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Active targeting strategy is adopted in nanomedicine for cancer treatment. Personalizing the nanomedicine in accordance with patients' omics, under the precision medicine platform, is met with challenges in targeting ligand and matrix material selection at nanoformulation stage. The past 5-year literatures show that the nanoparticulate targeting ligand and matrix material are not selected based upon the cancer omics profiles of patients. The expression of cancer cellular target receptors and metabolizing enzymes is primarily influenced by age, gender, race/ethnic group and geographical origin of patients. The personalized perspective of a nanomedicine cannot be realised with premature digestion of matrix and targeting ligand by specific metabolizing enzymes that are overexpressed by the patients, and unmatched targeting ligand to the majority of cell surface receptors overexpressed in cancer. Omics analysis of individual metabolizing enzyme and cancer cell surface receptor expressed in cancer facilitates targeting ligand and matrix material selection in nanomedicine development.

Student absenteeism affects students’ engagement in school and academic and professional success. While research documents a significant association between school bullying/fighting and student absenteeism due to fear of being at school or getting to school, little research has examined the association of adolescent dating violence (ADV) victimization with this type of absenteeism. This study examined the relationship between physical and/or sexual ADV victimization in the past year (dichotomized as yes or no), and number of days of student absenteeism due to feeling unsafe at school or on the way to school in the past month (dichotomized as any vs. none). We analyzed cross-sectional data from the 2019 Youth Risk Behavior Survey (YRBS), a nationally representative survey of U.S. high school students ( n = 9507). We conducted crude and multivariate regression models for the total sample and stratified by sex to assess our hypothesized association of ADV victimization and absenteeism; sex, grade, race/ethnicity, and sexual identity were included as covariates in adjusted models. Findings demonstrate that students reporting past year ADV victimization had 3.69 times the odds of student absenteeism due to feeling unsafe, when compared to students who did not report ADV victimization (95% CI: 3.06–4.45, p < 0.001). Sex-stratified models reveal that this effect is significantly stronger for males than for females, as indicated by non-overlapping confidence intervals (male AOR: 5.67, 95% CI: 4.18–7.68; female AOR: 2.95, 95% CI: 2.32–3.74). The multivariate models also show that Black and Latinx compared with White students, and lesbian/gay/bisexual/unsure compared with heterosexual students, had higher odds of student absenteeism due to feeling unsafe. Findings indicate the need to address ADV victimization and student absenteeism with integrated and gender-tailored responses, and with consideration of greater vulnerabilities for queer students and students of color.

X-linked lymphoproliferative disease (XLP) is either caused by loss of the SLAM-associated protein (SAP; XLP-1) or the X-linked inhibitor of apoptosis (XIAP; XLP-2). In both instances, infection with the oncogenic human Epstein Barr virus (EBV) leads to pathology, but EBV-associated lymphomas only emerge in XLP-1 patients. Therefore, we investigated the role of XIAP during B cell transformation by EBV. Using humanized mice, IAP inhibition in EBV-infected mice led to a loss of B cells and a tendency to lower viral titers and lymphomagenesis. Loss of memory B cells was also observed in four newly described patients with XIAP deficiency. EBV was able to transform their B cells into lymphoblastoid cell lines (LCLs) with similar growth characteristics to patient mothers’ LCLs in vitro and in vivo. Gene expression analysis revealed modest elevated lytic EBV gene transcription as well as the expression of the tumor suppressor cell adhesion molecule 1 (CADM1). CADM1 expression on EBV-infected B cells might therefore inhibit EBV-associated lymphomagenesis in patients and result in the absence of EBV-associated malignancies in XLP-2 patients.

Hepatocellular carcinoma (HCC) has one of the poorest survival rates among cancers. Using multi-regional sampling of nine resected HCC with different aetiologies, here we construct phylogenetic relationships of these sectors, showing diverse levels of genetic sharing, spanning early to late diversification. Unlike the variegated pattern found in colorectal cancers, a large proportion of HCC display a clear isolation-by-distance pattern where spatially closer sectors are genetically more similar. Two resected intra-hepatic metastases showed genetic divergence occurring before and after primary tumour diversification, respectively. Metastatic tumours had much higher variability than their primary tumours, suggesting that intra-hepatic metastasis is accompanied by rapid diversification at the distant location. The presence of co-existing mutations offers the possibility of drug repositioning for HCC treatment. Taken together, these insights into intra-tumour heterogeneity allow for a comprehensive understanding of the evolutionary trajectories of HCC and suggest novel avenues for personalized therapy., Hepatocellular carcinoma has one of the poorest survival rates amongst cancers. Here, the authors highlight the intra-tumour heterogeneity of this disease, finding that spatially closer tumour sectors are genetically more similar and that intra-hepatic metastasis is accompanied by rapid genetic diversification.

Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Accepted version We acknowledge H.M. Kang, S. Das, A. Tan, F. Zhang, J. Terhorst, P.-R. Loh, and G. Hellenthal for helpful discussions and support from all participants and clinical research coordinators of the contributing cohorts and studies: the TTSH Healthy Control Workgroup, the SEED cohort, the Asian Sudden Cardiac Death in Heart Failure Study, the Singapore Heart Failure Outcomes and Phenotypes (SHOP) cohort, the Asian neTwork for Translational Research and Cardiovascular Trials (ATTRaCT), the Parkinson’s Disease Study, the Peranakan Genome Study, the Platinum Asian Genomes Project, the Bariatric Surgery Study, the National Heart Centre Singapore Biobank and SingHEART cohorts, and the GUSTO and S-PRESTO study groups. This study was supported by Singapore’s A*STAR (core funding and IAF-PP H17/01/a0/007), BMRC (SPF2014/001, SPF2013/002, SPF2014/003, SPF2014/004, and SPF2014/005), NMRC (CIRG/1371/2013, CIRG/1417/2015, CIRG/1488/ 2018, CSA-SI/0012/2017, CG/017/2013, CG/M006/2017_NHCS, TCR/013- NNI/2014, STaR/0011/2012, STaR2013/001, STaR/014/2013, STaR/0026/ 2015, TCR/006-NUHS/2013, TCR/012-NUHS/2014, TCR/004-NUS/2008, TCR/012-NUHS/2014, and center grants 2010-13 and 2013-2017), NRF (NRFF2016-03), National University of Singapore, SingHealth and DukeNUS, and Alexandra Health small innovative grant SIGII/15203 and funding from Huazhong University of Science and Technology, the Tanoto Foundation, the Lee Foundation, the Boston Scientific Investigator Sponsored Research Program and Bayer, the NSF (DEB-1753489), and the Alfred P. Sloan Foundation. The computation was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg).