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Cancer-associated anemia promotes tumor progression, leads to poor quality of life in patients with cancer, and even obstructs the efficacy of immune checkpoint inhibitors therapy. However, the precise mechanism for cancer-associated anemia remains unknown and the feasible strategy to target cancer-associated anemia synergizing immunotherapy needs to be clarified. Here, we review the possible mechanisms of cancer-induced anemia regarding decreased erythropoiesis and increased erythrocyte destruction, and cancer treatment-induced anemia. Moreover, we summarize the current paradigm for cancer-associated anemia treatment. Finally, we propose some prospective paradigms to slow down cancer-associated anemia and synergistic the efficacy of immunotherapy.

Immunotherapies targeting cancer neoantigens are safe, effective, and precise. Neoantigens can be identified mainly by genomic techniques such as next-generation sequencing and high-throughput single-cell sequencing; proteomic techniques such as mass spectrometry; and bioinformatics tools based on high-throughput sequencing data, mass spectrometry data, and biological databases. Neoantigen-related therapies are widely used in clinical practice and include neoantigen vaccines, neoantigen-specific CD8+ and CD4+ T cells, and neoantigen-pulsed dendritic cells. In addition, neoantigens can be used as biomarkers to assess immunotherapy response, resistance, and prognosis. Therapies based on neoantigens are an important and promising branch of cancer immunotherapy. Unremitting efforts are needed to unravel the comprehensive role of neoantigens in anti-tumor immunity and to extend their clinical application. This review aimed to summarize the progress in neoantigen research and to discuss its opportunities and challenges in precision cancer immunotherapy.

In this study, a series of CuMgAl layered double oxides (CuMgAl-LDOs) were obtained via calcination of CuMgAl layered double hydroxides (CuMgAl-LDHs) synthesised via a co-precipitation method. The results show that CuMgAl-LDO can be prepared using an optimal Cu:Mg:Al molar ratio of 3:3:2, NaOH:Na2CO3 molar ratio of 2:1, and calcination temperature of 600 °C. CuMgAl-LDO is a characteristic of mesoporous material with a lamellar structure and large specific surface area. The removal efficiency of sulfameter (SMD) based on CuMgAl-LDO/persulfate (PS) can reach > 98% over a wide range of initial SMD concentrations (5–20 mg·L−1). The best removal efficiency of 99.49% was achieved within 120 min using 10 mg·L−1 SMD, 0.3 g·L−1 CuMgAl-LDO, and 0.7 mM PS. Kinetic analysis showed that the degradation of SMD was in accordance with a quasi-first-order kinetic model. The stability of the CuMgAl-LDO catalyst was verified by the high SMD removal efficiency (>97% within 120 min) observed after five recycling tests and low copper ion leaching concentration (0.89 mg·L−1), which is below drinking water quality standard of 1.3 mg·L−1 permittable in the U.S. Radical scavenging experiments suggest that SO 4 · − is the primary active species participating in the CuMgAl-LDO/PS system. Moreover, our mechanistic investigations based on the radical scavenging tests and X-ray photoelectron spectroscopy (XPS) results indicate that Cu(II)–Cu(III)–Cu(II) circulation is responsible for activating PS in the degradation of SMD and the degradation pathway for SMD was deduced. Accordingly, the results presented in this work demonstrate that CuMgAl-LDO may be an efficient and stable catalyst for the activation of PS during the degradation of organic pollutants.

Anti–PD-1/PD-L1 therapy, either by anti–PD-1 antibody or anti–PD-L1 antibody, has efficacy by reinvigorating tumor-infiltrating CD8 + T cells in a subset of patients with cancer, but it has unequal effects on heterogeneous CD8 + T cell populations. Hence, the subset crucial to efficacious PD-1 blockade therapy remains elusive. Here, we found an increase in tumor-infiltrating CD200 + cytotoxic T lymphocytes (CTLs) upon PD-1/PD-L1 blockade, with higher proportions of CD200 + T cells positively related to a favorable clinical outcome to anti–PD-1/PD-L1 therapy in three independent cohorts of patients with cancer. Using multiple mouse tumor models, we demonstrated that CD200 + CTLs are essential for efficacious anti–PD-L1 therapy. Mechanistically, we observed a unique chromatin landscape in CD200 + CTLs and found that these cells are enriched for tumor antigen–specific CTLs and have antitumor effector functions. Coinoculation of CD200 + CTLs with tumor cells led to robust tumor regression in two transplanted mouse models. Clinically, we found that infiltration of CD200 + CTLs into tumors could predict immunotherapy efficacy in six patient cohorts. Together, our findings reveal that CD200 + CTLs in the tumor microenvironment are crucial for efficacious anti–PD-1/PD-L1 therapy and could serve as a predictor of successful immunotherapy in the clinic.

Background Caspase-8 (Casp8) acts as an initiator in cell apoptosis signaling. However, the role of Casp8 in tuning the tumor immune microenvironment remains controversial due to the complicated crosstalk between immune-tolerogenic apoptotic cell death and immunogenic cell death cascades. Methods The Cancer Genome Atlas (TCGA) and publicly accessible immune checkpoint blockade (ICB)-treated cohorts were used to investigate the clinical relevance of Casp8. A tumor-bearing mouse model was used to characterize changes in the tumor microenvironment and to explore the efficacy of ICB treatment under Casp8 knockout conditions. Results By exploring TCGA datasets, we showed that the expression level of Casp8 was associated with an immuno-hot microenvironment across various solid tumor types. Casp8 deficiency leads to decreased CD8+ T cell infiltration and resistance to anti-PD-L1 therapy in a mouse model. Mechanistically, Casp8 deficiency or pharmacological disruption results in impaired ecto-calreticulin transition in tumor cells, which in turn hampers antigen presentation in draining lymph nodes. Furthermore, radiotherapy restored sensitivity to anti-PD-L1 treatment via elevated calreticulin surface expression. Conclusions Our data revealed a causative role of Casp8 in modulating the immunogenicity of tumor cells and responsiveness to ICB immunotherapies and proposed radiotherapy as a salvage approach to overcome Casp8 deficiency-mediated ICB resistance.

