Tumor phylogeography reveals block-shaped spatial heterogeneity and the mode of evolution in Hepatocellular Carcinoma.

Solid tumors are complex ecosystems with heterogeneous 3D structures, but the spatial intra-tumor heterogeneity (sITH) at the macroscopic (i.e., whole tumor) level is under-explored. Using a phylogeographic approach, we sequence genomes and transcriptomes from 235 spatially informed sectors across 13 hepatocellular carcinomas (HCC), generating one of the largest datasets for studying sITH. We find that tumor heterogeneity in HCC segregates into spatially variegated blocks with large genotypic and phenotypic differences. By dissecting the transcriptomic heterogeneity, we discover that 30% of patients had a "spatially competing distribution" (SCD), where different spatial blocks have distinct transcriptomic subtypes co-existing within a tumor, capturing the critical transition period in disease progression. Interestingly, the tumor regions with more advanced transcriptomic subtypes (e.g., higher cell cycle) often take clonal dominance with a wider geographic range, rejecting neutral evolution for SCD patients. Extending the statistical tests for detecting natural selection to many non-SCD patients reveal varying levels of selective signal across different tumors, implying that many evolutionary forces including natural selection and geographic isolation can influence the overall pattern of sITH. Taken together, tumor phylogeography unravels a dynamic landscape of sITH, pinpointing important evolutionary and clinical consequences of spatial heterogeneity in cancer.

SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics.

Recent advancements in spatial transcriptomic technologies have enabled the measurement of whole transcriptome profiles with preserved spatial context. However, limited by spatial resolution, the measured expressions at each spot are often from a mixture of multiple cells. Computational deconvolution methods designed for spatial transcriptomic data rarely make use of the valuable spatial information as well as the neighboring similarity information. Here, we propose SONAR, a Spatially weighted pOissoN-gAmma Regression model for cell-type deconvolution with spatial transcriptomic data. SONAR directly models the raw counts of spatial transcriptomic data and applies a geographically weighted regression framework that incorporates neighboring information to enhance local estimation of regional cell type composition. In addition, SONAR applies an additional elastic weighting step to adaptively filter dissimilar neighbors, which effectively prevents the introduction of local estimation bias in transition regions with sharp boundaries. We demonstrate the performance of SONAR over other state-of-the-art methods on synthetic data with various spatial patterns. We find that SONAR can accurately map region-specific cell types in real spatial transcriptomic data including mouse brain, human heart and human pancreatic ductal adenocarcinoma. We further show that SONAR can reveal the detailed distributions and fine-grained co-localization of immune cells within the microenvironment at the tumor-normal tissue margin in human liver cancer.

MADE: A Computational Tool for Predicting Vaccine Effectiveness for the Influenza A(H3N2) Virus Adapted to Embryonated Eggs.

Seasonal Influenza H3N2 virus poses a great threat to public health, but its vaccine efficacy remains suboptimal. One critical step in influenza vaccine production is the viral passage in embryonated eggs. Recently, the strength of egg passage adaptation was found to be rapidly increasing with time driven by convergent evolution at a set of functionally important codons in the hemagglutinin (HA1). In this study, we aim to take advantage of the negative correlation between egg passage adaptation and vaccine effectiveness (VE) and develop a computational tool for selecting the best candidate vaccine virus (CVV) for vaccine production. Using a probabilistic approach known as mutational mapping, we characterized the pattern of sequence evolution driven by egg passage adaptation and developed a new metric known as the adaptive distance (AD) which measures the overall strength of egg passage adaptation. We found that AD is negatively correlated with the influenza H3N2 vaccine effectiveness (VE) and ~75% of the variability in VE can be explained by AD. Based on these findings, we developed a computational package that can Measure the Adaptive Distance and predict vaccine Effectiveness (MADE). MADE provides a powerful tool for the community to calibrate the effect of egg passage adaptation and select more reliable strains with minimum egg-passaged changes as the seasonal A/H3N2 influenza vaccine.

Evolution under Spatially Heterogeneous Selection in Solid Tumors.

