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Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 703 records · Page 39Linked to original sources

Conformations of the Human Immunodeficiency Virus (HIV-1) Envelope Glycoproteins in Detergents and Styrene-Maleic Acid Lipid Particles (SMALPs)

The mature human immunodeficiency virus (HIV-1) envelope glycoprotein (Env) trimer, which consists of non-covalently associated gp120 exterior and gp41 transmembrane subunits, mediates virus entry into cells. The pretriggered (State-1) Env conformation is the major target for broadly neutralizing antibodies (bNAbs), whereas receptor-induced downstream Env conformations elicit immunodominant, poorly neutralizing antibody (pNAb) responses. To examine the contribution of membrane anchorage to the maintenance of the metastable pretriggered Env conformation, we compared wild-type and State-1-stabilized Envs solubilized in detergents or in styrene-maleic acid (SMA) copolymers. SMA directly incorporates membrane lipids and resident membrane proteins into lipid nanodiscs (SMALPs). The integrity of the Env trimer in SMALPs was maintained at both 4{degrees}C and room temperature. By contrast, Envs solubilized in Cymal-5, a non-ionic detergent, were unstable at room temperature, although their stability was improved at 4{degrees}C and after incubation with the entry inhibitor BMS-806. Envs solubilized in ionic detergents were relatively unstable at either temperature. Comparison of Envs solubilized in Cymal-5 and SMA at 4{degrees}C revealed subtle differences in bNAb binding to the gp41 membrane-proximal external region (MPER), consistent with these distinct modes of Env solubilization. Otherwise, the antigenicity of the Cymal-5- and SMA- solubilized Envs was remarkably similar, both in the absence and presence of BMS-806. However, both solubilized Envs were recognized differently from the mature membrane Env by specific bNAbs and pNAbs. Thus, detergent-based and detergent-free solubilization at 4{degrees}C alters the pretriggered membrane Env conformation in consistent ways, indicating that loss of Env association with the membrane results in default state(s). IMPORTANCEThe human immunodeficiency virus (HIV-1) envelope glycoproteins (Envs) in the viral membrane mediate virus entry into the host cell and are targeted by neutralizing antibodies elicited by natural infection or vaccines. Detailed studies of membrane proteins rely on purification procedures that allow the proteins to maintain their natural conformation. In this study, we show that a styrene-maleic acid (SMA) copolymer can extract HIV-1 Env from a membrane without the use of detergents. The Env in SMA is more stable at room temperature than Env in detergents. The purified Env in SMA maintains many but not all of the characteristics expected of the natural membrane Env. Our results underscore the importance of the membrane environment to the native conformation of HIV-1 Env. Purification methods that bypass the need for detergents could be useful tools for future studies of HIV-1 Env structure and its interaction with receptors and antibodies.

microbiology↗

MsPBRsP: Multi-scale Protein Binding Residues Prediction Using Language Model

Accurate prediction of protein binding residues (PBRs) from sequence is important for the understanding of cellular activity and helpful for the design of novel drug. However, experimental methods are time-consuming and expensive. In recent years, a lot of computational predictors based on machine learning and deep learning models are proposed to reduce such consumption. But those methods often use MSA tools such as PSI-BLAST or NetSurfP to generate some statistical features and enter them into predictive models as necessary supplementary input. The input generation process normally takes long time, and there is no standard to specify which and how many statistic results should be provided to a prediction model. In addition, prediction of PBRs relies on residue local context, but the most appropriate scale is undetermined. Most works pre-selected certain residue features as input and a scale size based on expertise for certain type of PBRs. In this study, we propose a general tool-free end-to-end framework that can be applied to all types of PBRs, Multi-scale Protein Binding Residues Prediction using language model (MsPBRsP). We adopt a pre-trained language model ProtTrans to save the large consumption caused by MSA tools, and use protein sequence alone as input to our model. To ease scale size uncertainty, we construct multi-size windows in attention layer and multi-size kernels in convolutional layer. We test our framework on various benchmark datasets including PBRs from protein-protein, protein-nucleotide, protein-small ligand, heterodimer, homodimer and antibody-antigen interactions. Compared with existing state-of-the-art methods, MsPBRsP achieves superior performance with less running time and higher prediction rates on every PBRs prediction task. Specifically, we boost F1 score by 27.1% and AUPRC score by 7.6% on NSP448 dataset and decrease running time from over 10 minutes to under 0.1s on average. The source code and datasets are available at https://github.com/biolushuai/MsPBRsP-for-multiple-PBRs-prediction.

