A pangenome reference of 36 Chinese populations.

Human genomics is witnessing an ongoing paradigm shift from a single reference sequence to a pangenome form, but populations of Asian ancestry are underrepresented. Here we present data from the first phase of the Chinese Pangenome Consortium, including a collection of 116 high-quality and haplotype-phased de novo assemblies based on 58 core samples representing 36 minority Chinese ethnic groups. With an average 30.65× high-fidelity long-read sequence coverage, an average contiguity N50 of more than 35.63 megabases and an average total size of 3.01 gigabases, the CPC core assemblies add 189 million base pairs of euchromatic polymorphic sequences and 1,367 protein-coding gene duplications to GRCh38. We identified 15.9 million small variants and 78,072 structural variants, of which 5.9 million small variants and 34,223 structural variants were not reported in a recently released pangenome reference1. The Chinese Pangenome Consortium data demonstrate a remarkable increase in the discovery of novel and missing sequences when individuals are included from underrepresented minority ethnic groups. The missing reference sequences were enriched with archaic-derived alleles and genes that confer essential functions related to keratinization, response to ultraviolet radiation, DNA repair, immunological responses and lifespan, implying great potential for shedding new light on human evolution and recovering missing heritability in complex disease mapping.

ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization.

Drug discovery and development constitute a laborious and costly undertaking. The success of a drug hinges not only good efficacy but also acceptable absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties. Overall, up to 50% of drug development failures have been contributed from undesirable ADMET profiles. As a multiple parameter objective, the optimization of the ADMET properties is extremely challenging owing to the vast chemical space and limited human expert knowledge. In this study, a freely available platform called Chemical Molecular Optimization, Representation and Translation (ChemMORT) is developed for the optimization of multiple ADMET endpoints without the loss of potency (https://cadd.nscc-tj.cn/deploy/chemmort/). ChemMORT contains three modules: Simplified Molecular Input Line Entry System (SMILES) Encoder, Descriptor Decoder and Molecular Optimizer. The SMILES Encoder can generate the molecular representation with a 512-dimensional vector, and the Descriptor Decoder is able to translate the above representation to the corresponding molecular structure with high accuracy. Based on reversible molecular representation and particle swarm optimization strategy, the Molecular Optimizer can be used to effectively optimize undesirable ADMET properties without the loss of bioactivity, which essentially accomplishes the design of inverse QSAR. The constrained multi-objective optimization of the poly (ADP-ribose) polymerase-1 inhibitor is provided as the case to explore the utility of ChemMORT.

ChemFH: an integrated tool for screening frequent false positives in chemical biology and drug discovery.

High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. By leveraging a dataset containing 823 391 compounds, we constructed high-quality prediction models using multi-task directed message-passing network (DMPNN) architectures combining uncertainty estimation, yielding an average AUC value of 0.91. Furthermore, ChemFH incorporated 1441 representative alert substructures derived from the collected data and ten commonly used frequent hitter screening rules. ChemFH was validated with an external set of 75 compounds. Subsequently, the virtual screening capability of ChemFH was successfully confirmed through its application to five virtual screening libraries. Furthermore, ChemFH underwent additional validation on two natural products and FDA-approved drugs, yielding reliable and accurate results. ChemFH is a comprehensive, reliable, and computationally efficient screening pipeline that facilitates the identification of true positive results in assays, contributing to enhanced efficiency and success rates in drug discovery. ChemFH is freely available via https://chemfh.scbdd.com/.

Q negatively regulates wheat salt tolerance through directly repressing the expression of TaSOS1 and reactive oxygen species scavenging genes.

The Q transcription factor plays important roles in improving multiple wheat domestication traits such as spike architecture, threshability and rachis fragility. However, whether and how it regulates abiotic stress adaptation remain unclear. We found that the transcriptional expression of Q can be induced by NaCl and abscisic acid treatments. Using the q mutants generated by CRISPR/Cas9 and Q overexpression transgenic lines, we showed that the domesticated Q gene causes a penalty in wheat salt tolerance. Then, we demonstrated that Q directly represses the transcription of TaSOS1-3B and reactive oxygen species (ROS) scavenging genes to regulate Na+ and ROS homeostasis in wheat. Furthermore, we showed that wheat salt tolerance protein TaWD40 interacts with Q to competitively interfere with the interaction between Q and the transcriptional co-repressor TaTPL. Taken together, our findings reveal that Q directly represses the expression of TaSOS1 and some ROS scavenging genes, thus causing a harmful effect on wheat salt tolerance.

