Nevin Manimala

Br J Cancer. 2021 Nov 26. doi: 10.1038/s41416-021-01641-1. Online ahead of print.

ABSTRACT

BACKGROUND: Aberrant activation of androgen receptor signalling following castration therapy is a common clinical observation in prostate cancer (PCa). Earlier, we demonstrated the role of MYB overexpression in androgen-depletion resistance and PCa aggressiveness. Here, we investigated MYB-androgen receptor (AR) crosstalk and its functional significance.

METHODS: Interaction and co-localization of MYB and AR were examined by co-immunoprecipitation and immunofluorescence analyses, respectively. Protein levels were measured by immunoblot analysis and enzyme-linked immunosorbent assay. The role of MYB in ligand-independent AR transcriptional activity and combinatorial gene regulation was studied by promoter-reporter and chromatin immunoprecipitation assays. The functional significance of MYB in castration resistance was determined using an orthotopic mouse model.

RESULTS: MYB and AR interact and co-localize in the PCa cells. MYB-overexpressing PCa cells retain AR in the nucleus even when cultured under androgen-deprived conditions. AR transcriptional activity is also sustained in MYB-overexpressing cells in the absence of androgens. MYB binds and promotes AR occupancy to the KLK3 promoter. MYB-overexpressing PCa cells exhibit greater tumorigenicity when implanted orthotopically and quickly regain growth following castration leading to shorter mice survival, compared to those carrying low-MYB-expressing prostate tumours.

CONCLUSIONS: Our findings reveal a novel MYB-AR crosstalk in PCa and establish its role in castration resistance.

PMID:34837075 | DOI:10.1038/s41416-021-01641-1

Nat Rev Genet. 2021 Nov 26. doi: 10.1038/s41576-021-00434-9. Online ahead of print.

ABSTRACT

The scale of genetic, epigenomic, transcriptomic, cheminformatic and proteomic data available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the application of supervised learning in genomics research. However, the assumptions behind the statistical models and performance evaluations in ML software frequently are not met in biological systems. In this Review, we illustrate the impact of several common pitfalls encountered when applying supervised ML in genomics. We explore how the structure of genomics data can bias performance evaluations and predictions. To address the challenges associated with applying cutting-edge ML methods to genomics, we describe solutions and appropriate use cases where ML modelling shows great potential.

PMID:34837041 | DOI:10.1038/s41576-021-00434-9

Eur J Hum Genet. 2021 Nov 26. doi: 10.1038/s41431-021-00984-w. Online ahead of print.

ABSTRACT

Although variant alleles of hundreds of genes are associated with sensorineural deafness in children, the genes and alleles involved remain largely unknown in the Sub-Saharan regions of Africa. We ascertained 56 small families mainly of Yoruba ethno-lingual ancestry in or near Ibadan, Nigeria, that had at least one individual with nonsyndromic, severe-to-profound, prelingual-onset, bilateral hearing loss not attributed to nongenetic factors. We performed a combination of exome and Sanger sequencing analyses to evaluate both nuclear and mitochondrial genomes. No biallelic pathogenic variants were identified in GJB2, a common cause of deafness in many populations. Potential causative variants were identified in genes associated with nonsyndromic hearing loss (CIB2, COL11A1, ILDR1, MYO15A, TMPRSS3, and WFS1), nonsyndromic hearing loss or Usher syndrome (CDH23, MYO7A, PCDH15, and USH2A), and other syndromic forms of hearing loss (CHD7, OPA1, and SPTLC1). Several rare mitochondrial variants, including m.1555A>G, were detected in the gene MT-RNR1 but not in control Yoruba samples. Overall, 20 (33%) of 60 independent cases of hearing loss in this cohort of families were associated with likely causal variants in genes reported to underlie deafness in other populations. None of these likely causal variants were present in more than one family, most were detected as compound heterozygotes, and 77% had not been previously associated with hearing loss. These results indicate an unusually high level of genetic heterogeneity of hearing loss in Ibadan, Nigeria and point to challenges for molecular genetic screening, counseling, and early intervention in this population.

PMID:34837038 | DOI:10.1038/s41431-021-00984-w

Sci Rep. 2021 Nov 26;11(1):23023. doi: 10.1038/s41598-021-02548-w.

ABSTRACT

SARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein variation is correlated with nsp3, nsp6, and 3′-to-5′ exonuclease variation. Country of origin and time since the start of the pandemic were the most influential metadata associated with genomic variation, while host sex and age were the least influential. We define a novel statistic-coherence-and show its utility in identifying geographic regions (populations) with unusually high (many new variants) or low (isolated) viral phylogenetic diversity. Interestingly, at both global and regional scales, we identify geographic locations with high coherence neighboring regions of low coherence; this emphasizes the utility of this metric to inform public health measures for disease spread. Our results provide a direction to prioritize genes associated with outcome predictors (e.g., health, therapeutic, and vaccine outcomes) and to improve DNA tests for predicting disease status.