bioinformatics↗

The scale-invariant covariance spectrum of brain-wide activity

Understanding neural activity organization is vital for deciphering brain function. By recording whole-brain calcium activity in larval zebrafish during hunting and spontaneous behaviors, we find that the shape of the neural activity space, described by the neural covariance spectrum, is scale-invariant: a smaller, randomly sampled cell assembly resembles the entire brain. This phenomenon can be explained by Euclidean Random Matrix theory, where neurons are reorganized from anatomical to functional positions based on their correlations. Three factors contribute to the observed scale invariance: slow neural correlation decay, higher functional space dimension, and neural activity heterogeneity. In addition to matching data from zebrafish and mice, our theory and analysis demonstrate how the geometry of neural activity space evolves with population sizes and sampling methods, thus revealing an organizing principle of brain-wide activity.

neuroscience↗

A novel method for multiple phenotype association studies based on genotype and phenotype network

Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new insight to analyze multiple phenotypes, which can explore whether phenotypes and genotypes might be related to each other at a higher level of cellular and organismal organization. In this paper, we first develop a bipartite signed network by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). The GPN can be constructed by a mixture of quantitative and qualitative phenotypes and is applicable to binary phenotypes with extremely unbalanced case-control ratios in large-scale biobank datasets. We then apply a powerful community detection method to partition phenotypes into disjoint network modules based on GPN. Finally, we jointly test the association between multiple phenotypes in a network module and a single nucleotide polymorphism (SNP). Simulations and analyses of 72 complex traits in the UK Biobank show that multiple phenotype association tests based on network modules detected by GPN are much more powerful than those without considering network modules. The newly proposed GPN provides a new insight to investigate the genetic architecture among different types of phenotypes. Multiple phenotypes association studies based on GPN are improved by incorporating the genetic information into the phenotype clustering. Notably, it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy.

genetics↗

Protective effect of plasma neutralization from prior SARS-CoV-2 Omicron infection against BA.5 subvariant symptomatic reinfection

From December 2022 to January 2023, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections caused by BA.5 and BF.7 subvariants of B.1.1.529 (Omicron) swept across mainland China. It is crucial to estimate the protective effect of the neutralizing antibodies generated by such mass infections against the next potential SARS-CoV-2 reinfection wave, especially if driven by CH.1.1 or XBB.1.5. Previously, we recruited and continuously followed a cohort of individuals that experienced Omicron BA.1, BA.2, and BA.5 breakthrough infections, as well as a control cohort with no history of SARS-CoV-2 infection. In the previously uninfected cohort, the total symptomatic infection rate surveyed during the outbreak was 91.6%, while the symptomatic reinfection rate was 32.9%, 10.5%, and 2.8% among individuals with prior Omicron BA.1, BA.2 and BA.5 infection, respectively, with median intervals between infections of 335, 225 and 94 days. Pseudovirus neutralization assays were performed in plasma samples collected from previously Omicron BA.1-infected individuals approximately 3 months before the outbreak. Results indicate a robust correlation between the plasma neutralizing antibody titers and the protective effect against symptomatic reinfection. The geometric mean of the 50% neutralizing titers (NT50) against D614G, BA.5, and BF.7 were 2.0, 2.5, and 2.3-fold higher in individuals without symptomatic reinfection than in those with symptomatic reinfection (p < 0.01). Low plasma neutralizing antibody titer (below the geometric mean of NT50) was associated with an enhanced cumulative risk of symptomatic reinfection, with a hazard ratio (HR) of 23.55 (95% CI: 9.23-60.06) against BF.7 subvariant. Importantly, neutralizing antibodies titers post one month after BF.7/BA.5 breakthrough infections against CH.1.1 and XBB.1.5 are similar to that against BF.7 from individuals with prior BA.1 infection while not experiencing a symptomatic BF.7/BA.5 reinfection (plasma collected 3 months before the outbreak), suggesting that the humoral immunity generated by the current BF.7/BA.5 breakthrough infection may provide protection against CH.1.1 and XBB.1.5 symptomatic reinfection wave for 4 months. Of note, the higher hACE2 binding of XBB.1.5 may reduce the protection period since the potential increase of infectivity.

immunology↗

Network Pharmacology and Bioinformatics Methods Reveal the Mechanism of Sishenwan in the Treatment of diabetic nephropathy

