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Non-small cell lung cancer (NSCLC) is known to carry heavy mutation load. Besides smoking, cytidine deaminase APOBEC3B plays a key role in the mutation process of NSCLC. APOBEC3B is also reported to be upregulated and predicts bad prognosis in NSCLC. However, targeting APOBEC3B high NSCLC is still a big challenge. Here we show that APOBEC3B upregulation is significantly associated with immune gene expression, and APOBEC3B expression positively correlates with known immunotherapy response biomarkers, including: PD-L1 expression and T-cell infiltration in NSCLC. Importantly, APOBEC mutational signature is specifically enriched in NSCLC patients with durable clinical benefit after immunotherapy and APOBEC mutation count can be better than total mutation in predicting immunotherapy response. In together, this work provides evidence that APOBEC3B upregulation and APOBEC mutation count can be used as novel predictive markers in guiding NSCLC checkpoint blockade immunotherapy.

Bacterial DNA methylation occurs at diverse sequence contexts and plays important functional roles in cellular defense and gene regulation. Existing methods for detecting DNA modification from nanopore sequencing data do not effectively support de novo study of unknown bacterial methylomes. In this work, we observed that a nanopore sequencing signal displays complex heterogeneity across methylation events of the same type. To enable nanopore sequencing for broadly applicable methylation discovery, we generated a training dataset from an assortment of bacterial species and developed a method, named nanodisco (https://github.com/fanglab/nanodisco), that couples the identification and fine mapping of the three forms of methylation into a multi-label classification framework. We applied it to individual bacteria and the mouse gut microbiome for reliable methylation discovery. In addition, we demonstrated the use of DNA methylation for binning metagenomic contigs, associating mobile genetic elements with their host genomes and identifying misassembled metagenomic contigs.This work describes nanodisco, a tool for de novo identifying DNA methylation in bacterial species and microbiomes using nanopore sequencing and for performing metagenomic binning using microbial DNA methylation patterns.

Sex differences in innate and adaptive immune responses are known, and women generally mount a stronger immune response than men. Cancer immunotherapy, represented by immune checkpoint inhibitors (ICIs), has revolutionized the treatment of cancer, and sex differences in cancer immunotherapy are just starting to be revealed. Here, we summarize recent research progress concerning sex differences in cancer immunotherapy efficacy. On their own, ICIs tend to be more effective in male cancer patients compared with female patients, while ICIs combined with chemotherapy tend to be more effective in female patients than male patients. Male tumors are usually more antigenic than female tumors, and this is reflected by their increased number of tumor mutations and cancer germline antigens. The biomarker tumor mutational burden (TMB), which reflects tumor antigenicity, is more effective at predicting immunotherapy response for female lung cancer patients than for male patients. In this review, we propose different therapeutic strategies for the different sexes: For male cancer patients, the immune environment should be enhanced, whereas for female cancer patients, tumor antigenicity should be enhanced.

Quantum magnets provide the simplest example of strongly interacting quantum matter, yet they continue to resist a comprehensive understanding above one spatial dimension. We explore a promising framework in two dimensions, the Dirac spin liquid (DSL) — quantum electrodynamics (QED 3 ) with 4 Dirac fermions coupled to photons. Importantly, its excitations include magnetic monopoles that drive confinement. We address previously open key questions — the symmetry actions on monopoles on square, honeycomb, triangular and kagome lattices. The stability of the DSL is enhanced on triangular and kagome lattices compared to bipartite (square and honeycomb) lattices. We obtain the universal signatures of the DSL on triangular and kagome lattices, including those of monopole excitations, as a guide to numerics and experiments on existing materials. Even when unstable, the DSL helps unify and organize the plethora of ordered phases in correlated two-dimensional materials. The Dirac spin liquid is a candidate description for the strongly correlated behaviour of some quantum magnets. Song et al. study the symmetry dependence physics of monopole excitations and argue that the lattice-dependent consequences for magnetic ordering may provide a unifying picture for 2D quantum magnetism.

The synthesis of all-carbon tetrasubstituted olefins under mild reaction conditions is challenging because of the inevitable issues including significant steric hindrance and the uncontrolled Z/E stereoselectivity. In this paper, we report the synthesis of all-carbon tetrasubstituted alkenes from readily available carboxylic acids and alkenyl triflates with the synergistic catalysis of cyclo-octa-1,5-diene(tetramethyl-1,4-benzoquinone)nickel and visible light under an air atmosphere, thus avoiding the need for a glovebox or a Schlenk line. A wide range of aromatic carboxylic acids and cyclic and acyclic alkenyl triflates undergo the C-C coupling process smoothly, forming structurally diverse alkenes stereospecifically in moderate to good yields. The practicality of the method is further illustrated by the late-stage modification of complex molecules, the one pot synthesis and gram-scale applications. This is an important step towards the valuable utilization of carboxylic acids, and it also simplifies the experimental operation of metallophotoredox catalysis with moisture sensitive nickel(0) catalysis. Tetrasubstituted olefins have been explored as chemical synthons and can sometime have useful photophysical properties, but are sometimes difficult to synthesize with high selectivity in mild conditions. Here the authors present a method to make tetrasubstituted olefins via dual photo- and nickel catalysis, without the need for an inert atmosphere.

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool “sigminer” has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis.