Multi-task bioassay pre-training for protein-ligand binding affinity prediction.

Protein-ligand binding affinity (PLBA) prediction is the fundamental task in drug discovery. Recently, various deep learning-based models predict binding affinity by incorporating the three-dimensional (3D) structure of protein-ligand complexes as input and achieving astounding progress. However, due to the scarcity of high-quality training data, the generalization ability of current models is still limited. Although there is a vast amount of affinity data available in large-scale databases such as ChEMBL, issues such as inconsistent affinity measurement labels (i.e. IC50, Ki, Kd), different experimental conditions, and the lack of available 3D binding structures complicate the development of high-precision affinity prediction models using these data. To address these issues, we (i) propose Multi-task Bioassay Pre-training (MBP), a pre-training framework for structure-based PLBA prediction; (ii) construct a pre-training dataset called ChEMBL-Dock with more than 300k experimentally measured affinity labels and about 2.8M docked 3D structures. By introducing multi-task pre-training to treat the prediction of different affinity labels as different tasks and classifying relative rankings between samples from the same bioassay, MBP learns robust and transferrable structural knowledge from our new ChEMBL-Dock dataset with varied and noisy labels. Experiments substantiate the capability of MBP on the structure-based PLBA prediction task. To the best of our knowledge, MBP is the first affinity pre-training model and shows great potential for future development. MBP web-server is now available for free at: https://huggingface.co/spaces/jiaxianustc/mbp.

TRAIL-driven targeting and reversing cervical cancer radioresistance by seleno-nanotherapeutics through regulating cell metabolism.

Recently, radioresistance has become a major obstacle in the radiotherapy of cervical cancer. To demonstrate enhanced radiosensitization against radioresistant cervical cancer, radioresistant cervical cancer cell line was developed and the mechanism of radioresistance was explored. Due to the overexpression of (death receptor 5, DR5) in cervical cancer, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-overexpressed cervical cancer cell membrane-camouflaged Cu2-xSe nanomedicine (CCMT) was designed. Since the CCMT was encapsulated with TRAIL-modified cell membrane, it represented high target to cervical cancer cell and immune evasion. Furthermore, Cu2-xSe had the ability to scavenge glutathione (GSH) and produce ·OH with excess H2O2 in the tumor microenvironment. The presence of CCMT combined with radiation therapy could effectively increase the 1O2 produced by X-rays. In vitro and in vivo studies elaborated that CCMT exhibited excellent radiosensitization properties to reverse radiotolerance by scavenging GSH and promoting DNA damage, apoptosis, mitochondrial membrane potential damage and metabolic disruption. Collectively, this study suggested that the development of TRAIL-overexpressed cell membrane-camouflaged Cu2-xSe nanomedicine could advance future cervical cancer treatment and minimize the disadvantages associated with radiation treatment.

Revealing the Optical Transition Properties of Interlayer Excitons in Defective WS2/WSe2 Heterobilayers.

Manipulation of physical properties in multidimensional tunable moiré superlattice systems is a key focus in nanophotonics, especially for interlayer excitons (IXs) in two-dimensional materials. However, the impact of defects on IXs remains unclear. Here, we thoroughly study the optical properties of WS2/WSe2 heterobilayers with varying defect densities. Low-temperature photoluminescence (PL) characterizations reveal that the low-energy IXs are more susceptible to defects compared to the high-energy IXs. The low-energy IXs also show much faster PL quenching rate with temperature, faster peak width broadening rate with laser power, shorter lifetime, and lower circular polarization compared to the low-energy IXs in the region with fewer defects. These effects are attributed to the combined effects of increased electron scattering, exciton-phonon interactions, and nonradiative channels introduced by the defects. Our findings aid in optimizing moiré superlattice structures.