Objective. In order to decipher the bioactive components and potential mechanisms of the traditional Chinese medicine (TCM) formula Sishenwan (SSW) for diabetic nephropathy (DN), we integrated network pharmacology and bioinformatics. Methods. The candidate compounds of SSW and relative targets were obtained from the TCMSP, BATMAN-TCM, SiwssTartgetPrediction, STITCH, and ChEMBL web servers. The UniProt database was used to translate the target names into gene names, and then constructed the herbal-compound-target network. DN-related targets were ascertained based on OMIM, CTD, GeneCards, DisGeNET, and GEO. Furthermore, there was a protein-protein interaction (PPI) network to explore the overlapping targets between SSW and DN, which focused on screening the pivotal targets by topology. GO and KEGG enrichment analyses were carried out to further understand the potential functions associated with the effect of SSW against DN. Eventually, molecular docking simulations were performed to validate the binding affinity between major bioactive components and hub genes. Results. A total of 120 candidate active compounds and 542 corresponding drug targets were derived, in which 195 targets intersected with DN. Then, KEGG pathway analysis showed that several signaling pathways were closely related to the process of SSW against DN, including the AGE-RAGE signaling pathway in diabetic complications, the TNF signaling pathway, and IL-17 signaling pathway, ect. The PPI network analysis identified PTGS2, CREB1, ESR1, TNF, IL1B, INS, AKT1, PPARG, and JUN were the top 9 hub targets. The molecular docking confirmed that the bioactive compounds of SSW had a firm binding affinity with hub targets. Conclusions. As a whole, the present study revealed that SSW exerted therapeutic effects on DN via modulating multi-targets with multi-compounds through multi-pathways.

bioinformatics↗

CRACD, a gatekeeper restricting proliferation, heterogeneity, and immune evasion of small cell lung cancer

Small cell lung cancer (SCLC) is aggressive with limited therapeutic options. Despite recent advances in targeted therapies and immunotherapies, therapy resistance is a recurring issue, which might be partly due to tumor cell plasticity, a change in cell fate. Nonetheless, the mechanisms underlying tumor cell plasticity and immune evasion in SCLC remain elusive. CRACD, a capping protein inhibitor that promotes actin polymerization, is frequently inactivated in SCLC. Cracd knockout (KO) transforms preneoplastic cells into SCLC tumor-like cells and promotes in vivo SCLC development driven by Rb1, Trp53, and Rbl2 triple KO. Cracd KO induces neuroendocrine (NE) plasticity and increases tumor cell heterogeneity of SCLC tumor cells via dysregulated NOTCH1 signaling by actin cytoskeleton disruption. CRACD depletion also reduces nuclear actin and induces EZH2-mediated H3K27 methylation. This nuclear event suppresses the MHC-I genes and thereby depletes intratumoral CD8+ T cells for accelerated SCLC tumorigenesis. Pharmacological blockade of EZH2 inhibits CRACD-negative SCLC tumorigenesis by restoring MHC-I expression and immune surveillance. Unsupervised single-cell transcriptomics identifies SCLC patient tumors with concomitant inactivation of CRACD and downregulated MHC-I pathway. This study defines CRACD, an actin regulator, as a tumor suppressor that limits cell plasticity and immune evasion and proposes EZH2 blockade as a viable therapeutic option for CRACD-negative SCLC.

cancer biology↗

Tumor Niche Network-Defined Subtypes Predict Immunotherapy Response of Esophageal Squamous Cell Cancer

Despite the promising outcomes of immune checkpoint blockade (ICB), resistance to ICB presents a new challenge. Therefore, selecting patients for specific ICB applications is crucial for maximizing therapeutic efficacy. Herein we curated 69 human esophageal squamous cell cancer (ESCC) patients tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network transcriptional signatures of T cells, myeloid cells, and fibroblasts define distinct ESCC subtypes characterized by T cell exhaustion, Interferon (IFN) a/b signaling, TIGIT enrichment, and specific marker genes. Furthermore, this approach classifies ESCC patients into ICB responders and non-responders, as validated by liquid biopsy single-cell transcriptomics. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and predicting ICB responses in ESCC patients.

cancer biology↗

Omics Analysis Unveils the Pathway Involved in the Purple Coloration in Tomato Seedling and Fruits

