistencies were good for all items in each subscale (Cronbach's alpha = 0.83-0.95). The highest inter-item correlation for each item with at least one other item in the construct ranged from 0.47 to 0.90. The lowest corrected item-total correlation values ranged from 0.47 to 0.72. The test-retest analysis showed good reproducibility (intraclass correlation coefficient = 0.71-0.98). In exploratory factor analysis, the Kaiser-Meyer-Olkin values were excellent in all four subscales (0.76, 0.92, 0.91, and 0.86). For all subscales, the number of factors extracted cumulatively explained more than 50% of the variance. The Malay BREAST-Q demonstrated good reliability, face validity, content validity, and construct validity.

Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke.

Stroke is the second largest cause of mortality in the world. Genome-wide association studies (GWAS) have identified some genetic variants associated with stroke risk, but their putative functional causal genes are unknown. Hence, we aimed to identify putative functional causal gene biomarkers of stroke risk. We used a summary-based Mendelian randomisation (SMR) approach to identify the pleiotropic associations of genetically regulated traits (i.e., gene expression and DNA methylation) with stroke risk. Using SMR approach, we integrated cis-expression quantitative loci (cis-eQTLs) and cis-methylation quantitative loci (cis-mQTLs) data with GWAS summary statistics of stroke. We also utilised heterogeneity in dependent instruments (HEIDI) test to distinguish pleiotropy from linkage from the observed associations identified through SMR analysis. Our integrative SMR analyses and HEIDI test revealed 45 candidate biomarker genes (FDR < 0.05; PHEIDI > 0.01) that were pleiotropically or potentially causally associated with stroke risk. Of those candidate biomarker genes, 10 genes (HTRA1, PMF1, FBN2, C9orf84, COL4A1, BAG4, NEK6, SH2B3, SH3PXD2A, ACAD10) were differentially expressed in genome-wide blood transcriptomics data from stroke and healthy individuals (FDR < 0.05). Functional enrichment analysis of the identified candidate biomarker genes revealed gene ontologies and pathways involved in stroke, including "cell aging", "metal ion binding" and "oxidative damage". Based on the evidence of genetically regulated expression of genes through SMR and directly measured expression of genes in blood, our integrative analysis suggests ten genes as blood biomarkers of stroke risk. Furthermore, our study provides a better understanding of the influence of DNA methylation on the expression of genes linked to stroke risk.

Benefits of PECS Block as Part of the Enhanced Recovery After Surgery (ERAS) Protocol for Breast Cancer Surgery in an Asian Institution: A Retrospective Cohort Study.

INTRODUCTION: Regional analgesia techniques have been increasingly used for post-operative pain management following mastectomy. We aim to evaluate analgesic benefits of pectoral nerve (PECS2) block incorporated as part of the enhanced recovery after surgery (ERAS) protocol in patients undergoing mastectomy in University Malaya Medical Centre, Malaysia. MATERIAL AND METHODS: A single centre, cohort study evaluating 335 women who have undergone unilateral mastectomy between January 2017 and March 2020 in Malaysia. Regional anaesthesia were given pre-operatively via ultrasound guided pectoral and intercostal nerves block (PECSII). RESULTS: Utilization of regional anaesthesia increased from 11% in 2017 to 43% in 2020. Types and duration of surgeries were comparable. Opiod consumption was 3 mg lower in those who had PECS2 block ((27 [24-30] mg), in comparison with those who received general anaesthesia only (30 [26-34] mg), p < 0.001, and length of stay was half a day shorter in the regional anaesthesia group and these were statistically significant. However, pain score (2 [1-3]; 2 [1-3], p=0.719) and post-operative nausea and vomiting (PONV) (32.6-32.5%, p = 0.996) were similar. CONCLUSION: This study highlights the importance of PECS2 block as a component of ERAS protocol for mastectomy in an Asian hospital. This study also inferred that patients may be safely discharged within 24 h of surgery and therefore, same day surgery may be feasible in selected group of patients undergoing mastectomy and this could imply overall cost benefits.

A longitudinal study of physical activity among Malaysian breast cancer survivors.