The m6A reader IGF2BP2 promotes the progression of esophageal squamous cell carcinoma cells by increasing the stability of OCT4 mRNA.

Esophageal squamous cell carcinoma (ESCC) is a common malignancy with high morbidity and mortality. Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) serves as a reader of RNA m6A (N6 methyladenosine) modification to regulate gene expression at the post-transcriptional level. Emerging evidence suggests that IGF2BP2 plays critical roles in tumorigenesis and malignant development. However, the biological function and molecular mechanism of IGF2BP2 in ESCC are not well understood. Here, we found that IGF2BP2 expression was upregulated in esophageal cancer tissues and ESCC cells, and IGF2BP2 overexpression enhanced proliferation, migration, invasion, and stem cell-like properties of ESCC cells. Conversely, the knockdown of IGF2BP2 expression inhibited malignant phenotype of ESCC cells. Mechanistically, IGF2BP2 upregulated octomer-binding transcription factor 4 (OCT4) mRNA expression, and RNA immunoprecipitation (RIP) assay proved that IGF2BP2 could interact with OCT4 mRNA. Moreover, OCT4 was modified at m6A confirmed by methylated m6A RNA immunoprecipitation (Me-RIP)-qPCR assay, and IGF2BP2 knockdown reduced OCT4 mRNA stability. These results suggested that IGF2BP2 served as a reader for m6A-modified OCT4, thus increased OCT4 mRNA expression by regulating its stability. Furthermore, the knockdown of OCT4 could reverse the effects of IGF2BP2 on ESCC cells. In conclusion, these data indicate that IGF2BP2, as a reader for m6A, plays an oncogenic role by regulating OCT4 expression in ESCC, which provides new insights into targeting IGF2BP2/OCT4 axis for the therapy of ESCC.

Identification of COQ2 as a regulator of proliferation and lipid peroxidation through genome-scale CRISPR-Cas9 screening in myeloma cells.

Multiple myeloma (MM) is the second most common malignant haematological disease with a poor prognosis. The limit therapeutic progress has been made in MM patients with cancer relapse, necessitating deeper research into the molecular mechanisms underlying its occurrence and development. A genome-wide CRISPR-Cas9 loss-of-function screening was utilized to identify potential therapeutic targets in our research. We revealed that COQ2 plays a crucial role in regulating MM cell proliferation and lipid peroxidation (LPO). Knockout of COQ2 inhibited cell proliferation, induced cell cycle arrest and reduced tumour growth in vivo. Mechanistically, COQ2 promoted the activation of the MEK/ERK cascade, which in turn stabilized and activated MYC protein. Moreover, we found that COQ2-deficient MM cells increased sensitivity to the LPO activator, RSL3. Using an inhibitor targeting COQ2 by 4-CBA enhanced the sensitivity to RSL3 in primary CD138+ myeloma cells and in a xenograft mouse model. Nevertheless, co-treatment of 4-CBA and RSL3 induced cell death in bortezomib-resistant MM cells. Together, our findings suggest that COQ2 promotes cell proliferation and tumour growth through the activation of the MEK/ERK/MYC axis and targeting COQ2 could enhance the sensitivity to ferroptosis in MM cells, which may be a promising therapeutic strategy for the treatment of MM patients.

RhoGDIß inhibition via miR-200c/AUF1/SOX2/miR-137 axis contributed to lncRNA MEG3 downregulation-mediated malignant transformation of human bronchial epithelial cells.