The purple tomato variety Indigo Rose(InR) is favored due to its bright appearance and abundant anthocyanins. SlHY5 is associated with anthocyanin biosynthesis in Indigo Rose plants. However, residual anthocyanins still present in Slhy5 seedlings and fruit peel indicated there was an anthocyanin induction pathway that is independent of HY5 in plants. The molecular mechanism of color formation in Indigo Rose and Slhy5 mutants is unclear. In this study, we performed omics analysis to clarify the regulatory network underlying coloration in seedling and fruit peel of Indigo Rose and Slhy5 mutant. Results showed that the total amount of anthocyanins in both seedling and fruit of InR were significantly higher than those in Slhy5 mutant and most genes associated with anthocyanin biosynthesis exhibited higher expression levels in InR, suggesting that SlHY5 play pivotal roles in flavonoid biosynthesis both in tomato seedlings and fruit. Yeast two-hybrid (Y2H) results revealed that SlBBX24 physically interacts with SlAN2-like and SlAN2, while SlWRKY44 could interact with SlAN11 protein. Unexpectedly, both SlPIF1 and SlPIF3 were found to interact with SlBBX24, SlAN1 and SlJAF13 by yeast two-hybrid assay. Suppression of SlBBX24 by virus-induced gene silencing (VIGS) retarded the purple coloration of the fruit peel, indicating an important role of SlBBX24 in the regulation of anthocyanin accumulation. These results deepen the understanding of purple color formation in tomato seedling and fruits in an HY5-dependent or independent manner via excavating the genes involved in anthocyanin biosynthesis based on omics analysis.

molecular biology↗

Neutralization of SARS-CoV-2 BQ.1.1 and XBB.1.5 by Breakthrough Infection Sera from Previous and Current Waves in China

SARS-CoV-2 is continuing to evolve and diversify, with an array of various Omicron sub-lineages, including BA.5, BA.2.75, BN.1, BF.7, BQ.1, BQ.1.1, XBB and XBB.1.5, now circulating globally at recent time. In this study, we evaluated the neutralization sensitivity of a comprehensive panel of Omicron subvariants to sera from different clinical cohorts, including individuals who received homologous or heterologous booster vaccinations, vaccinated people who had Delta or BA.2 breakthrough infection in previous waves, and patients who had BA.5 or BF.7 breakthrough infection in the current wave in China. All the Omicron subvariants exhibited substantial neutralization evasion, with BQ.1, BQ.1.1, XBB.1, and XBB.1.5 being the strongest escaped subvariants. Sera from Omicron breakthrough infection, especially the recent BA.5 or BF.7 breakthrough infection, exhibited higher neutralizing activity against all Omicron sub-lineages, indicating the chance of BA.5 and BF.7 being entirely replaced by BQ or XBB subvariants in China in a short-term might be low. We also demonstrated that the BQ and XBB subvariants were the most resistant viruses to monoclonal antibodies. Continuing to monitor the immune escape of SARS-CoV-2 emerging variants and developing novel broad-spectrum vaccines and antibodies are still crucial.

immunology↗

Stroke induces early recurrent vascular events by inflammasome-dependent atherosclerotic plaque rupture

The risk of early recurrent events after stroke remains high despite currently established secondary prevention strategies. Risk is particularly high in patients with atherosclerosis, with more than 10% of patients experiencing early recurrent events. However, despite the enormous medical burden of this clinical phenomenon, the underlying mechanisms leading to increased vascular risk and recurrent stroke are largely unknown. Here, using a novel mouse model of stroke-induced recurrent ischemia, we show that stroke leads to activation of the AIM2 inflammasome in vulnerable atherosclerotic plaques via an increase of circulating cell-free DNA from the ischemic tissue. Enhanced plaque inflammation post-stroke results in plaque destabilization and atherothrombosis, finally leading to arterio-arterial embolism and recurrent stroke within days after the index stroke. We confirm key steps of plaque destabilization also after experimental myocardial infarction and in carotid artery plaque samples from patients with acute stroke. Neutralization of cell-free DNA by DNase treatment or inhibition of inflammasome activation reduced the rate of stroke recurrence after experimental stroke. Our findings present an explanation for the high recurrence rate after incident ischemic events in atherosclerotic patients. The detailed mechanisms uncovered here provide so far clinically uncharted therapeutic targets for which we show high efficacy to prevent recurrent events. Targeting DNA-mediated inflammasome activation after remote tissue injury represents a promising avenue for further clinical development in the prevention of early recurrent events.

immunology↗

Unraveling the causal genes and transcriptomic determinants of human telomere length

Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogated TL-modulated genes and their potential functions. We found that placental TL is relatively longer across human tissues and which maintenance is mostly connected to genes responsible for alternative lengthening of telomeres. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identified 20 novel genetic associations and provided increased polygenic determination of human TL. Next, we integrated the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 31 likely causal genes, among which 4 were functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improved the prediction performance of human TL. This study deepened our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

genetics↗

Duck pan-genome reveals two transposon-derived structural variations caused bodyweight enlarging and white plumage phenotype formation during evolution