PMID:34837008 | DOI:10.1038/s41598-021-02548-w

Sci Rep. 2021 Nov 26;11(1):22997. doi: 10.1038/s41598-021-02476-9.

ABSTRACT

We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decision trees (GBDT) and important predictors were identified using a Shapley values-based feature attribution method, SHAP values. Cox models controlled for false discovery rate were used for confounder adjustment, interpretability, and further validation. The pipeline was tested using information from 502,506 UK Biobank participants, aged 37-73 years at recruitment and followed over seven years for mortality registrations. From the 11,639 predictors included in GBDT, 193 potential risk factors had SHAP values ≥ 0.05, passed the correlation test, and were selected for further modelling. Of the total variable importance summed up, 60% was directly health related, and baseline characteristics, sociodemographics, and lifestyle factors each contributed about 10%. Cox models adjusted for baseline characteristics, showed evidence for an association with mortality for 166 out of the 193 predictors. These included mostly well-known risk factors (e.g., age, sex, ethnicity, education, material deprivation, smoking, physical activity, self-rated health, BMI, and many disease outcomes). For 19 predictors we saw evidence for an association in the unadjusted but not adjusted analyses, suggesting bias by confounding. Our GBDT-SHAP pipeline was able to identify relevant predictors ‘hidden’ within thousands of variables, providing an efficient and pragmatic solution for the first stage of hypothesis free risk factor identification.

PMID:34837000 | DOI:10.1038/s41598-021-02476-9

Sci Rep. 2021 Nov 26;11(1):23002. doi: 10.1038/s41598-021-02330-y.

ABSTRACT

Radiotherapy requires the target area and the organs at risk to be contoured on the CT image of the patient. During the process of organs-at-Risk (OAR) of the chest and abdomen, the doctor needs to contour at each CT image. The delineations of large and varied shapes are time-consuming and laborious. This study aims to evaluate the results of two automatic contouring softwares on OARs definition of CT images of lung cancer and rectal cancer patients. The CT images of 15 patients with rectal cancer and 15 patients with lung cancer were selected separately, and the organs at risk were manually contoured by experienced physicians as reference structures. And then the same datasets were automatically contoured based on AiContour (version 3.1.8.0, Manufactured by Linking MED, Beijing, China) and Raystation (version 4.7.5.4, Manufactured by Raysearch, Stockholm, Sweden) respectively. Deep learning auto-segmentations and Atlas were respectively performed with AiContour and Raystation. Overlap index (OI), Dice similarity index (DSC) and Volume difference (D_v) were evaluated based on the auto-contours, and independent-sample t-test analysis is applied to the results. The results of deep learning auto-segmentations on OI and DSC were better than that of Atlas with statistical difference. There was no significant difference in D_v between the results of two software. With deep learning auto-segmentations, auto-contouring results of most organs in the chest and abdomen are good, and with slight modification, it can meet the clinical requirements for planning. With Atlas, auto-contouring results in most OAR is not as good as deep learning auto-segmentations, and only the auto-contouring results of some organs can be used clinically after modification.

PMID:34836989 | DOI:10.1038/s41598-021-02330-y

Sci Data. 2021 Nov 26;8(1):305. doi: 10.1038/s41597-021-01089-1.

ABSTRACT

Statistical Parametric Mapping (SPM) is a computational approach for analysing functional brain images like Positron Emission Tomography (PET). When performing SPM analysis for different patient populations, brain PET template images representing population-specific brain morphometry and metabolism features are helpful. However, most currently available brain PET templates were constructed using the Caucasian data. To enrich the family of publicly available brain PET templates, we created Chinese-specific template images based on 116 [¹⁸F]-fluorodeoxyglucose ([¹⁸F]-FDG) PET images of normal participants. These images were warped into a common averaged space, in which the mean and standard deviation templates were both computed. We also developed the SPM analysis programmes to facilitate easy use of the templates. Our templates were validated through the SPM analysis of Alzheimer’s and Parkinson’s patient images. The resultant SPM t-maps accurately depicted the disease-related brain regions with abnormal [¹⁸F]-FDG uptake, proving the templates’ effectiveness in brain function impairment analysis.

PMID:34836985 | DOI:10.1038/s41597-021-01089-1

Sci Rep. 2021 Nov 26;11(1):22970. doi: 10.1038/s41598-021-00083-2.