Immune checkpoint inhibitor (ICI) responses vary, and biomarkers for predicting responders are urgently needed. Growing evidence points to the association between programmed cell death protein ligand 2 (PDL2) and ICI benefits, while clinical evidences were lacking. Thus, we consolidated five public ICI-treated cohorts to investigate the association between PDL2 expression and ICI treatment prognosis. Immune cell signatures and IFN-γ signatures are investigated in The Cancer Genome Atlas (TCGA) dataset and later in ICI-treated cohorts to explore the association between PDL2 and antitumor immunity in the tumor microenvironment (TME). We found that immune cell signatures and IFN-γ signatures were enriched in the PDL2-high group in TCGA pooled cohorts and most cancers. Consistently, in ICI-treated cohorts, patients with high PDL2 expression experienced longer overall survival time (OS) and were more likely responsive to ICIs than patients with low PDL2 expression. Immune cell scores of the high PDL2 expression patients were significantly higher ( P < 0.05 ) than those of the low PDL2 expression patients in ICI-treated cohorts. In conclusion, our findings suggest that PDL2 is a potential predictive biomarker for ICIs.

In this work, atomic connectivity group contribution (ACGC) method is developed for predicting critical properties of organic compounds. Herein, a new group defining method, namely atomic adjacent group (AAG) method, is proposed to describe the relationship between core atom and its adjacent atoms. For distinguishing isomers effectively, the shape factor (SF) is used to describe the effect of molecular shape on group, and atomic connectivity factors (ACF) are defined for describing the position of each group in a molecule. The external and internal verification methods were utilized during the modelling process. Compared with AAG model, ARE decreased by 6.82-42.57 % when SF was considered and, ARE decreased by 24.19-62.25 % when both SF and ACF were applied as using the ACGC method. Accordingly, SF and ACF are effective in improving the group contribution method and ACGC method is accurate in calculating the properties of organic compounds.

Deterministic structure representation of polymers plays a crucial role in developing models for polymer property prediction and polymer design by data-centric approaches. Currently, unique structure representations of polymers, especially the polymers with heteroatomic backbones, are unavailable. In this contribution, we propose a so-called ring repeating unit (RRU) method that can uniquely represent polymers with a broad range of structure diversity. To prove the rationality of RRU-based structure representation for generating feature descriptors, a quantitative structure property relationship (QSPR) model for glass transition temperature (Tg) was established for 1321 polyimides with good accuracy (R2 = 0.8793). Comprehensive model validations including external, internal, and Y-random validations were performed, providing Tg prediction result with an average absolute error (AAE) of 19.38 ℃. It is believed that the as-developed RRU method allows for dealing with any macromolecular structure and targeted property, enabling for reliable polymer property prediction and high-performance polymer design by data-driven approaches.

Background Caspase-8 play as an initiator caspase of cell apoptosis signaling. However, the role of caspase-8 in tunning tumor immune microenvironment remains controversial due to a complicated crosstalk between immuno-tolerogenic apoptotic cell death and immunogenic cell death (ICD) cascades. Methods TCGA and publicly accessible immune checkpoint blockade (ICB)-treated cohort were introduced to investigate the clinical relevance of caspase-8. Tumor-bearing mouse model was used to characterize the change of tumor microenvironment and explore efficacy to ICB treatment in caspase-8 knockout condition. Results We showed that the expression level of Casp8 was associated with an immuno-hot microenvironment across various solid tumor types by exploring TCGA dataset. Casp8 deficiency led to decreased CD8+ T cell infiltration and resistance to αPD-L1 therapy in mouse model. Mechanistically, Casp8 deficiency or pharmacological disruption resulted in impaired ecto-calreticulin (ecto-CRT) transition on tumor cells, which in turn hampered antigen presentation in draining lymph node. Furthermore, radiotherapy restore the sensitivity to αPD-L1 treatment via elevated surface expression of CRT. Conclusions Our data revealed a causative role of Casp8 in modulating immunogenicity of tumor cells and responsiveness to immune checkpoint blockade immunotherapies and proposed that radiotherapy as a salvage approach to overcome Casp8 deficiency-mediated ICB resistance.

The thermodynamic properties at variable temperature and pressure, such as density (ρ) and viscosity (η) are necessary in chemical process design. The quantitative structure-property relationship (QSPR) is a quick and accurate method to obtain the properties from a large number of potential ionic liquids (ILs). The QSPR models for ρ and η may have “pseudo-high” robustness validated by leave-one-out cross-validation (LOO-CV) and weakened stability with the unbalanced data point distribution. A rigorous model evaluation method named the leave-one-ion-out cross-validation (LOIO-CV) was proposed to evaluate robustness of ILs QSPR models. Balancing the distribution of data points in ILs, two f(T,P,I)-QSPR models were developed with norm index (I) to predict ρ and η of ILs at variable temperature and pressure. LOIO-CV method can enhance the stability QSPR model in predicting the properties of ILs with new cations and anions, which is essential for data driven design of ILs.