Regular physical activity (PA) after a breast cancer diagnosis is associated with reduced mortality and better quality of life. In this prospective cohort study, we aimed to explore the trends of PA among breast cancer survivors over three years and identify factors associated with low PA. Interviews on 133 breast cancer patients were conducted at baseline, one and three years after the diagnosis of breast cancer at University Malaya Medical Centre in Kuala Lumpur. Physical activity was measured by using the Global Physical Activity Questionnaire. PA was categorised as active (≥ 600 MET-min/week) and inactive (<600 MET-min/week). We used the generalised estimating equation method to examine PA levels and factors affecting PA longitudinally. The survivors' mean age was 56.89 (±10.56) years; half were Chinese (50.4%), and 70.7% were married. At baseline, 48.1% of the patients were active, but the proportion of active patients declined to 39.8% at one year and 35.3% in the third year. The mean total PA decreased significantly from 3503±6838.3 MET-min/week to 1494.0±2679.8 MET-min/week (one year) and 792.5±1364 MET-min/week (three years) (p<0.001). Three years after diagnosis (adjusted odds ratio [AOR]: 1.74, p = 0.021); Malay ethnicity (AOR: 1.86, p = 0.042) and being underweight (AOR: 3.43, p = 0.004) were significantly associated with inactivity. We demonstrated that breast cancer survivors in Malaysia had inadequate PA levels at diagnosis, which decreased over time. Thus, it is vital to communicate about the benefits of PA on cancer outcomes and continue to encourage breast cancer survivors to be physically active throughout the extended survivorship period, especially in the Malay ethnic group and underweight patients.

Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification.

BACKGROUND: Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear. METHODS: In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, or TP53), and polygenic risk score (PRS) 5yAR above 1.3%. RESULTS: Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low (r=0.27). Fifty-three percent of breast cancer patients (n=4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history. CONCLUSIONS: Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.

Changes in Dietary Intake of Breast Cancer Survivors: Early Findings of a Malaysian Breast Cancer Prospective Cohort Study.

This study aimed to evaluate the changes in post-diagnosis dietary intake of breast cancer survivors. A total of 112 participants from the Malaysian Breast Cancer Survivorship Cohort study with dietary intake at one-year post-diagnosis (T1) and three-year post-diagnosis (T2) were included. A three-day food record was used to assess the dietary intake of breast cancer survivors. The participants' anthropometrical measurements were measured at both time points (n = 95). Notably, we found that around half of the participants were obese at both time points. Body weight and body mass index increased significantly between the two time points (P < 0.01). Most of the participants did not meet the Malaysian recommended nutrient intake for dietary fat, fiber, and calcium at both time points. The energy intake significantly decreased (from 1,596 kcal/day to 1,524 kcal/day, P = 0.028) within the survivors. Significant decreases were observed in the overall intakes of carbohydrates, total sugar, protein, fiber, and calcium (P < 0.05). Overall, many Malaysian breast cancer survivors remained overweight or obese and had suboptimal dietary intake even at three years post-diagnosis. These require more proactive dietary intervention with continuous monitoring and evaluation among breast cancer survivors for their survivorship care.

rMisbeta: A robust missing value imputation approach in transcriptomics and metabolomics data.

Transcriptomics and metabolomics data often contain missing values or outliers due to limitations of the data acquisition techniques. Most of the statistical methods require complete datasets for downstream analysis. A number of methods have been developed for missing value imputation using the classical mean and variance based on maximum likelihood estimators, which are not robust against outliers. Consequently, the performance of these methods deteriorates in the presence of outliers. Hence precise imputation of missing values and outliers handling are both concurrently important. Therefore, in this paper, we developed a robust iterative approach using robust estimators based on the minimum beta divergence method, which simultaneously impute missing values and outliers. We investigate the performance of the proposed method in a comparison with six frequently used missing value imputation methods such as Zero, KNN, robust SVD, EM, random forest (RF) and weighted least square approach (WLSA) through feature selection using both simulated and real datasets. Ten performance indices were used to explore the optimal method such as Frobenius norm (FOBN), accuracy (ACC), sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), detection rate (DR), misclassification error rate (MER), the area under the ROC curve (AUC) and computational runtime. Evaluation based on both simulated and real data suggests the superiority of the proposed method over the other traditional methods in terms of various rates of outliers and missing values. The suggested approach also keeps almost equal performance in absence of outliers with the other methods. The proposed method is accurate, simple, and consumes lower computational time compared to the other methods. Therefore, our recommendation is to apply the proposed procedure for large-scale transcriptomics and metabolomics data analysis. The computational tool has been implemented in an R package, which is publicly available from https://CRAN.R-project.org/package=rMisbeta.