Spatial genetic and phenotypic diversity within solid tumors has been well documented. Nevertheless, how this heterogeneity affects temporal dynamics of tumorigenesis has not been rigorously examined because solid tumors do not evolve as the standard population genetic model due to the spatial constraint. We therefore, propose a neutral spatial (NS) model whereby the mutation accumulation increases toward the periphery; the genealogical relationship is spatially determined and the selection efficacy is blunted (due to kin competition). In this model, neutral mutations are accrued and spatially distributed in manners different from those of advantageous mutations. Importantly, the distinctions could be blurred in the conventional model. To test the NS model, we performed a three-dimensional multiple microsampling of two hepatocellular carcinomas. Whole-genome sequencing (WGS) revealed a 2-fold increase in mutations going from the center to the periphery. The operation of natural selection can then be tested by examining the spatially determined clonal relationships and the clonal sizes. Due to limited migration, only the expansion of highly advantageous clones can sweep through a large part of the tumor to reveal the selective advantages. Hence, even multiregional sampling can only reveal a fraction of fitness differences in solid tumors. Our results suggest that the NS patterns are crucial for testing the influence of natural selection during tumorigenesis, especially for small solid tumors.

Variation in the life history strategy underlies functional diversity of tumors.

Classical r- vs. K-selection theory describes the trade-offs between high reproductive output and competitiveness and guides research in evolutionary ecology. While its impact has waned in the recent past, cancer evolution may rekindle it. Herein, we impose r- or K-selection on cancer cell lines to obtain strongly proliferative r cells and highly competitive K cells to test ideas on life-history strategy evolution. RNA-seq indicates that the trade-offs are associated with distinct expression of genes involved in the cell cycle, adhesion, apoptosis, and contact inhibition. Both empirical observations and simulations based on an ecological competition model show that the trade-off between cell proliferation and competitiveness can evolve adaptively. When the r and K cells are mixed, they exhibit strikingly different spatial and temporal distributions. Due to this niche separation, the fitness of the entire tumor increases. The contrasting selective pressure may operate in a realistic ecological setting of actual tumors.

Deep sequencing reveals the genomic characteristics of lung adenocarcinoma presenting as ground-glass nodules (GGNs).

BACKGROUND: The concept of multi-step progression from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (ADC) has been proposed, and ground-glass nodules (GGNs) may play a critical role during the early lung tumorigenesis. We present the first comprehensive description of the genomic architecture of GGNs to unravel the genetic basis of GGN. METHODS: We investigated 30 GGN-like lungs ADC by performing >1,000× whole-exome sequencing (WES) and characterized the genomic variations and evaluate the relationship between the clinicopathologic and molecular characteristics in this disease. RESULTS: Despite the low somatic mutation burden, GGNs exhibited high intratumor heterogeneity (ITH) characterized by the proportion of subclonal mutations. Different mutagenesis shaped the genomes of GGN during cancer evolution and were mostly featured by molecular clock-like signatures that occur in clonal mutations and defective DNA mismatch signatures that occur in subclonal mutations. Moreover, 10.7-67.1% clonal mutations occurred after whole-genome doubling (WGD), indicating that WGD could be a frequent truncal event in GGNs. Samples with WGD showed higher genomic instability but lower ITH. These GGNs were characterized by recurrent focal copy-number changes that are highly associated with tumorigenesis, with only two genes (EGFR and RBM10) that were recurrently mutated. Additionally, GGNs with different pathological subtypes or computed tomography (CT) features exhibited distinct genetic characteristics. Lepidic predominant or pure GGNs in CT images carried a lower mutation burden and had a relatively stable genome than nonlepidic or mixed GGNs. GGNs with RBM10 mutations tended to accompany a pathologically lepidic pattern, indicating RBM10 may drive the distinct subtype of lung cancer with better prognosis. CONCLUSIONS: These findings facilitated interpreting the genomic characteristics of GGNs, provided insight into the early stages of lung cancer evolution, and possessed potential clinical significance.

Using ultra-sensitive next generation sequencing to dissect DNA damage-induced mutagenesis.