BACKGROUND: Only a fraction of patients with advanced non-small cell lung cancer (NSCLC) respond well to immune checkpoint blockade (ICB) therapy. Here, we investigated whether Titin (TTN) mutation, which has been demonstrated to be a predictive biomarker in tissue-based analysis, can identify patients with a greater likelihood in response to ICB based on circulatory tumor DNA (ctDNA) sequencing. METHODS: In this retrospective analysis, 92 patients with advanced NSCLC from two independent cohorts who received ICB treatment were included. A probe panel covering all exons of TTN was developed and validated to detect TTN mutation in ctDNA. Baseline plasma samples were collected and subjected to ctDNA sequencing with the TTN probe panel. RESULTS: Of the 92 patients, 28.3% harbored TTN mutation in their baseline ctDNA. Progression-free survival was significantly improved in patients with the mutated TTN (212 days and 334.5 days for cohort 1 and 2) compared to those without the mutation (113 days and 147 days for cohort 1 and 2). Objective response to ICB treatment (40% for TTN(mut) and 15.8% for TTN(wt) in cohort 1; 50% for TTN(mut) and 23.4% for TTN(wt) in cohort 2) was common in patients with mutated TTN. Stratified analysis showed a generally predictive potential of TTN mutation in patients with advanced NSCLC. CONCLUSIONS: The presence of mutated TTN in pre-treatment peripheral blood was associated with favorable objective response and survival with ICB administration. Therefore, circulatory TTN mutation may be applicable for guiding ICB immunotherapy in patients with NSCLC.

During the course of tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous. Consequently, the tumor mass might be infiltrated by diverse immune-related components, including the cytokine/chemokine environment, cytotoxic activity, or immunosuppressive elements. This immunological heterogeneity is universally presented spatially or varies temporally along with tumor evolution or therapeutic intervention across almost all solid tumors. The heterogeneity of anti-tumor immunity shows a profound association with the progression of disease and responsiveness to treatment, particularly in the realm of immunotherapy. Therefore, an accurate understanding of tumor immunological heterogeneity is essential for the development of effective therapies. Facilitated by multi-regional and -omics sequencing, single cell sequencing, and longitudinal liquid biopsy approaches, recent studies have demonstrated the potential to investigate the complexity of immunological heterogeneity of the tumors and its clinical relevance in immunotherapy. Here, we aimed to review the mechanism underlying the heterogeneity of the immune microenvironment. We also explored how clinical assessments of tumor heterogeneity might facilitate the development of more effective personalized therapies.

Reaction acceleration is a hot topic in recent years since it is very useful for rapid reaction screening and small-scale synthesis on a short timescale. It is known that the rates of chemical reactions are often accelerated in confined volumes (small droplets or thin films) where the unique chemical reactivities of molecules at the air–droplet/thin film interface, usually different from that in the bulk and gas phases, play a dominant role in acceleration. The Leidenfrost effect was employed to create small levitated droplets with no net charge. These droplets can accelerate many kinds of organic reactions. Our first accelerated synthesis of a series of organoimido-functionalized polyoxometalate (POM) clusters using Leidenfrost droplets with product analysis by electrospray ionization mass spectrometry (ESI-MS) demonstrated that this method can be successfully extended to the synthesis of inorganic/organic hybrids, a very promising area for developing POM-based functional materials. Comparable amounts of synthetic products [Mo6O18(NC6H4R)]2− (R = H (6), m/z 477; p-i-C3H7 (7), m/z 498; p-OCH3 (8), m/z 492; p-NO2 (9), m/z 500) were prepared within minutes in Leidenfrost droplets versus in hours in the corresponding bulk reactions under the same reaction conditions in the presence of the DCC catalyst, suggesting that both concentration and interfacial effects are pivotal in causing reaction acceleration in the Leidenfrost droplet. Compared to the conventional bulk reactions, the acceleration factors (AFs) were 92, 136, 126, and 89 for the four model reactions (1)–(4), respectively. We also found out that substitution affects the rate of reactions occurring in droplets, and hence the magnitude of AF. The rates increase in the order of R = NO2 < H < i-C3H7 < OCH3, in which the electron-donating groups (i.e., R = OCH3, i-C3H7) on the benzene ring are more favorable to the reaction than the electron-withdrawing group (i.e., R = NO2). This experimental result is in good agreement with the DFT calculation which indicates that the free-energy barriers for the direct imidoylization of POM with RNH2 are linearly correlated with the basicity constants (pKb) of amines.

With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

Background The gene ENPEP encodes glutamyl aminopeptidase, which can cut N‐terminal aspartic acid from angiotensin II, and is related to tumorigenesis and immune microenvironment, however, the association between the expression of ENPEP and benefits of immune checkpoint inhibitors (ICIs) has had no investigation. Methods We assess the immunotherapeutic predictive performance of ENPEP expression and mutation in multiple cohorts, including one discovery cohort (Pender cohort), four validation cohorts (Hugo cohort; Liu cohort; Mariathasan cohort; Zhao cohort), and one mutation cohort (Miao cohort). Cohorts from The Cancer Genome Atlas (TCGA) were used to explore mechanism and analysis prognosis. Results In the discovery cohort, patients with lower ENPEP expression had superior response rates (47.2% vs. 36.1%) and over‐all survival (OS) (HR [95% CI] = 0.61 [0.39–0.96]; p = 0.032) compared with those with higher ENPEP expression. The association between ENPEP and immunotherapy efficacy was consistently observed in validation cohorts (Hugo: OS HR [95% CI] = 0.41 [0.11–1.45], p = 0.158; Liu: OS HR [95% CI] = 0.73 [0.44–1.20], p = 0.211; Mariathasan: OS HR [95% CI] = 0.84 [0.65–1.09], p = 0.181; Zhao: OS HR [95% CI] = 0.20 [0.04–1.01], p = 0.033; Pooled cohort: OS HR [95% CI] = 0.76 [0.61–0.95], p = 0.015), and in the mutation cohort (ENPEP mutation vs. wild type (WT), OS HR [95% CI] = 0.46 [0.26–0.93], p = 0.017). Reliably, ENPEP is associated with M2 macrophage infiltration and activation in TCGA. Conclusions Our results demonstrated ENPEP is a potential biomarker to classify patients’ response to ICIs treatment.

