Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor

Methadone maintenance treatment (MMT) is commonly used for controlling opioid dependence, preventing withdrawal symptoms, and improving the quality of life of heroin-dependent patients. A steady-state plasma concentration of methadone enantiomers, a measure of methadone metabolism, is an index of treatment response and efficacy of MMT. Although the methadone metabolism pathway has been partially revealed, no genome-wide pharmacogenomic study has been performed to identify genetic determinants and characterize genetic mechanisms for the plasma concentrations of methadone R- and S-enantiomers. This study was the first genome-wide pharmacogenomic study to identify genes associated with the plasma concentrations of methadone R- and S-enantiomers and their respective metabolites in a methadone maintenance cohort. After data quality control was ensured, a dataset of 344 heroin-dependent patients in the Han Chinese population of Taiwan who underwent MMT was analyzed. Genome-wide single-locus and haplotype-based association tests were performed to analyze four quantitative traits: the plasma concentrations of methadone R- and S-enantiomers and their respective metabolites. A significant single nucleotide polymorphism (SNP), rs17180299 (raw p = 2.24 × 10−8), was identified, accounting for 9.541% of the variation in the plasma concentration of the methadone R-enantiomer. In addition, 17 haplotypes were identified on SPON1, GSG1L, and CYP450 genes associated with the plasma concentration of methadone S-enantiomer. These haplotypes accounted for approximately one-fourth of the variation of the overall S-methadone plasma concentration. The association between the S-methadone plasma concentration and CYP2B6, SPON1, and GSG1L were replicated in another independent study. A gene expression experiment revealed that CYP2B6, SPON1, and GSG1L can be activated concomitantly through a constitutive androstane receptor (CAR) activation pathway. In conclusion, this study revealed new genes associated with the plasma concentration of methadone, providing insight into the genetic foundation of methadone metabolism. The results can be applied to predict treatment responses and methadone-related deaths for individualized MMTs.

Normalization and batch correction are critical steps in processing single-cell RNA sequencing (scRNA-seq) data, which remove technical effects and systematic biases to unmask biological signals of interest. Although a number of computational methods have been developed, there is no guidance for choosing appropriate procedures in different scenarios. In this study, we assessed the performance of 28 scRNA-seq noise reduction procedures in 55 scenarios using simulated and real datasets. The scenarios accounted for multiple biological and technical factors that greatly affect the denoising performance, including relative magnitude of batch effects, the extent of cell population imbalance, the complexity of cell group structures, the proportion and the similarity of nonoverlapping cell populations, dropout rates and variable library sizes. We used multiple quantitative metrics and visualization of low-dimensional cell embeddings to evaluate the performance on batch mixing while preserving the original cell group and gene structures. Based on our results, we specified technical or biological factors affecting the performance of each method and recommended proper methods in different scenarios. In addition, we highlighted one challenging scenario where most methods failed and resulted in overcorrection. Our studies not only provided a comprehensive guideline for selecting suitable noise reduction procedures but also pointed out unsolved issues in the field, especially the urgent need of developing metrics for assessing batch correction on imperceptible cell-type mixing.

Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD (http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/).

4116 Background: Despite the therapeutic promise of ICIs for patients (pts) with some advanced malignancies, they are FDA-approved for only a few GI cancer pts. In NSCLC, melanoma and urothelial carcinoma, there is emerging data that pts who experience IRAEs while on ICIs have improved outcomes compared with pts who do not. This association in GI cancer pts has not been reported. Methods: We retrospectively analyzed outcomes for metastatic GI cancer pts receiving ICIs for FDA-approved indications (later-line MSI-H tumors, 2nd line hepatocellular carcinoma (HCC), 3rd line PD-L1+ gastric (GA)/gastroesophageal junction (GEJ) adenocarcinoma), at Vanderbilt Ingram Cancer Center, Winship Cancer Institute and Stanford Cancer Institute. Our primary aim was to compare progression-free survival (PFS) and overall survival (OS) between pts who did and did not experience IRAEs. Secondary aims were comparison of these outcomes within pts who experienced IRAEs, by initial IRAE severity (Grade (G)3/G4 vs G1/G2) (CTCAE v5.0), time-to-onset (TTO) (≤ 6 weeks (w) vs > 6 w) and management (steroids vs drug cessation vs observation). PFS and OS were determined by Kaplan-Meier (KM) analysis; KM comparisons were done by the logrank test. Results: Between 1/2015-12/2018 61 GI cancer pts with HCC (28), colorectal cancer (27) and GA/GEJ cancer (6) were treated with ICIs; median age was 63 years. The majority (59) received single-agent nivolumab or pembrolizumab while minority (2) received nivolumab and ipilimumab; median time on ICIs was 5.9 months (mos). Twenty-four pts experienced initial IRAEs (6 G3/G4, 18 G1/G2); median TTO was 3.8 mos. Pts who experienced any IRAE had improvements in PFS and OS compared to those who did not (PFS: 32.4 mos (95% confidence interval (CI), 32.4-not reached (NR)) vs 4.8 mos (95% CI, 2.9-8.7), p = 0.0001; OS: 32.4 mos (95% CI, 32.4-NR) vs 8.5 mos (95% CI, 6-NR), p = 0.0036). Among pts who experienced IRAEs, PFS and OS differences between above-specified subgroups did not meet statistical significance. Conclusions: GI cancer pts who experienced IRAEs while on ICIs had marked improvements in PFS and OS compared to those who did not, suggesting the predictive potential for IRAEs as a clinical biomarker in this population.