Nickel pollution is a recognized factor contributing to lung cancer. Understanding the molecular mechanisms of its carcinogenic effects is crucial for lung cancer prevention and treatment. Our previous research identified the downregulation of a long noncoding RNA, maternally expressed gene 3 (MEG3), as a key factor in transforming human bronchial epithelial cells (HBECs) into malignant cells following nickel exposure. In our study, we found that deletion of MEG3 also reduced the expression of RhoGDIß. Notably, artificially increasing RhoGDIß levels counteracted the malignant transformation caused by MEG3 deletion in HBECs. This indicates that the reduction in RhoGDIß contributes to the transformation of HBECs due to MEG3 deletion. Further exploration revealed that MEG3 downregulation led to enhanced c-Jun activity, which in turn promoted miR-200c transcription. High levels of miR-200c subsequently increased the translation of AUF1 protein, stabilizing SOX2 messenger RNA (mRNA). This stabilization affected the regulation of miR-137, SP-1 protein translation, and the suppression of RhoGDIß mRNA transcription and protein expression, leading to cell transformation. Our study underscores the co-regulation of RhoGDIß expression by long noncoding RNA MEG3, multiple microRNAs (miR-200c and miR-137), and RNA-regulated transcription factors (c-Jun, SOX2, and SP1). This intricate network of molecular events sheds light on the nature of lung tumorigenesis. These novel findings pave the way for developing targeted strategies for the prevention and treatment of human lung cancer based on the MEG3/RhoGDIß pathway.

SPLDExtraTrees: robust machine learning approach for predicting kinase inhibitor resistance.

Drug resistance is a major threat to the global health and a significant concern throughout the clinical treatment of diseases and drug development. The mutation in proteins that is related to drug binding is a common cause for adaptive drug resistance. Therefore, quantitative estimations of how mutations would affect the interaction between a drug and the target protein would be of vital significance for the drug development and the clinical practice. Computational methods that rely on molecular dynamics simulations, Rosetta protocols, as well as machine learning methods have been proven to be capable of predicting ligand affinity changes upon protein mutation. However, the severely limited sample size and heavy noise induced overfitting and generalization issues have impeded wide adoption of machine learning for studying drug resistance. In this paper, we propose a robust machine learning method, termed SPLDExtraTrees, which can accurately predict ligand binding affinity changes upon protein mutation and identify resistance-causing mutations. Especially, the proposed method ranks training data following a specific scheme that starts with easy-to-learn samples and gradually incorporates harder and diverse samples into the training, and then iterates between sample weight recalculations and model updates. In addition, we calculate additional physics-based structural features to provide the machine learning model with the valuable domain knowledge on proteins for these data-limited predictive tasks. The experiments substantiate the capability of the proposed method for predicting kinase inhibitor resistance under three scenarios and achieve predictive accuracy comparable with that of molecular dynamics and Rosetta methods with much less computational costs.

Wnt/ß-catenin signalling activates IMPDH2-mediated purine metabolism to facilitate oxaliplatin resistance by inhibiting caspase-dependent apoptosis in colorectal cancer.

BACKGROUND: Oxaliplatin resistance usually leads to therapeutic failure and poor prognosis in colorectal cancer (CRC), while the underlying mechanisms are not yet fully understood. Metabolic reprogramming is strongly linked to drug resistance, however, the role and mechanism of metabolic reprogramming in oxaliplatin resistance remain unclear. Here, we aim to explore the functions and mechanisms of purine metabolism on the oxaliplatin-induced apoptosis of CRC. METHODS: An oxaliplatin-resistant CRC cell line was generated, and untargeted metabolomics analysis was conducted. The inosine 5'-monophosphate dehydrogenase type II (IMPDH2) expression in CRC cell lines was determined by quantitative real-time polymerase chain reaction (qPCR) and western blotting analysis. The effects of IMPDH2 overexpression, knockdown and pharmacological inhibition on oxaliplatin resistance in CRC were assessed by flow cytometry analysis of cell apoptosis in vivo and in vitro. RESULTS: Metabolic analysis revealed that the levels of purine metabolites, especially guanosine monophosphate (GMP), were markedly elevated in oxaliplatin-resistant CRC cells. The accumulation of purine metabolites mainly arose from the upregulation of IMPDH2 expression. Gene set enrichment analysis (GSEA) indicated high IMPDH2 expression in CRC correlates with PURINE_METABOLISM and MULTIPLE-DRUG-RESISTANCE pathways. CRC cells with higher IMPDH2 expression were more resistant to oxaliplatin-induced apoptosis. Overexpression of IMPDH2 in CRC cells resulted in reduced cell death upon treatment with oxaliplatin, whereas knockdown of IMPDH2 led to increased sensitivity to oxaliplatin through influencing the activation of the Caspase 7/8/9 and PARP1 proteins on cell apoptosis. Targeted inhibition of IMPDH2 by mycophenolic acid (MPA) or mycophenolate mofetil (MMF) enhanced cell apoptosis in vitro and decreased in vivo tumour burden when combined with oxaliplatin treatment. Mechanistically, the Wnt/ß-catenin signalling was hyperactivated in oxaliplatin-resistant CRC cells, and a reciprocal positive regulatory mechanism existed between Wnt/ß-catenin and IMPDH2. Blocking the Wnt/ß-catenin pathway could resensitize resistant cells to oxaliplatin, which could be restored by the addition of GMP. CONCLUSIONS: IMPDH2 is a predictive biomarker and therapeutic target for oxaliplatin resistance in CRC.