Despite the unprecedented success of immune checkpoint inhibitors (ICIs) as anti-cancer therapy, it remains a prevailing clinical need to identify additional mechanisms underlying ICI therapeutic efficacy and potential drug resistance. Here, using lineage tracking in cancer patients and tumor-bearing mice, we demonstrate that erythroid progenitor cells lose their developmental potential and switch to the myeloid lineage. Single-cell transcriptome analyses reveal that, notwithstanding quantitative differences in erythroid gene expression, erythroid differentiated myeloid cells (EDMCs) are transcriptionally indistinguishable from their myeloid-originated counterparts. EDMCs possess multifaceted machinery to curtail T cell-mediated anti-tumor responses. Consequently, EDMC content within tumor tissues is negatively associated with T cell inflammation for the majority of solid cancers; moreover, EDMC enrichment, in accordance with anemia manifestation, is predictive of poor prognosis in various cohorts of patients undergoing ICI therapy. Together, our findings reveal a feedforward mechanism by which tumors exploit anemia-triggered erythropoiesis for myeloid transdifferentiation and immunosuppression.

Radiotherapy is an effective regimen for cancer treatment alone or combined with chemotherapy or immunotherapy. The direct effect of radiotherapy involves radiation-induced DNA damage, and most studies have focused on this area to improve the efficacy of radiotherapy. Recently, the immunomodulatory effect of radiation on the tumour microenvironment has attracted much interest. Dying tumour cells can release multiple immune-related molecules, including tumour-associated antigens, chemokines, and inflammatory mediators. Then, immune cells are attracted to the irradiated site, exerting immunostimulatory or immunosuppressive effects. CC chemokines play pivotal roles in the trafficking process. The CC chemokine family includes 28 members that attract different immune subsets. Upon irradiation, tumour cells or immune cells can release different CC chemokines. Here, we mainly discuss the importance of CCL2, CCL3, CCL5, CCL8, CCL11, CCL20 and CCL22 in radiotherapy. In irradiated normal tissues, released chemokines induce epithelial to mesenchymal transition, thus promoting tissue injury. In the tumour microenvironment, released chemokines recruit cancer-associated cells, such as tumour-infiltrating lymphocytes, myeloid-derived suppressor cells and tumour-associated macrophages, to the tumour niche. Thus, CC chemokines have protumour and antitumour properties. Based on the complex roles of CC chemokines in the response to radiation, it would be promising to target specific chemokines to alleviate radiation-induced injury or promote tumour control.

The aquatic ecological environment is being threatened from overuse of pesticides, and the aquatic toxicity toward rainbow trout (Oncorhynchus mykiss) plays a significant role in environmental risk assessment of agrochemicals. In the present study, 2 norm index formulas were developed, from which several norm descriptors were derived. A quantitative structure-activity relationship (QSAR) model was established for the prediction of acute toxicity (median lethal concentration) toward rainbow trout of various pesticides. Results indicated that the present QSAR model presented an R2 of 0.8053. Meanwhile, internal validation (QLOO 2 = 0.7606), external validation (Rtraining 2 = 0.8011, Rtesting 2 = 0.8108), Y-randomization test, and applicability domain analysis further demonstrated the stability, reliability, and wide application domain of the present QSAR model. Accordingly, these norm descriptors might be applicable to the structures of pesticides for predicting the acute toxicity to aquatic organism. Environ Toxicol Chem 2020;39:352-358. © 2019 SETAC.

The degradation of organic contaminants in aquatic systems has raised immense attention worldwide, and the second-order rate constant ([Formula: see text]) of water pollutants oxidized by sulfate radical anion is an important index for assessing the degradation efficiency of organics. Herein, a new norm mathematical formula is defined. Based on this, four new descriptors are proposed and a QSPR model is developed for predicting [Formula: see text] using 30 families of emerging organic pollutants in water. The statistical results fully prove that this model has good fitting effect and stability with R2 of 0.8862, Q2LOO of 0.8466, and Q25-fold of 0.8329, respectively. The validation results including cross validation, applicability domain analysis, and model comparison show that this model has good robustness, predictive performance, and reliability. These decent results indicate that the new norm mathematical formula is effective in calculating descriptors and the norm indexes have a great application for evaluating the transformation fate of organic pollutants by sulfate radical in aquatic systems.

The evaluation of eco-toxicity of ionic liquids (ILs) in the aquatic environment is essential for their safe utilization and QSTR approach plays an important role in obtaining the eco-toxicity data of ILs with diverse structures. Usually, the descriptors used to build QSTR model were made up of anion and cation descriptors, and their interactions were often neglected to some extent. In this work, based on the optimization of the ILs structure, a new set of descriptors were proposed to describe the interaction between anions and cations, and some new atomic distribution matrices were constructed to calculate norm descriptors of ILs, anion and cation. A norm index-based QSTR model was built to predict the eco-toxicity of ILs toward Leukemia rat cell line (IPC-81). This model has satisfactory statistical results with the R2 of 0.954 and RMSE of 0.241, respectively. Furthermore, leave-one-out cross-validation and applicability domain results showed good stability and predictability of this model. This approach showed that the interaction between cations and anions could be reflected by optimizing the whole structure of ILs which might play an important role for describing the eco-toxicity of ILs. Therefore, it is further suggested that the norm descriptors would be applicable to predict the eco-toxicity of ILs towards IPC-81.