An Artificial Intelligence-Enabled Pipeline for Medical Domain: Malaysian Breast Cancer Survivorship Cohort as a Case Study.

Automated artificial intelligence (AI) systems enable the integration of different types of data from various sources for clinical decision-making. The aim of this study is to propose a pipeline to develop a fully automated clinician-friendly AI-enabled database platform for breast cancer survival prediction. A case study of breast cancer survival cohort from the University Malaya Medical Centre was used to develop and evaluate the pipeline. A relational database and a fully automated system were developed by integrating the database with analytical modules (machine learning, automated scoring for quality of life, and interactive visualization). The developed pipeline, iSurvive has helped in enhancing data management as well as to visualize important prognostic variables and survival rates. The embedded automated scoring module demonstrated quality of life of patients whereas the interactive visualizations could be used by clinicians to facilitate communication with patients. The pipeline proposed in this study is a one-stop center to manage data, to automate analytics using machine learning, to automate scoring and to produce explainable interactive visuals to enhance clinician-patient communication along the survivorship period to modify behaviours that relate to prognosis. The pipeline proposed can be modelled on any disease not limited to breast cancer.

Discovering common pathogenetic processes between COVID-19 and diabetes mellitus by differential gene expression pattern analysis.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

Is pre-operative axillary ultrasound alone sufficient to determine need for axillary dissection in early breast cancer patients?

ABSTRACT: Pre-operative status of axillary lymph node (ALN) in early breast cancer is usually initially assessed by pre-operative ultrasound, followed by ultrasound-guided needle biopsy (UNB) confirmation. Patients with positive nodal status will undergo axillary lymph node dissection (ALND), while those with negative nodal status will have sentinel lymph node biopsy. ALND is associated with higher morbidity than Sentinel lymph node biopsy. The objective of this study is to determine if axillary ultrasound alone without UNB is predictive enough to assign patients to ALND and to identify ultrasound features that are significantly associated with pathologically positive ALN.383 newly diagnosed primary breast cancer patients between 2012 and 2014, and who had undergone pre-operative axillary ultrasound in University Malaya Medical Centre with a complete histopathology report of the axillary surgery were retrospectively reviewed. ALN was considered positive if it had any of these features: cortical thickening > 3 mm, loss of fatty hilum, hypoechoic solid node, mass-like appearance, round shape and lymph node size > 5 mm. Post-operative histopathological reports were then analyzed for nodal involvement.The overall sensitivity, specificity, and accuracy of pre-operative axillary ultrasound in detecting diseased nodes were 45.5%, 80.7%, and 60.3% respectively. The positive (PPV) and negative predictive values were 76.5% and 51.8%. Round shape, loss of fatty hilum and mass-like appearance had the highest PPVs of 87%, 83% and 81.6% respectively and significant odds ratios (ORs) of 5.22 (95% confidence interval [CI]: 1.52 - 17.86), ORs of 4.77 (95% CI: 2.62 - 8.70) and ORs of 4.26 (95% CI: 2.37 - 7.67) respectively (P-value < .05). Cortical thickness of > 3 mm was identified to have low PPV at 69.1%, ORs of 1.71 (95% CI: 0.86 - 3.41, P = .126).There are features on axillary ultrasound that confer high PPV for axillary involvement i.e. round shape, loss of fatty hilum, and mass-like appearance. In a low resource setting, these features may benefit from ALND without further pre-operative biopsies. However, pre-operative UNB for features with low PPV that is, cortical thickness > 3 mm should be considered to obviate the unnecessary morbidity associated with ALND.