Sequential activation of strigolactone and salicylate biosynthesis promotes leaf senescence.

Leaf senescence is a complex process strictly regulated by various external and endogenous factors. However, the key signaling pathway mediating leaf senescence remains unknown. Here, we show that Arabidopsis SPX1/2 negatively regulate leaf senescence genetically downstream of the strigolactone (SL) pathway. We demonstrate that the SL receptor AtD14 and MAX2 mediate the age-dependent degradation of SPX1/2. Intriguingly, we uncover an age-dependent accumulation of SLs in leaves via transcriptional activation of SL biosynthetic genes by the transcription factors (TFs) SPL9/15. Furthermore, we reveal that SPX1/2 interact with the WRKY75 subclade TFs to inhibit their DNA-binding ability and thus repress transcriptional activation of salicylic acid (SA) biosynthetic gene SA Induction-Deficient 2, gating the age-dependent SA accumulation in leaves at the leaf senescence onset stage. Collectively, our new findings reveal a signaling pathway mediating sequential activation of SL and salicylate biosynthesis for the onset of leaf senescence in Arabidopsis.

Plant-specific BLISTER interacts with kinase BIN2 and BRASSINAZOLE RESISTANT1 during skotomorphogenesis.

Brassinosteroids play an essential role in promoting skotomorphogenesis, yet the underlying mechanisms remain unknown. Here we report that a plant-specific BLISTER (BLI) protein functions as a positive regulator of both BR signaling and skotomorphogenesis in Arabidopsis (Arabidopsis thaliana). We found that the glycogen synthase kinase 3 (GSK3)-like kinase BRASSINOSTEROID INSENSITIVE2 interacts with and phosphorylates BLI at 4 phosphorylation sites (Ser70, Ser146, Thr256, and Ser267) for degradation; in turn, BR inhibits degradation of BLI. Specifically, BLI cooperates with the BRASSINAZOLE RESISTANT1 (BZR1) transcription factor to facilitate the transcriptional activation of BR-responsive genes. Genetic analyses indicated that BLI is essentially required for BZR1-mediated hypocotyl elongation in the dark. Intriguingly, we reveal that BLI and BZR1 orchestrate the transcriptional expression of gibberellin (GA) biosynthetic genes to promote the production of bioactive GAs. Our results demonstrate that BLI acts as an essential regulator of Arabidopsis skotomorphogenesis by promoting BR signaling and GA biosynthesis.

Intestinal metabolite xylulose inhibits colorectal cancer by inducing apoptosis through the MAPK signalling pathway.

BACKGROUND: The intestinal metabolites are involved in the initiation, progression and metastasis of colorectal cancer (CRC). They are a potential source of agents for cancer therapy. Our previous study identified altered faecal metabolites between CRC patients and healthy volunteers. However, no specific metabolite was clearly illustrated for CRC therapy. RESULTS: We found that the level of xylulose was lower in the stools of CRC patients than in those of healthy volunteers. Xylulose inhibited cell growth without affecting the cell cycle by inducing apoptosis in CRC cells, which was evidenced by increased expression of the proapoptotic proteins C-PARP and C-Caspase3 and decreased expression of the antiapoptotic protein BCL-2 in CRC cells. Mechanistically, xylulose reduced the activity of the MAPK signalling pathway, represented by reduced phosphorylation of JNK, ERK, and P38. Furthermore, an ALI model was used to show the tumour killing ability of xylulose on human CRC spheres, as well as human colorectal adenoma (AD) spheres. CONCLUSION: Xylulose inhibits CRC growth by inducing apoptosis through attenuation of the MAPK signalling pathway. These results suggest that xylulose may serve as an effective agent for CRC therapy.