Enthalpy of vaporization (∆Hv) is an important physicochemical property and has been widely used in chemical industry and process design. In this work, based on the concept of norm index proposed by our group, a QSPR model was developed to predict ∆Hv at the boiling point for 13 kinds of organic compounds including chain and cyclic hydrocarbons, alcohols, ketones, carboxylic acids and amines etc. The results showed that this model had satisfactory predictive performance with the squared correlation coefficient R2 of 0.9503, the Fisher's criterion F of 378.84 and the average absolute relative deviation of 3.17%. The internal validation, external validation and applicability domain analysis results indicated the robustness and reliability of this model. Moreover, comparison results demonstrated that this model performed well both in accuracy and stability. The satisfactory results further suggested that the norm index can be applied to the calculation of ∆Hv for organic compounds.

Introduction Whether the efficacy of programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors declines with senescence remains controversial for lung adenocarcinoma (LUAD). Responsiveness to anti–PD-1/PD-L1 therapy is thought to rely on neoantigen exposure and immune elements in the tumor microenvironment. In this study, we explored the features of the tumor immune microenvironment in elderly patients with treatment-naive LUAD. Methods Transcriptome profiles and clinical characteristics of patients with LUAD were retrieved from The Cancer Genome Atlas as a discovery cohort. Immune cell infiltration (quantified by a single-sample gene set enrichment analysis), immunoregulatory molecule expression, and mutational patterns (from The Cancer Immunome Atlas) were compared between young and elderly patients. Immune cell infiltration was verified by immunohistochemistry using a validation cohort including 105 treatment-naive patients with LUAD. A tissue microarray consisting of 120 LUAD patients was used in the immunohistochemistry validation. Results Activated CD8+ T cell numbers increased slightly with age, but cytolytic molecules in T cells (granzyme B [GZMB], perforin 1 [PRF1], granzyme A [GZMA], granzyme M [GZMM], and granulysin [GNLY]) gradually declined. PD-L1 expression was not associated with age; however, a number of immunosuppressive elements beyond PD-L1 were upregulated in aging patients, including regulatory T cells and co-inhibitory molecules, for example, TIM-3, TIGIT, and HHLA2. Finally, senescence was accompanied by a loss of clonal neoantigens, which is believed to be correlated with responsiveness to immune checkpoint inhibitors. Conclusions Elderly patients were characterized by increased numbers of CD8+ T cells and impaired cytolytic molecule expression. The observed immune signature was also associated with a loss of clonal neoantigens and the accumulation of immunosuppressive elements. These findings show a unique immune microenvironment in senescence and support biomarker-guided candidate identification for anti–PD-1/PD-L1 therapeutic strategies for elderly patients with LUAD.

Ovarian tumor domain-containing ubiquitin aldehyde binding protein 1 (OTUB1) is overexpressed in many cancers and plays an important role in tumor progression and metastasis. However, the molecular mechanisms underlying OTUB1 overexpression are not clear. In this study, we found that estrogen-related receptor alpha (ERRα, also called NR3B1) binds to OTUB1 promoter and regulates its expression in colorectal cancer. Furthermore, ERRα promoted the migration of CRC cells by inducing vimentin expression via OTUB1. Our data show that OTUB1 is a novel target of ERRα and indicate that ERRα-OTUB1 signaling may play a significant role in CRC metastasis.

Therapeutic radiation can result in substantially different survival outcomes for patients with non-small cell lung cancer (NSCLC). Measures for identification of patients who can benefit most throughout radiotherapy remain limited. In this retrospective study, survival analysis was performed based on a discovery cohort from TCGA and a validation cohort from three independent hospitals. Tumor mutational burden (TMB) and chromosomal aneuploidy (ANE) were derived from the whole exome sequencing (WES) data from treatment-naïve tumors. Integrated risk scores were derived from TMB and ANE by a multivariate Cox proportional hazards model. TCGA reveal that TMB and ANE are associated positively and negatively, respectively, with survival throughout radiotherapy. Additionally, the synergistically predictive significance of these two genomic alterations, in differing responders and non-responders to radiotherapy is identified. These biomarkers may have clinical potential to improve personalized treatment management by rationally identifying highly likely responders to therapeutic radiation in patients with NSCLC., Here, the authors use whole exome sequencing to determine the effect of tumor mutational burden (TMB) and chromosomal aneuploidy (ANE) on survival outcomes of non-small cell lung cancer patients undergoing radiotherapy. The authors find that a higher TMB and lower ANE were correlated with better survival outcomes and that these factors interact synergistically.

Eosinophil can be considered as a mechanistically relevant biomarker for predicting the effectiveness of radio-immunotherapy., The efficacy of cancer immunotherapy is dictated by CD8+ T cell infiltration and the nature of the tumor microenvironment (TME). By inflaming the TME to favor CD8+ T cell immunity, radiation is now widely considered as a neoadjuvant for immunomodulation. Here, we observed that local irradiation enhances the infiltration of intratumoral eosinophils, and depletion of eosinophil dampens CD8+ T cell infiltration and diminishes the anti-tumor effectiveness of radiation. Retrospectively, we identified a strong correlation between eosinophilia and survival benefit in radiation-treated cancer patients. Experimentally, we further show that radiation enhances the intratumoral infiltration of adoptive transferred T cells therapy, bolstering eosinophils by intravenous interleukin-5 administration promotes the efficacy of radiation-induced abscopal effect. Together, these results suggest that eosinophil mobilization can be considered as a mechanistically relevant biomarker for predicting the effectiveness of pre-immunotherapy radiation, as well as a new strategy to enhance T cell-mediated immunotherapy against cancers.