Structural variations (SVs) are a major source of domestication and improvement traits, however SV profiles of duck and their phenotypic impacts largely hidden. We present the first duck pan-genome constructed using five genome assemblies capturing [~]40.98 Mb new sequences. This pan-genome together with high-depth sequencing data ([~]46.5X) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchoring in a gene body or regulatory region are linked to ducks domestication and improvement. By combining quantitative genetics with molecular experiments, we dissect how TE-derived SVs change gene expression of IGF2BP1 and generate a novel transcript of MITF, shaping bodyweight and white plumage. In the IGF2BP1 locus, the TE-derived SV explains the largest effect on bodyweight among avian species (27.61% of phenotypic variation). Our findings highlight the importance of using a pan-genome as a reference in genomics studies and explore the roles of TE-derived SVs in trait formation and in livestock breeding.

genetics↗

EB1 decoration of microtubule lattice facilitates spindle-kinetochore lateral attachment in Plasmodium male gametogenesis

Faithful chromosome segregation of 8 duplicated haploid genomes into 8 daughter male gametes is essential for male gametogenesis and mosquito transmission of Plasmodium. Plasmodium evolves the endomitosis for this multinucleated cell division. However, the mechanism underlying the spindle-kinetochore attachment remains elusive. End-binding proteins (EBs) are the conserved microtubule (MT) plus-end binding proteins and play an important role in regulating MT plus-end dynamics. Here we report that Plasmodium EB1 is a unique orthologue distinct from the canonical eukaryotic EB1. Both in vitro and in vivo assays revealed that Plasmodium EB1 lost MT plus-end tracking but gained MT-lattice affinity. This MT-binding feature of EB1 is contributed by both the CH domain and the linker region. EB1-deficient parasites produce male gametocytes that develop to the anucleated male gametes, leading to defective mosquito transmission of parasite. EB1 is localized at the nucleoplasm of male gametocytes. Upon gametogenesis, EB1 decorates the full-length of spindle MTs and regulates spindle structure. The kinetochores attach to spindle MTs laterally throughout three rounds of endomitosis and this attachment is EB1-dependent. Consequently, impaired spindle-kinetochore attachment was observed in EB1-deficient parasites. These results indicate that a parasite-specific EB1 with MT-lattice affinity has evolved to fulfill the spindle-kinetochore lateral attachment in male gametogenesis.

microbiology↗

Ultra-Fast Bioorthogonal Spin-Labeling and Distance Measurements in Mammalian Cells Using Small, Genetically Encoded Tetrazine Amino Acids

Studying protein structures and dynamics directly in the cellular environments in which they function is essential to fully understand the molecular mechanisms underlying cellular processes. Site-directed spin-labeling (SDSL)--in combination with double electron-electron resonance (DEER) spectroscopy--has emerged as a powerful technique for determining both the structural states and the conformational equilibria of biomacromolecules. In-cell DEER spectroscopy on proteins in mammalian cells has thus far not been possible due to the notable challenges of spin-labeling in live cells. In-cell SDSL requires exquisite biorthogonality, high labeling reaction rates and low background signal from unreacted residual spin label. While the bioorthogonal reaction must be highly specific and proceed under physiological conditions, many spin labels display time-dependent instability in the reducing cellular environment. Additionally, high concentrations of spin label can be toxic. Thus, an exceptionally fast bioorthogonal reaction is required that can allow for complete labeling with low concentrations of spin-label prior to loss of signal. Here we utilized genetic code expansion to site-specifically encode a novel family of small, tetrazine-bearing non-canonical amino acids (Tet-v4.0) at multiple sites in green fluorescent protein (GFP) and maltose binding protein (MBP) expressed both in E. coli and in human HEK293T cells. We achieved specific and quantitative spin-labeling of Tet-v4.0-containing proteins by developing a series of strained trans-cyclooctene (sTCO)-functionalized nitroxides--including a gem-diethyl-substituted nitroxide with enhanced stability in cells--with rate constants that can exceed 106 M-1 s-1. The remarkable speed of the Tet-v4.0/sTCO reaction allowed efficient spin-labeling of proteins in live HEK293T cells within minutes, requiring only sub-micromolar concentrations of sTCO-nitroxide added directly to the culture medium. DEER recorded from intact cells revealed distance distributions in good agreement with those measured from proteins purified and labeled in vitro. Furthermore, DEER was able to resolve the maltose-dependent conformational change of Tet-v4.0-incorporated and spin-labeled MBP in vitro and successfully discerned the conformational state of MBP within HEK293T cells. We anticipate the exceptional reaction rates of this system, combined with the relatively short and rigid side chains of the resulting spin labels, will enable structure/function studies of proteins directly in cells, without any requirements for protein purification. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/525763v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1251523org.highwire.dtl.DTLVardef@18ee6ddorg.highwire.dtl.DTLVardef@d6d4b0org.highwire.dtl.DTLVardef@259a53_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