Deconvolution at the single-cell level reveals ovarian cell-type-specific transcriptomic changes in PCOS.

BACKGROUND: Polycystic ovary syndrome (PCOS) is one of the most common reproductive endocrine disorders in females of childbearing age. Various types of ovarian cells work together to maintain normal reproductive function, whose discordance often takes part in the development and progression of PCOS. Understanding the cellular heterogeneity and compositions of ovarian cells would provide insight into PCOS pathogenesis, but are, however, not well understood. Transcriptomic characterization of cells isolated from PCOS cases have been assessed using bulk RNA-seq but cells isolated contain a mixture of many ovarian cell types. METHODS: Here we utilized the reference scRNA-seq data from human adult ovaries to deconvolute and estimate cell proportions and dysfunction of ovarian cells in PCOS, by integrating various granulosa cells(GCs) transcriptomic data. RESULTS: We successfully defined 22 distinct cell clusters of human ovarian cells. Then after transcriptome integration, we obtained a gene expression matrix with 13,904 genes within 30 samples (15 control vs. 15 PCOS). Subsequent deconvolution analysis revealed decreased proportion of small antral GCs and increased proportion of KRT8high mural GCs, HTRA1high cumulus cells in PCOS, especially increased differentiation from small antral GCs to KRT8high mural GCs. For theca cells, the abundance of internal theca cells (TCs) and external TCs was both increased. Less TCF21high stroma cells (SCs) and more STARhigh SCs were observed. The proportions of NK cells and monocytes were decreased, and T cells occupied more in PCOS and communicated stronger with inTCs and exTCs. In the end, we predicted the candidate drugs which could be used to correct the proportion of ovarian cells in patients with PCOS. CONCLUSIONS: Taken together, this study provides insights into the molecular alterations and cellular compositions in PCOS ovarian tissue. The findings might contribute to our understanding of PCOS pathophysiology and offer resource for PCOS basic research.

Isorhapontigenin inhibition of basal muscle-invasive bladder cancer attributed to its downregulation of SNHG1 and DNMT3b.

BACKGROUND: Bladder cancer (BC) is among the most prevalent malignant urothelial tumors globally, yet the prognosis for patients with muscle-invasive bladder cancer (MIBC) remains dismal, with a very poor 5-year survival rate. Consequently, identifying more effective and less toxic chemotherapeutic alternatives is critical for enhancing clinical outcomes for BC patients. Isorhapontigenin (ISO), a novel stilbene isolated from a Gnetum found in certain provinces of China, has shown potential as an anticancer agent due to its diverse anticancer activities. Despite its promising profile, the specific anticancer effects of ISO on BC and the underlying mechanisms are still largely unexplored. METHODS: The anchorage-independent growth, migration and invasion of BC cells were assessed by soft agar and transwell invasion assays, respectively. The RNA levels of SOX2, miR-129 and SNHG1 were quantified by qRT-PCR, while the protein expression levels were validated through Western blotting. Furthermore, methylation-specific PCR was employed to assess the methylation status of the miR-129 promoter. Functional assays utilized siRNA knockdown, plasmid-mediated overexpression, and chemical inhibition approaches. RESULTS: Our study demonstrated that ISO treatment significantly reduced SNHG1 expression in a dose- and time-dependent manner in BC cells, leading to the inhibition of anchorage-independent growth and invasion in human basal MIBC cells. This effect was accompanied by the downregulation of MMP-2 and MMP-9 and the upregulation of the tumor suppressor PTEN. Further mechanistic investigations revealed that SOX2, a key upstream regulator of SNHG1, played a crucial role in mediating the ISO-induced transcriptional suppression of SNHG1. Additionally, we found that ISO treatment led to a decrease in DNMT3b protein levels, which in turn mediated the hypomethylation of the miR-129 promoter and the subsequent suppression of SOX2 mRNA 3'-UTR activity, highlighting a novel pathway through which ISO exerts its anticancer effects. CONCLUSIONS: Collectively, our study highlights the critical role of SNHG1 downregulation as well as its upstream DNMT3b/miR-129/SOX2 axis in mediating ISO anticancer activity. These findings not only elucidate the mechanism of action of ISO but also suggest novel targets for BC therapy.