Reaction acceleration is a hot topic in recent years since it is very useful for rapid reaction screening and small-scale synthesis on a short timescale. It is known that the rates of chemical reactions are often accelerated in confined volumes (small droplets or thin films) where the unique chemical reactivities of molecules at the air-droplet/thin film interface, usually different from that in the bulk and gas phases, play a dominant role in acceleration. The Leidenfrost effect was employed to create small levitated droplets with no net charge. These droplets can accelerate many kinds of organic reactions. Our first accelerated synthesis of a series of organoimido-functionalized polyoxometalate (POM) clusters using Leidenfrost droplets with product analysis by electrospray ionization mass spectrometry (ESI-MS) demonstrated that this method can be successfully extended to the synthesis of inorganic/organic hybrids, a very promising area for developing POM-based functional materials. Comparable amounts of synthetic products [Mo

SummaryBackgroundA recently emerging respiratory disease named coronavirus disease 2019 (COVID-19) has quickly spread across the world. This disease is initiated by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and uncontrolled cytokine storm, but it remains unknown as to whether a robust antibody response is related to clinical deterioration and poor outcome in laboratory-confirmed COVID-19 patients.MethodsAnti-SARS-CoV-2 IgG and IgM antibodies were determined by chemiluminescence analysis (CLIA) in COVID-19 patients from a single center in Wuhan. Median IgG and IgM levels in acute and convalescent-phase sera (within 35 days) for all included patients were calculated and compared among severe and nonsevere patients. Immune response phenotyping based on late IgG levels and neutrophil-to-lymphocyte ratio (NLR) was characterized to stratify patients with different disease severities and outcome. Laboratory parameters in patients with different immune response phenotypes and disease severities were analyzed.FindingsA total of 222 patients were included in this study. IgG was first detected on day 4 of illness, and its peak levels occurred in the fourth week. Severe cases were more frequently found in patients with high IgG levels, compared to those who with low IgG levels (51.8% versus 32.3%; p=0.008). Severity rates for patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype was 72.3%, 48.5%, 33.3%, and 15.6%, respectively (phiIgGhi, NLRhiIgGlo had higher proinflammatory cytokines levels including IL-2, IL-6 and IL-10, and decreased CD4+ T cell count compared to those with NLRloIgGlo phenotype (phiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype was 58.8% (20/34), 68.8% (11/16), 80.0% (4/5), and 100% (12/12), respectively (p=0.0592). Dead cases only occurred in NLRhiIgGhi and NLRhiIgGlo phenotypes.InterpretationCOVID-19 severity is associated with increased IgG response, and an immune response phenotyping based on late IgG response and NLR could act as a simple complementary tool to discriminate between severe and nonsevere COVID-19 patients, and further predict their clinical outcome.Research in contextEvidence before this studyFollowing SARS-CoV-2 infection, a high viral load and overexuberant host immune response involving innate and acquired immunity, simultaneously contributes to the pathogenesis of COVID-19 and organ injury. Through searching PubMed and the China National knowledge infrastructure databases up to March 12, 2020, no published article focusing on anti-SARS-CoV-2 IgG-mediated immune response was identified.Added value of this studyWe evaluated antibody response within 35 days after symptom onset in laboratory-confirmed case with COVID-19 as one component of an overall exaggerated immune activation in severe SARS-CoV-2 infection, and developed an immune phenotyping based on late IgG response and NLR that could help determine disease severity and clinical outcome of COVID-19 patients. Severe cases were more frequently found in patients with high IgG levels, compared to those who with low IgG levels (51.8% versus 32.3%). Severity rates for patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype was 72.3%, 48.5%, 33.3%, and 15.6%, respectively. Furthermore, severe patients with NLRhiIgGhi, NLRhiIgGlo had higher proinflammatory cytokines levels including IL-2, IL-6 and IL-10, and decreased CD4+ T cell count compared to those with NLRloIgGlo phenotype. Recovery rate for severe patients with NLRhiIgGhi, NLRhiIgGlo, NLRloIgGhi, and NLRloIgGlo phenotype was 58.8% (20/34), 68.8% (11/16), 80.0% (4/5), and 100% (12/12), respectively.Implications of all the available evidenceCOVID-19 severity is associated with a high viral load and overexuberant IgG response. We developed an immune response phenotyping based on NLR and IgG that could act as a simple complementary tool to discriminate between severe and nonsevere COVID-19 patients and would be helpful in guiding clinical decision.

Triple-negative breast cancer (TNBC) accounts for 15-30% of all breast cancer cases and is clinically difficult to treat due to the lack of hormone or human epidermal growth factor receptor 2 receptors, which are usually targeted by the most successful therapeutic approaches. Immune checkpoint inhibitors (ICIs) have offered long-term survival benefits in several types of solid tumors, however with low response rates. Thus, there is an urgent need to develop feasible biomarkers for identifying patients with TNBC, who are responsive. The present study demonstrated that the immune microenvironment of TNBC has the highest expression of immunoregulatory molecules among all pathologic types. The tumor mutation burden (TMB) of TNBC was not strongly correlated with cytolytic activity and showed no significant associations with different degrees of immune cell infiltration and TMB. The machine learning method divided patients with TNBC into two groups characterized by 'hot' and 'cold' tumors, according to whether immune-associated genes were highly expressed, and different responses to immunotherapy were seen between these two groups. Furthermore, patients with a TP53MutPIK3CAWild genotype demonstrated favorable immunotherapy-responsive signatures and may have improved outcomes with ICIs. In conclusion, the present study revealed that TP53 and PIK3CA may be appropriate biomarkers to screen for patients who would benefit most from ICIs, which could guide precise immunotherapy for patients with TNBC.

Zebrafish embryos are highly sensitive to toxicant exposure and have been used to evaluate the potential eco-toxicity caused by organic pollutants in the aquatic environment. This study was to develop four quantitative structure–activity relationship (QSAR) models based on norm descriptors for acute toxicity of different exposure times toward zebrafish embryo of organic compounds with various structures. Norm descriptors were obtained by calculating the norm index of the atomic distribution matrix, which was composed of atomic spatial distribution and atomic properties. These norm index-based QSAR models presented satisfactory results with R2 of 0.8549, 0.9162, 0.8335 and 0.8119 for 48, 96, 120 and 132 h, respectively. Validation results including cross validation, external validation, Y-randomized test and applicability domain analysis indicated that the proposed models were stable, robust and reliable. Accordingly, these norm descriptors might be effective in predicting the acute toxicity of various organics to zebrafish embryos, which might be useful for evaluating the potential hazards of organic pollutants to aquatic environment.