Next generation sequencing (NGS) technologies have dramatically improved studies in biology and biomedical science. However, no optimal NGS approach is available to conveniently analyze low frequency mutations caused by DNA damage treatments. Here, by developing an exquisite ultra-sensitive NGS (USNGS) platform "EasyMF" and incorporating it with a widely used supF shuttle vector-based mutagenesis system, we can conveniently dissect roles of lesion bypass polymerases in damage-induced mutagenesis. In this improved mutagenesis analysis pipeline, the initial steps are the same as in the supF mutation assay, involving damaging the pSP189 plasmid followed by its transfection into human 293T cells to allow replication to occur. Then "EasyMF" is employed to replace downstream MBM7070 bacterial transformation and other steps for analyzing damage-induced mutation frequencies and spectra. This pipeline was validated by using UV damaged plasmid after its replication in lesion bypass polymerase-deficient 293T cells. The increased throughput and reduced cost of this system will allow us to conveniently screen regulators of translesion DNA synthesis pathway and monitor environmental genotoxic substances, which can ultimately provide insight into the mechanisms of genome stability and mutagenesis.

Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution.

The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 "polymorphic" SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model, MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors.

Age-related immune clearance of hepatitis B virus infection requires the establishment of gut microbiota.

A unique feature of hepatitis B virus (HBV) infection in humans is that viral clearance heavily depends on the age of exposure. However, the reason for this remains unclear. Here we show that gut microbiota contribute to the age dependence of HBV immunity in a hydrodynamic transfection mouse model. Although adult (12-wk-old) C3H/HeN mice cleared HBV within 6 wk postinjection (wpi), their young (6-wk-old) counterparts remained HBV-positive at 26 wpi. Sterilization of gut microbiota from 6 to 12 wk of age using antibiotics prevented adult mice from rapidly clearing HBV. Young mice with the Toll-like-receptor (TLR) 4 mutation (C3H/HeJ) exhibited rapid HBV clearance. The results suggest that an immuno-tolerating pathway to HBV prevailed in young mice, before the establishment of gut bacteria, through a TLR4-dependent pathway and that the maturation of gut microbiota in adult mice stimulated liver immunity, resulting in rapid HBV clearance.

New insights into the evolutionary rate of hepatitis B virus at different biological scales.

UNLABELLED: The evolutionary rates of hepatitis B virus (HBV) estimated using contemporary sequences are 10(2) to 10(4) times higher than those derived from archaeological and genetic evidence. This discrepancy makes the origin of HBV and the time scale of its spread, both of which are critical for studying the burden of HBV pathogenicity, largely unresolved. To evaluate whether the dual demands (i.e., adaptation within hosts and colonization between hosts) of the viral life cycle affect this conundrum, the HBV quasispecies dynamics within and among hosts from a family consisting of a grandmother, her 5 children, and her 2 granddaughters, all of whom presumably acquired chronic HBV through mother-to-infant transmission, were examined by PCR cloning and next-generation sequencing methods. We found that the evolutionary rate of HBV between hosts was considerably lower than that within hosts. Moreover, the between-host substitution rates of HBV decreased as transmission numbers between individuals increased. Both observations were due primarily to changes at nonsynonymous rather than synonymous sites. There were significantly more multiple substitutions than expected for random mutation processes, and 97% of substitutions were changed from common to rare amino acid residues in the database. Continual switching between colonization and adaptation resulted in a rapid accumulation of mutations at a limited number of positions, which quickly became saturated, whereas substitutions at the remaining regions occurred at a much lower rate. Our study may help to explain the time-dependent HBV substitution rates reported in the literature and provide new insights into the origin of the virus. IMPORTANCE: It is known that the estimated hepatitis B virus (HBV) substitution rate is time dependent, but the reason behind this observation is still elusive. We hypothesize that owing to the small genome size of HBV, transmission between hosts and adaptation within hosts must exhibit high levels of fitness trade-offs for the virus. By studying the HBV quasispecies dynamics for a chain of sequentially infected transmissions within a family, we found the HBV substitution rate between patients to be negatively correlated with the number of transmissions. Continual switching between hosts resulted in a rapid accumulation of mutations at a limited number of genomic sites, which quickly became saturated in the short term. Nevertheless, substitutions at the remaining regions occurred at a much lower rate. Therefore, the HBV substitution rate decreased as the divergence time increased.