Identification of Common Pathogenetic Processes between Schizophrenia and Diabetes Mellitus by Systems Biology Analysis.

Schizophrenia (SCZ) is a psychiatric disorder characterized by both positive symptoms (i.e., psychosis) and negative symptoms (such as apathy, anhedonia, and poverty of speech). Epidemiological data show a high likelihood of early onset of type 2 diabetes mellitus (T2DM) in SCZ patients. However, the molecular processes that could explain the epidemiological association between SCZ and T2DM have not yet been characterized. Therefore, in the present study, we aimed to identify underlying common molecular pathogenetic processes and pathways between SCZ and T2DM. To this aim, we analyzed peripheral blood mononuclear cell (PBMC) transcriptomic data from SCZ and T2DM patients, and we detected 28 differentially expressed genes (DEGs) commonly modulated between SCZ and T2DM. Inflammatory-associated processes and membrane trafficking pathways as common biological processes were found to be in common between SCZ and T2DM. Analysis of the putative transcription factors involved in the regulation of the DEGs revealed that STAT1 (Signal Transducer and Activator of Transcription 1), RELA (v-rel reticuloendotheliosis viral oncogene homolog A (avian)), NFKB1 (Nuclear Factor Kappa B Subunit 1), and ERG (ETS-related gene) are involved in the expression of common DEGs in SCZ and T2DM. In conclusion, we provide core molecular signatures and pathways that are shared between SCZ and T2DM, which may contribute to the epidemiological association between them.

Development and evaluation of a sustainable video health education program for newly diagnosed breast cancer patients in Malaysia.

PURPOSE: Wider breast cancer (BC) treatment options, short consultation time with physicians, lack of knowledge, and poor coping skills at the time of diagnosis may affect patients' decisions causing treatment delays and non-adherence. To address this gap, a breast care nurse video orientation program was started. Our aim was to evaluate the video on patients' knowledge, satisfaction, and treatment adherence. METHODS: The video was developed using the BC delay explanatory model. A self-administered pre- and post-survey on 241 newly diagnosed BC patients in University Malaya Medical Center was performed. The Wilcoxon matched paired signed rank test was used to evaluate patients' pre and post perceived knowledge using a Likert scale 0 to 4 (0 = "no knowledge," 4 = "a great degree of knowledge"). Treatment adherence among participants were measured after 1-year follow-up. RESULTS: Eighty percent of the patients reported that the video met or exceeded their expectations. In total 80.5% reported that the video was very effective and effective in improving their perspective on BC treatments. There was improvement in perceived knowledge for treatment options (mean scores; M = 0.93 versus M = 2.97) (p < 0.001) and also for perceived knowledge on types of operation, information on chemotherapy, radiotherapy, hormone therapy, healthy diet, physical activity after treatments, and care of the arm after operation(p < 0.001). In total 89.4%, 79.3%, and 85.9% adhered to surgical, chemotherapy, and radiotherapy recommended treatment, respectively. CONCLUSION: The video improved patients' perceived knowledge and satisfaction. The program improved access not only to new BC patients but also the public and found sustainable using the YouTube platform.

Comprehensive Analysis of RNA-Seq Gene Expression Profiling of Brain Transcriptomes Reveals Novel Genes, Regulators, and Pathways in Autism Spectrum Disorder.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with deficits in social communication ability and repetitive behavior. The pathophysiological events involved in the brain of this complex disease are still unclear. METHODS: In this study, we aimed to profile the gene expression signatures of brain cortex of ASD patients, by using two publicly available RNA-seq studies, in order to discover new ASD-related genes. RESULTS: We detected 1567 differentially expressed genes (DEGs) by meta-analysis, where 1194 were upregulated and 373 were downregulated genes. Several ASD-related genes previously reported were also identified. Our meta-analysis identified 235 new DEGs that were not detected using the individual RNA-seq studies used. Some of those genes, including seven DEGs (PAK1, DNAH17, DOCK8, DAPP1, PCDHAC2, and ERBIN, SLC7A7), have been confirmed in previous reports to be associated with ASD. Gene Ontology (GO) and pathways analysis showed several molecular pathways enriched by the DEGs, namely, osteoclast differentiation, TNF signaling pathway, complement and coagulation cascade. Topological analysis of protein-protein interaction of the ASD brain cortex revealed proteomics hub gene signatures: MYC, TP53, HDAC1, CDK2, BAG3, CDKN1A, GABARAPL1, EZH2, VIM, and TRAF1. We also identified the transcriptional factors (TFs) regulating DEGs, namely, FOXC1, GATA2, YY1, FOXL1, USF2, NFIC, NFKB1, E2F1, TFAP2A, HINFP. CONCLUSION: Novel core genes and molecular signatures involved with ASD were identified by our meta-analysis.