The kinetic rate constant of volatile organic compounds (VOCs) degradation represents an important parameter, which is valuable for evaluating the degradation efficiency and ecological risk of pollutants. In this study, the multiple-linear-regression method using quantum chemical and norm descriptors is utilized to develop a room-temperature quantitative structure-property relationships (QSPR) model for kinetic rate constant estimation. The correlation coefficient (R2) and root-mean-square error (RMSE) are 0.8918 and 0.4086 for the training set, as well as 0.9096 and 0.3901 for the test set, respectively, which suggests the as-developed model has good stability and predictability. Applicability domain analysis demonstrates that the model is reliable and generalizable for assessing the -logk·OH of VOCs covering a wide variety of molecular structures. In addition, an external prediction is made to assess the degradation rate constants of nine hydrofluoroethers, which implies the predictability of the model. It is worth noting that the quantum mechanical parameters, i.e., natural population analysis and orbital energy for atoms are introduced to norm descriptors, which expands the number/type of norm descriptors and greatly improves the accuracy of the model. Such combinational quantum chemical and norm descriptors are expected to be used for building accurate and robust models for other chemical properties prediction.

Flash point (FP) is an important reference property for characterizing the fire hazards of any combustible material in the field of petro-chemical processes and functional materials designing, whereas, obtaining FP data for flammable liquids is difficult owing to several limitations. Herein, the distributive structure-properties relationship (DSPR) method for simultaneously investigating the relationship between the structure and the FP for multiple-component mixtures (mono/binary/ternary component) was proposed and was composed of a DSPR model and hybrid norm indexes. Serial of validation metrics prove that this model exhibited good predictive and generalization abilities in prediction of FP for multiple-component mixtures. Thus, this new method and hybrid indexes proposed in this work is effective for the characteristic of the relationship between structure and FP and might have larger applications in chemical process safety.

Impaired immunity in patients with late-stage cancer is not limited to antitumor responses, as demonstrated by poor vaccination protection and high susceptibility to infection1-3. This has been largely attributed to chemotherapy-induced impairment of innate immunity, such as neutropenia2, whereas systemic effects of tumors on hematopoiesis and adoptive immunity remain incompletely understood. Here we observed anemia associated with severe deficiency of CD8+ T cell responses against pathogens in treatment-naive mice bearing large tumors. Specifically, we identify CD45+ erythroid progenitor cells (CD71+TER119+; EPCs) as robust immunosuppressors. CD45+ EPCs, induced by tumor growth-associated extramedullary hematopoiesis, accumulate in the spleen to become a major population, outnumbering regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs). The CD45+ EPC transcriptome closely resembles that of MDSCs, and, like MDSCs, reactive oxygen species production is a major mechanism underlying CD45+ EPC-mediated immunosuppression. Similarly, an immunosuppressive CD45+ EPC population was detected in patients with cancer who have anemia. These findings identify a major population of immunosuppressive cells that likely contributes to the impaired T cell responses commonly observed in patients with advanced cancer.

Background The benefits of immune checkpoint inhibitors for first-line treatment in patients with lung adenocarcinoma harboring EGFR mutations are unclear. The effects of ICIs depend on the tumor microenvironment (TME). Differences in TME properties between mutant and wild-type EGFR have not been fully characterized. Patients and Methods We collected 105 surgically resected (50 EGFR mutated and 55 EGFR wild-type), treatment-naive lung adenocarcinoma tissues with clinical data to investigate the landscape and compartmentalization of tumor-infiltrating immune cells with respect to EGFR status by immunohistochemistry. The normalized FPKM values of data for 531 patients were obtained from The Cancer Genome Atlas (TCGA) Data Portal ( https://portal.gdc.cancer.gov/ ). Results CD68-positive cells within the tumor niche exhibited more intensive infiltration in wild-type EGFR than in mutations, and was related to lymph node invasion. In the RNA-Seq analysis, MMP9 and VEGFA showed higher levels in wild-type EGFR than in mutant cases. The EGFR mutation independently predicted a favorable disease-free survival. Conclusion The CD68-positive cells play a crucial role in discriminating the TME between different EGFR statuses.

The viscosity of ionic liquids (ILs) plays an important role in the chemical industry, material science and environmental science. This work presents a temperature- and pressure-dependent (η-T-P) model based on the norm indices for describing the viscosity of ILs. While the parameters for the temperature and pressure dependence of the viscosity have been generally set as constants in previous work, they are adjusted based on the molecular structures in the η-T-P model. Because ILs consist of only cations and anions, the norm indices are derived from cations and anions, respectively. However, the close connection between the interaction of the cations and anions and IL viscosity cannot be neglected; therefore, another set of norms is further deduced to represent the cation–anion interaction. The η-T-P model is developed using 349 ILs (3228 data points) in the temperature range of 253.15–573.00 K and the pressure range of 0.06–300.00 MPa. Consequently, a η-T-P model is derived with convincing results, as evaluated by the following statistical parameters: the squared correlation coefficient (R2), Fisher significance (F) and the overall average absolute relative deviation (AARD), which are 0.964, 1809 and 4.62%, respectively.