Immunotherapy, represented by immune checkpoint inhibitors (ICI), is transforming the treatment of cancer. However, only a small percentage of patients show response to ICI, and there is an unmet need for biomarkers that will identify patients who are more likely to respond to immunotherapy. The fundamental basis for ICI response is the immunogenicity of a tumor, which is primarily determined by tumor antigenicity and antigen presentation efficiency. Here, we propose a method to measure tumor immunogenicity score (TIGS), which combines tumor mutational burden (TMB) and an expression signature of the antigen processing and presenting machinery (APM). In both correlation with pan-cancer ICI objective response rates (ORR) and ICI clinical response prediction for individual patients, TIGS consistently showed improved performance compared to TMB and other known prediction biomarkers for ICI response. This study suggests that TIGS is an effective tumor-inherent biomarker for ICI-response prediction. In the last decade a new kind of cancer therapy, called immunotherapy, has changed how doctors treat cancer patients. These therapies mean that previously incurable cancers, including some skin and lung cancers, can now sometimes be cured. Immunotherapy does this by activating the patient’s own immune system so that it will attack the cancer cells. But for this to work, the cancer cells, much like invading bacteria or viruses, need to be recognized as foreign. Cancer cells contain many DNA mutations that cause the cell to make mutated proteins it would not normally make. These proteins betray the cancer cells as foreign to the immune system. The extent to which cancer cells make mutated proteins – also called the ‘tumor mutational burden’ – can sometimes predict whether a patient will respond to immunotherapy. In general, patients with a high mutational burden respond well to immunotherapy, but overall fewer than one in five cancer patients are cured by this treatment. An important question is whether there are better ways of predicting if a cancer patient will respond to immunotherapy. Wang et al. have addressed this problem by adding a second variable to the prediction. Not only do cancer cells have to make mutated proteins, but these proteins also have to be ‘seen’ by immune cells. Cancer cells, like normal cells, have mechanisms to present protein fragments to immune cells. Wang et al. hypothesized that patients with a high mutational burden would not respond to immunotherapy if they were lacking the machinery required for presenting protein fragments. The experiments revealed that measuring both tumor mutational burden and the levels of the machinery that presents protein fragments resulted in better predictions of patients’ responses to immunotherapy than measuring tumor mutational burden alone. Additionally, this new way of predicting responses to immunotherapy was successful across many different cancer types. The combined measurement of these two variables could be applied in clinical practice as a way to predict cancer patients’ response to immunotherapy. This should allow doctors to determine which course of treatment will work best for a specific patient. The results also suggest that inducing tumor cells to produce more of the machinery that presents protein fragments to the immune system could increase their responsiveness to immunotherapy. In the future, predicting how well a patient will respond to immunotherapy could become even more accurate by incorporating additional variables.

Foodborne protein hydrolysates exhibit biological activity that may be therapeutic in a number of human disease settings. Hemp peptides (HP) generated by controlled hydrolysis of hemp proteins have a number of health benefits and are of pharmaceutical value. In the present study, we produce small molecular weight HP from hemp seed and investigate its anticancer properties in Hep3B human liver cancer cells. We demonstrate that HP treatment increased apoptosis, reduced cell viability, and reduced cell migration in Hep3B human liver cancer cells without affecting the normal liver cell line L02. We correlate these phenotypes with increased cellular ROS levels, upregulation of cleaved caspase 3 and Bad, and downregulation of antiapoptotic Bcl‐2. HP treatment led to increased Akt and GSK‐3β phosphorylation, with subsequent downregulation of β‐catenin, suggesting β‐catenin signaling modulation as a critical mechanism by which HP exhibits anticancer properties. Our findings suggest HP are of potential therapeutic interest for liver cancer treatment. Anti‐cancer property of new hemp protein hydrolysates on human liver cancers

Intensive selection pressure constrains the evolutionary trajectory of SARS-CoV-2 genomes and results in various novel variants with distinct mutation profiles. Point mutations, particularly those within the receptor binding domain (RBD) of SARS-CoV-2 spike (S) protein, lead to the functional alteration in both receptor engagement and monoclonal antibody (mAb) recognition. Here, we review the data of the RBD point mutations possessed by major SARS-CoV-2 variants and discuss their individual effects on ACE2 affinity and immune evasion. Many single amino acid substitutions within RBD epitopes crucial for the antibody evasion capacity may conversely weaken ACE2 binding affinity. However, this weakened effect could be largely compensated by specific epistatic mutations, such as N501Y, thus maintaining the overall ACE2 affinity for the spike protein of all major variants. The predominant direction of SARS-CoV-2 evolution lies neither in promoting ACE2 affinity nor evading mAb neutralization but in maintaining a delicate balance between these two dimensions. Together, this review interprets how RBD mutations efficiently resist antibody neutralization and meanwhile how the affinity between ACE2 and spike protein is maintained, emphasizing the significance of comprehensive assessment of spike mutations.

Background The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China has been declared a public health emergency of international concern. The cardiac injury is a common condition among the hospitalized patients with COVID-19. However, whether N terminal pro B type natriuretic peptide (NT-proBNP) predicted outcome of severe COVID-19 patients was unknown. Methods The study initially enrolled 102 patients with severe COVID-19 from a continuous sample. After screening out the ineligible cases, 54 patients were analyzed in this study. The primary outcome was in-hospital death defined as the case fatality rate. Research information and following-up data were obtained from their medical records. Results The best cut-off value of NT-proBNP for predicting in-hospital death was 88.64 pg/mL with the sensitivity for 100% and the specificity for 66.67%. Patients with high NT-proBNP values (> 88.64 pg/mL) had a significantly increased risk of death during the days of following-up compared with those with low values (≤88.64 pg/mL). After adjustment for potential risk factors, NT-proBNP was independently correlated with in-hospital death. Conclusion NT-proBNP might be an independent risk factor for in-hospital death in patients with severe COVID-19. Trial registration ClinicalTrials, NCT04292964. Registered 03 March 2020,