Integrative transcriptomics analysis of lung epithelial cells and identification of repurposable drug candidates for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease, more commonly COVID-19 has emerged as a world health pandemic. There are couples of treatment methods for COVID-19, however, well-established drugs and vaccines are urgently needed to treat the COVID-19. The new drug discovery is a tremendous challenge; repurposing of existing drugs could shorten the time and expense compared with de novo drug development. In this study, we aimed to decode molecular signatures and pathways of the host cells in response to SARS-CoV-2 and the rapid identification of repurposable drugs using bioinformatics and network biology strategies. We have analyzed available transcriptomic RNA-seq COVID-19 data to identify differentially expressed genes (DEGs). We detected 177 DEGs specific for COVID-19 where 122 were upregulated and 55 were downregulated compared to control (FDR<0.05 and logFC ≥ 1). The DEGs were significantly involved in the immune and inflammatory response. The pathway analysis revealed the DEGs were found in influenza A, measles, cytokine signaling in the immune system, interleukin-4, interleukin -13, interleukin -17 signaling, and TNF signaling pathways. Protein-protein interaction analysis showed 10 hub genes (BIRC3, ICAM1, IRAK2, MAP3K8, S100A8, SOCS3, STAT5A, TNF, TNFAIP3, TNIP1). The regulatory network analysis showed significant transcription factors (TFs) that target DEGs, namely FOXC1, GATA2, YY1, FOXL1, NFKB1. Finally, drug repositioning analysis was performed with these 10 hub genes and showed that in silico validated three drugs with molecular docking. The transcriptomics signatures, molecular pathways, and regulatory biomolecules shed light on candidate biomarkers and drug targets which have potential roles to manage COVID-19. ICAM1 and TNFAIP3 were the key hubs that have demonstrated good binding affinities with repurposed drug candidates. Dabrafenib, radicicol, and AT-7519 were the top-scored repurposed drugs that showed efficient docking results when they tested with hub genes. The identified drugs should be further evaluated in molecular level wet-lab experiments in prior to clinical studies in the treatment of COVID-19.

Detection of molecular signatures and pathways shared in inflammatory bowel disease and colorectal cancer: A bioinformatics and systems biology approach.

Emerging evidence indicates IBD is a risk factor for the increasing incidence of colorectal cancer (CRC) development. We used a system biology approach to identify common molecular signatures and pathways that interact between IBD and CRC and the indispensable pathological mechanisms. First, we identified 177 common differentially expressed genes (DEGs) between IBD and CRC. Gene set enrichment, protein-protein, DEGs-transcription factors, DEGs-microRNAs, protein-drug interaction, gene-disease association, Gene Ontology, pathway enrichment analyses were conducted to these common genes. The inclusion of common DEGs with bimolecular networks disclosed hub proteins (LYN, PLCB1, NPSR1, WNT5A, CDC25B, CD44, RIPK2, ASAP1), transcription factors (SCD, SLC7A5, IKZF3, SLC16A1, SLC7A11) and miRNAs (mir-335-5p, mir-26b-5p, mir-124-3p, mir-16-5p, mir-192-5p, mir-548c-3p, mir-29b-3p, mir-155-5p, mir-21-5p, mir-15a-5p). Analysis of the interaction between protein and drug discovered ASAP1 interacts with cysteine sulfonic acid and double oxidized cysteine drug compounds. Gene-disease association analysis retrieved ASAP1 also associated with pulmonary and bladder neoplasm diseases.