Hashimoto disease (HD) is an autoimmune thyroid disease resulting from complex interactions between genetic and environmental factors. The human leukocyte antigen (HLA) gene has been established to be involved in the susceptibility to HD. We aim to investigate the associations between HLA-B alleles and Han Chinese children with HD by both case-control and family-based studies. A total of 108 unrelated children with HD, 380 unrelated healthy controls, 58 trios of affected patients and their parents, and 75 trios of unaffected siblings and their parents were recruited. HLA-B genotyping was performed by polymerase chain reaction and detected with a sequence-specific oligonucleotide probes system. We found that B*46:01 allele (OR = 2.31, 95% CI 1.60-3.34, P(c) = 9.99 × 10(-5)) and carrier (OR = 3.28, 95% CI 2.10-5.11, P(c) = 1.35 × 10(-6)) were associated with HD risk. Transmission/disequilibrium test further confirmed an overtransmission of the B*46:01 (OR 2.55, 95% CI 1.36-6.10, P = 6.5 × 10(-3)). The findings were similar in females when stratified by gender. In conclusion, our results clearly identify that HLA-B*46:01 confers susceptibility to HD in Han Chinese children. Further studies with larger children cohort are required to confirm the role of B*46:01 in the development of HD.

Aim: This is the first systematic study to examine the population differentiation effect of DNA methylation on the treatment response and drug absorption, distribution, metabolism and excretion in multiple tissue types and cancer types. Materials & methods: We analyzed the whole methylome and transcriptome data of primary tumor tissues of four cancer types (breast, colon, head & neck and uterine corpus) and lymphoblastoid cell lines for African and European ancestry populations. Results: Ethnicity-associated CpG sites exhibited similar methylation patterns in the two studied populations, but the patterns differed between tumor tissues and lymphoblastoid cell lines. Ethnicity-associated CpG sites may have triggered gene expression, influenced drug absorption, distribution, metabolism and excretion, and showed tumorspecific patterns of methylation and gene regulation. Conclusion: Ethnicity should be carefully accounted for in future pharmacoepigenetics research.

Heroin dependent patients have a high incidence of HIV infection. In contrast to the gene expression method, we developed a systemic correlation analysis method built upon the results of pharmacogenomics study in a methadone maintenance treatment (MMT) cohort consisting of 344 Taiwanese heroin dependent patients. We identified genetic variants and their encoding proteins that may be involved with HIV infection and MMT treatment outcome. Cadherin 2 (CDH2) genetic determinants were identified through the genome-wide pharmacogenomic study. We found significant correlations among HIV infection status, plasma levels of CDH2, cytokine IL-7, ADAM10, and the treatment responses to methadone. Two single nucleotide polymorphisms located within CDH2 gene showed associations with blood pressure and plasma CDH2 concentration. Plasma concentration of CDH2 showed correlations with the level of cytokine IL-7, status of HIV infection, and urine morphine test result. Plasma level of IL-7 was correlated with corrected QT interval (QTc) and gooseflesh skin withdrawal symptom score, while level of ADAM10 was correlated with plasma concentrations of vitamin D metabolite, nicotine metabolite, and R-methadone. The results suggest a novel network involving HIV infection and methadone treatment outcome.