AlphaFold Prediction of Structural Ensembles of Disordered Proteins

Deep learning methods of predicting protein structures have reached an accuracy comparable to that of high-resolution experimental methods. It is thus possible to generate accurate models of the native states of hundreds of millions of proteins. An open question, however, concerns whether these advances can be translated to disordered proteins, which should be represented as structural ensembles because of their heterogeneous and dynamical nature. Here we show that the inter-residue distances predicted by AlphaFold for disordered proteins can be used to construct accurate structural ensembles. These results illustrate the application to disordered proteins of deep learning methods originally trained for predicting the structures of folded proteins.

biophysics↗

Spatial transcriptomics analysis of neoadjuvant cabozantinib and nivolumab in advanced hepatocellular carcinoma identifies independent mechanisms of resistance and recurrence

Novel immunotherapy combination therapies have improved outcomes for patients with hepatocellular carcinoma (HCC), but responses are limited to a subset of patients and recurrence can also occur. Little is known about the inter- and intra-tumor heterogeneity in cellular signaling networks within the HCC tumor microenvironment (TME) that underlie responses to modern systemic therapy. We applied spatial transcriptomics (ST) profiling to characterize the tumor microenvironment in HCC resection specimens from a clinical trial of neoadjuvant cabozantinib, a multi-tyrosine kinase inhibitor that primarily blocks VEGF, and nivolumab, a PD-1 inhibitor in which 5 out of 15 patients were found to have a pathologic response. ST profiling demonstrated that the TME of responding tumors was enriched for immune cells and cancer associated fibroblasts (CAF) with pro-inflammatory signaling relative to the non-responders. The enriched cancer-immune interactions in responding tumors are characterized by activation of the PAX5 module, a known regulator of B cell maturation, which colocalized with spots with increased B cell markers expression suggesting strong activity of these cells. Cancer-CAF interactions were also enriched in the responding tumors and were associated with extracellular matrix (ECM) remodeling as there was high activation of FOS and JUN in CAFs adjacent to tumor. The ECM remodeling is consistent with proliferative fibrosis in association with immune-mediated tumor regression. Among the patients with major pathologic response, a single patient experienced early HCC recurrence. ST analysis of this clinical outlier demonstrated marked tumor heterogeneity, with a distinctive immune-poor tumor region that resembles the non-responding TME across patients and was characterized by cancer-CAF interactions and expression of cancer stem cell markers, potentially mediating early tumor immune escape and recurrence in this patient. These data show that responses to modern systemic therapy in HCC are associated with distinctive molecular and cellular landscapes and provide new targets to enhance and prolong responses to systemic therapy in HCC.

cancer biology↗

FastRecomb: Fast inference of genetic recombination rates in biobank scale data

While rates of recombination events across the genome (genetic maps) are fundamental to genetic research, the majority of current studies only use one standard map. There is evidence suggesting population differences in genetic maps, and thus estimating population-specific maps are of interest. While the recent availability of biobank-scale data offers such opportunities, current methods are not efficient at leveraging very large sample sizes. The most accurate methods are still linkage-disequilibrium (LD)-based methods that are only tractable for a few hundred samples. In this work, we propose a fast and memory-efficient method for estimating genetic maps from population genotyping data. Our method, FastRecomb, leverages the efficient positional Burrows-Wheeler transform (PBWT) data structure for counting IBD segment boundaries as potential recombination events. We used PBWT blocks to avoid redundant counting of pairwise matches. Moreover, we used a panel smoothing technique to reduce the noise from errors and recent mutations. Using simulation, we found that FastRecomb achieves state-of-the-art performance at 10k resolution, in terms of correlation coefficients between the estimated map and the ground truth. This is mainly due to the fact that FastRecomb can effectively take advantage of large panels comprising more than hundreds of thousands of haplotypes. At the same time, other methods lack the efficiency to handle such data. We believe further refinement of FastRecomb would deliver more accurate genetic maps for the genetics community.

bioinformatics↗