ABSTRACT

Several vaccines with different efficacies and effectivenesses are currently being distributed across the world to control the COVID-19 pandemic. Having enough doses from the most efficient vaccines in a short time is not possible for all countries. Hence, policymakers may propose using various combinations of available vaccines to control the pandemic with vaccine-induced herd immunity by vaccinating a fraction of the population. The classic vaccine-induced herd-immunity threshold suggests that we can stop spreading the disease by vaccinating a fraction of the population. However, that classic threshold is defined only for a single vaccine and may be invalid and biased when we have multi-vaccine strategies for a disease or multiple variants, potentially leading policymakers to suboptimal vaccine-allocation policies. Here, we determine which combination of multiple vaccines may lead to herd immunity. We show that simplifying the problem and considering the vaccination of the population as a single-vaccine strategy whose effectiveness is the sample mean of all effectivenesses would not be ideal, because many multi-vaccine strategies with a smaller herd-immunity threshold can be proposed. We show that the herd-immunity threshold may vary due to changes in vaccine-uptake proportions. Moreover, we propose methods to determine the optimal combination of multiple vaccines in order to achieve herd immunity and apply our results to the issue of multiple variants. In addition, we determine a condition for reaching herd immunity in the presence of new emerging variants of concern. We show by example that new variants could influence our estimation of the vaccination reproduction number. It follows that the herd-immunity threshold must be updated not only when multi-vaccine strategies are used but also when multiple variants coexist in the population.

PMID:34836984 | DOI:10.1038/s41598-021-00083-2

Sci Rep. 2021 Nov 26;11(1):22996. doi: 10.1038/s41598-021-02040-5.

ABSTRACT

Multiple N-methyl-D-aspartate (NMDA) receptor enhancing agents have had promising effects on cognition among patients with dementia. However, the results remain inconsistent. This exploratory meta-analysis investigated the effectiveness of NMDA receptor enhancing agents for cognitive function. PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews were searched for randomized controlled trials (RCTs). Controlled trials assessing add-on NMDA receptor enhancing agent treatment in patients with dementia and using cognition rating scales were eligible and pooled using a random-effect model for comparisons. The standardized mean difference (SMD) was calculated in each study from the effect size; positive values indicated that NMDA receptor enhancing agent treatment improved cognitive function. Funnel plots and the I2 statistic were evaluated for statistical heterogeneity. Moderators were evaluated using meta-regression. We identified 14 RCTs with 2224 participants meeting the inclusion criteria. Add-on NMDA receptor enhancing agents had small positive significant effects on overall cognitive function among patients with dementia (SMD = 0.1002, 95% CI 0.0105-0.1900, P = 0.02860). Subgroup meta-analysis showed patients with Alzheimer’s Disease and trials using the Alzheimer Disease Assessment Scale-cognitive subscale as the primary outcome had small positive significant effects (SMD = 0.1042, 95% CI 0.0076-0.2007, P = 0.03451; SMD = 0.1267, 95% CI 0.0145-0.2388, P = 0.2686). This exploratory meta-analysis showed a very small, positive, and significant effect on overall cognition function in patients with dementia. Studies with larger samples are needed to evaluate different cognitive domains and phases of dementia.

PMID:34836972 | DOI:10.1038/s41598-021-02040-5

Nat Commun. 2021 Nov 26;12(1):6920. doi: 10.1038/s41467-021-26556-6.

ABSTRACT

Bone marrow is a preferred metastatic site for multiple solid tumours and is associated with poor prognosis and significant morbidity. Accumulating evidence indicates that cancer cells colonise specialised niches within the bone marrow to support their long-term propagation, but the precise location and mechanisms that mediate niche interactions are unknown. Using breast cancer as a model of solid tumour metastasis to the bone marrow, we applied large-scale quantitative three-dimensional imaging to characterise temporal changes in the bone marrow microenvironment during disease progression. We show that mouse mammary tumour cells preferentially home to a pre-existing metaphyseal domain enriched for type H vessels. Metastatic lesion outgrowth rapidly remodelled the local vasculature through extensive sprouting to establish a tumour-supportive microenvironment. The evolution of this tumour microenvironment reflects direct remodelling of the vascular endothelium through tumour-derived granulocyte-colony stimulating factor (G-CSF) in a hematopoietic cell-independent manner. Therapeutic targeting of the metastatic niche by blocking G-CSF receptor inhibited pathological blood vessel remodelling and reduced bone metastasis burden. These findings elucidate a mechanism of ‘host’ microenvironment hijacking by mammary tumour cells to subvert the local microvasculature to form a specialised, pro-tumorigenic niche.

PMID:34836954 | DOI:10.1038/s41467-021-26556-6