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.

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.

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.

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.

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.

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.

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.

Identification of molecular signatures and pathways to identify novel therapeutic targets in Alzheimer's disease: Insights from a systems biomedicine perspective.

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. However, there are no peripheral biomarkers available that can detect AD onset. This study aimed to identify the molecular signatures in AD through an integrative analysis of blood gene expression data. We used two microarray datasets (GSE4226 and GSE4229) comparing peripheral blood transcriptomes of AD patients and controls to identify differentially expressed genes (DEGs). Gene set and protein overrepresentation analysis, protein-protein interaction (PPI), DEGs-Transcription Factors (TFs) interactions, DEGs-microRNAs (miRNAs) interactions, protein-drug interactions, and protein subcellular localizations analyses were performed on DEGs common to the datasets. We identified 25 common DEGs between the two datasets. Integration of genome scale transcriptome datasets with biomolecular networks revealed hub genes (NOL6, ATF3, TUBB, UQCRC1, CASP2, SND1, VCAM1, BTF3, VPS37B), common transcription factors (FOXC1, GATA2, NFIC, PPARG, USF2, YY1) and miRNAs (mir-20a-5p, mir-93-5p, mir-16-5p, let-7b-5p, mir-708-5p, mir-24-3p, mir-26b-5p, mir-17-5p, mir-193-3p, mir-186-5p). Evaluation of histone modifications revealed that hub genes possess several histone modification sites associated with AD. Protein-drug interactions revealed 10 compounds that affect the identified AD candidate biomolecules, including anti-neoplastic agents (Vinorelbine, Vincristine, Vinblastine, Epothilone D, Epothilone B, CYT997, and ZEN-012), a dermatological (Podofilox) and an immunosuppressive agent (Colchicine). The subcellular localization of molecular signatures varied, including nuclear, plasma membrane and cytosolic proteins. In the present study, it was identified blood-cell derived molecular signatures that might be useful as candidate peripheral biomarkers in AD. It was also identified potential drugs and epigenetic data associated with these molecules that may be useful in designing therapeutic approaches to ameliorate AD.

Discovering Biomarkers and Pathways Shared by Alzheimer's Disease and Ischemic Stroke to Identify Novel Therapeutic Targets.

Background and objectives: Alzheimer's disease (AD) is a progressive neurodegenerative disease that results in severe dementia. Having ischemic strokes (IS) is one of the risk factors of the AD, but the molecular mechanisms that underlie IS and AD are not well understood. We thus aimed to identify common molecular biomarkers and pathways in IS and AD that can help predict the progression of these diseases and provide clues to important pathological mechanisms. Materials and Methods: We have analyzed the microarray gene expression datasets of IS and AD. To obtain robust results, combinatorial statistical methods were used to analyze the datasets and 26 transcripts (22 unique genes) were identified that were abnormally expressed in both IS and AD. Results: Gene Ontology (GO) and KEGG pathway analyses indicated that these 26 common dysregulated genes identified several altered molecular pathways: Alcoholism, MAPK signaling, glycine metabolism, serine metabolism, and threonine metabolism. Further protein-protein interactions (PPI) analysis revealed pathway hub proteins PDE9A, GNAO1, DUSP16, NTRK2, PGAM2, MAG, and TXLNA. Transcriptional and post-transcriptional components were then identified, and significant transcription factors (SPIB, SMAD3, and SOX2) found. Conclusions: Protein-drug interaction analysis revealed PDE9A has interaction with drugs caffeine, γ-glutamyl glycine, and 3-isobutyl-1-methyl-7H-xanthine. Thus, we identified novel putative links between pathological processes in IS and AD at transcripts levels, and identified possible mechanistic and gene expression links between IS and AD.

Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis.

Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world, but early diagnosis ameliorates the survival of CRC. This report aimed to identify molecular biomarker signatures in CRC. We analyzed two microarray datasets (GSE35279 and GSE21815) from the Gene Expression Omnibus (GEO) to identify mutual differentially expressed genes (DEGs). We integrated DEGs with protein⁻protein interaction and transcriptional/post-transcriptional regulatory networks to identify reporter signaling and regulatory molecules; utilized functional overrepresentation and pathway enrichment analyses to elucidate their roles in biological processes and molecular pathways; performed survival analyses to evaluate their prognostic performance; and applied drug repositioning analyses through Connectivity Map (CMap) and geneXpharma tools to hypothesize possible drug candidates targeting reporter molecules. A total of 727 upregulated and 99 downregulated DEGs were detected. The PI3K/Akt signaling, Wnt signaling, extracellular matrix (ECM) interaction, and cell cycle were identified as significantly enriched pathways. Ten hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2), 10 transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1, FOXP3, E2F4, and PRDM14) and two microRNAs (miRNAs) (miR-193b-3p and miR-615-3p) were detected as reporter molecules. The survival analyses through Kaplan⁻Meier curves indicated remarkable performance of reporter molecules in the estimation of survival probability in CRC patients. In addition, several drug candidates including anti-neoplastic and immunomodulating agents were repositioned. This study presents biomarker signatures at protein and RNA levels with prognostic capability in CRC. We think that the molecular signatures and candidate drugs presented in this study might be useful in future studies indenting the development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC.

Factors associated with return to work of breast cancer survivors: a systematic review.

BACKGROUND: The breast cancer survival rate is the highest among all types of cancers, and survivors returning to work after completing treatment is extremely important in regards to economy and rehabilitation. The aim of this systematic review study is to identify the prevalence of breast cancer survivors who return to work (RTW) and the factors associated to RTW. METHODS: A computer based literature search was carried out. "PubMed, Cochrane Library, Embase, Web of Science, and Science Direct" databases were searched systematically. Our search strategy identified a total of 12,116 papers of which 26 studies met the inclusion criteria and quality assessment. These were original papers published between January 2003 and January 2013. RESULTS: The trends in RTW differ among countries for the breast cancer survivors. The time to RTW after successful cancer treatment also varies among the countries and by ethnicity. The prevalence of the RTW varies from 43% to 93% within one year of diagnosis. The prevalence of the RTW for the Netherland is the lowest in the world (43%). The United States survivors showed the highest RTW (93%) within 12 months of the diagnosis. Numerous barriers and facilitators were identified as factors that affect RTW. For instance, socio-demographic factors such as education and ethnicity; treatment oriented factors such as chemotherapy; work related factors such as heavy physical work; disease related factors such as poor health condition and fatigue; and psychological factors such as depression and emotional distress, act as barriers of RTW. In contrast, social, family, employer support, and financial independency emerge as key facilitators in enabling breast cancer survivors to return and continue work. CONCLUSION: Minimising these identified barriers and strengthening these facilitators could further improve the work condition and increase the percentage of RTW among the breast cancer survivors.

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.

Gene expression signature for predicting homologous recombination deficiency in triple-negative breast cancer.

Triple-negative breast cancers (TNBCs) are a subset of breast cancers that have remained difficult to treat. A proportion of TNBCs arising in non-carriers of BRCA pathogenic variants have genomic features that are similar to BRCA carriers and may also benefit from PARP inhibitor treatment. Using genomic data from 129 TNBC samples from the Malaysian Breast Cancer (MyBrCa) cohort, we developed a gene expression-based machine learning classifier for homologous recombination deficiency (HRD) in TNBCs. The classifier identified samples with HRD mutational signature at an AUROC of 0.93 in MyBrCa validation datasets and 0.84 in TCGA TNBCs. Additionally, the classifier strongly segregated HRD-associated genomic features in TNBCs from TCGA, METABRIC, and ICGC. Thus, our gene expression classifier may identify triple-negative breast cancer patients with homologous recombination deficiency, suggesting an alternative method to identify individuals who may benefit from treatment with PARP inhibitors or platinum chemotherapy.

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.

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.

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.

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.