The quantitative structure–activity relationship (QSAR) model is an effective alternative to traditional experimental toxicity testing, which is undoubtedly important for modern environmental risk assessment and property prediction. Based on this background, the toxicological effects of ionic liquids (ILs) against Candida albicans (C. albicans) were studied via the QSAR method. A large diverse group of 141 and 85 ILs that have a minimal inhibitory concentration (MIC) and a minimum fungicidal concentration (MBC) against C. albicans were used to obtain multiple linear regression models. These two models were developed based on matrix norm indexes and proposed based on the atomic character and position. Matrix norm indexes proposed in our research group were used to calculate the toxicity of these ILs towards C. albicans for the first time. These two models precisely estimated the toxicity of these ILs towards C. albicans with a square of correlation coefficient (R2) of = 0.930 and a standard error of estimate (SE) of = 0.254 for pMIC, and for pMBC, R2 = 0.873 and SE = 0.243.

Yi Feng,1,2 Ying Dai,1,2 Zhihua Gong,1,2 Jia-Nan Cheng,1,2 Longhui Zhang,1,2 Chengdu Sun,1,2 Xianghua Zeng,1,2 Qingzhu Jia,1,2 Bo Zhu1,2 1Institute of Cancer, Xinqiao Hospital, Third Military Medical University, Chongqing, People’s Republic of China; 2Chongqing Key Laboratory of Tumor Immunotherapy, Chongqing, People’s Republic of China Background: A suppressive immune microenvironment and pathological angiogenesis are hallmarks of gastric cancer. Theoretically, immune checkpoint inhibitors (ICIs) stimulate pre-primed neoantigen-specific T cells, and antiangiogenic agents then facilitate their infiltration into the tumor niche by promoting vascular normalization. Currently, the interconnections of these two phenotypes and their relevance to the tumor microenvironment (TME) have not been fully characterized in gastric cancer.Materials and methods: Transcriptome profiling data retrieved from The Cancer Genome Atlas (TCGA) database were used to deconvolute the feature of TME for gastric cancer (N = 375). Machine learning, correlation, and prognosis analysis were applied to elucidate the correlations between angiogenesis, cytotoxic T lymphocyte infiltration, and patient survival.Results: Substantial heterogeneous infiltration of immune cell populations among cases was observed. Furthermore, among targetable pathways, angiogenesis was identified as the dominant factor in discriminating different infiltration statuses. Most importantly, the angiogenesis pathway was negatively correlated with the amount of activated CD8+ T cells only for patients with a higher infiltration, and the concomitance of low angiogenesis signaling and highly activated CD8+ T-cell infiltration was associated with a significant survival benefit.Conclusion: Our findings demonstrated a negative correlation between angiogenesis signaling and cytotoxic function in gastric cancer patients with a highly infiltrated immune niche. These data provided a rationale for potential combination strategy and further clinical investigations of ICIs plus antiangiogenesis agents for patients with gastric cancer with an inflamed TME. Keywords: gastric cancer, immune microenvironment, TCGA, angiogenesis, therapeutic implications

Immunotherapy targeting the programmed cell death-1/programmed death ligand 1(PD-L1) pathway has shown promising antitumor activity in brain metastases (BMs) of non-small cell lung cancer (NSCLC) patients with an acceptable safety profile; however, the response rates often differ between primary lesions and intracranial lesions. Studies are necessary to identify detailed characterizations of the response biomarkers. In this study, we aimed to compare the differences of PD-L1 expression and CD8+ tumor-infiltrating lymphocyte (TIL) density, two major response biomarkers of PD-1/PD-L1 blockade, between paired primary and brain metastatic lesions in advanced NSCLC. We observed that among primary lesions or BMs, only a small number of patients harbored common PD-L1 expression on both tumor cells and tumor-infiltrating immune cells. Additionally, we found that the numbers of CD8+ TILs were significantly fewer in BMs than in primary lung cancers. Low stromal CD8+ TIL numbers in BMs were associated with significantly shorter overall survival compared to high stromal CD8+ TIL counts. Notably, we demonstrated a discrepancy in PD-L1 expression and CD8+ TIL density between primary lung cancers and their corresponding BMs. Such heterogeneities are significantly associated with the time at which BMs occurred. Our study emphasizes the spatial and temporal heterogeneity of biomarkers for anti-PD-1/PD-L1 therapy, which should be concerned in clinical practice.

A new quantitative structure-property relationship (QSPR) model was developed to predict critical micelles concentration (CMC) of sugar-based surfactants using the norm indexes descriptors our group previously proposed. Statistics results showed that this model could provide satisfactory prediction results with the squared correlation coefficient for the whole dataset, the training set and the test set of 0.9545, 0.9547 and 0.9699 respectively. Several validation procedures including cross validation, Y-randomized test, mean absolute error test and applicability domain analysis as well as the comparison results with other works further demonstrated the stability and robustness of this model. Thus, the QSPR model using the norm indexes descriptors was effective in the prediction of CMC for sugar-based surfactants.

Dynamic interaction with the immune system profoundly regulates tumor cell dormancy. However, it is unclear how immunological cues trigger cancer cell-intrinsic signaling pathways for entering into dormancy. Here, we show that IFN-β treatment induced tumor-repopulating cells (TRC) to enter dormancy through an indolamine 2,3-dioxygenase/kynurenine/aryl hydrocarbon receptor/p27-dependent (IDO/Kyn/AhR/p27-dependent) pathway. Strategies to block this metabolic circuitry did not relieve dormancy, but led to apoptosis of dormant TRCs in murine and human melanoma models. Specifically, blocking AhR redirected IFN-β signaling to STAT3 phosphorylation through both tyrosine and serine sites, which subsequently facilitated STAT3 nuclear translocation and subsequent binding to the p53 promoter in the nucleus. Upregulation of p53 in turn disrupted the pentose phosphate pathway, leading to excessive ROS production and dormant TRC death. Additionally, in melanoma patients, high expression of IFN-β correlated with tumor cell dormancy. Identification of this mechanism for controlling TRC dormancy by IFN-β provides deeper insights into cancer-immune interaction and potential new cancer immunotherapeutic modalities.