Prognostic Impact of Neoadjuvant Chemotherapy in Localized or Locoregionally Advanced Gallbladder Cancer: A Population-Based and Propensity Score Matched SEER Analysis.

BACKGROUND: The effect of neoadjuvant chemotherapy (NACT) in gallbladder cancer (GBC) patients remains controversial. The aim of this study was to assess the impact of NACT on overall survival (OS) and cancer specific survival (CSS) in patients with localized or locoregionally advanced GBC, and to explore possible protective predictors for prognosis. METHODS: Data for patients with localized or locoregionally advanced GBC (i.e., categories cTx-cT4, cN0-2, and cM0) from 2004 to 2020 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients in the NACT and non-NACT groups were propensity score matched (PSM) 1:3, and the Kaplan-Meier method and log-rank test were performed to analyze the impact of NACT on OS and CSS. Univariable and multivariable Cox regression models were applied to identify the possible prognostic factors. Subgroup analysis was conducted to identify patients who would benefit from NACT. RESULTS: Of the 2676 cases included, 78 NACT and 234 non-NACT patients remained after PSM. In localized or locoregionally advanced GBC patients, the median OS of the NACT and non-NACT was 31 and 16 months (log-rank P < 0.01), and the median CSS of NACT and non-NACT was 32 and 17 months (log-rank P < 0.01), respectively. Longer median OS (31 vs 17 months, log-rank P < 0.01) and CSS (32 vs 20 months, log-rank P < 0.01) was associated with NACT compared with surgery alone. Multivariable Cox regression analysis showed that NACT, stage, and surgery type were prognostic factors for OS and CSS in GBC patients. Subgroup analysis revealed that the survival hazard ratios (HRs) of NACT vs non-NACT for localized or locoregionally advanced GBC patients were significant in most subgroups. CONCLUSIONS: NACT may provide therapeutic benefits for localized or locoregionally advanced GBC patients, especially for those with advanced stage, node-positive, poorly differentiated or undifferentiated disease. NACT combined with radical surgery was associated with a survival advantage. Therefore, NACT combined with surgery may provide a better treatment option for resectable GBC patients.

Discovery of sesquiterpenoids from an actinomycete Crossiella cryophila through genome mining and heterologous expression.

Genome mining of the Actinomycete Crossiella cryophila facilitated the discovery of a minimal terpenoid biosynthetic gene cluster of cry consisting of a class I terpene cyclase CryA and a CYP450 monooxygenase CryB. Heterologous expression of cry allowed the isolation and characterization of two new sesquiterpenoids, ent-viridiflorol (1) and cryophilain (2). Notably, cryophilain (2) possesses a 5/7/3-fused tricyclic skeleton bearing a distinctive bridgehead hydroxy group. The combined in vivo and in vitro experiments revealed that CryA, the first ent-viridiflorol terpene cyclase, catalyzes farnesyl diphosphate to form the 5/7/3 sesquiterpene core scaffold and P450 CryB serves as a tailoring enzyme responsible for installing a hydroxy group at the bridgehead carbon.

Tumor microenvironment reprogramming combined with immunogenic enhancement by nanoemulsions potentiates immunotherapy.

The combination of immune checkpoint inhibitors and immunogenic cell death (ICD) inducers has become a promising strategy for the treatment of various cancers. However, its efficacy remains unmet because of the dense stroma and defective vasculatures in the tumor microenvironment (TME) that restricts the intratumoral infiltration of cytotoxic T lymphocytes (CTLs). Herein, cancer-associated fibroblasts (CAFs)-targeted nanoemulsions are tailored to combine the ICD induction and the TME reprogramming to sensitize checkpoint blockade immunotherapy. Melittin, as an ICD inducer and an antifibrotic agent, is efficiently encapsulated into the nanoemulsion accompanied by a nitric oxide donor to improve its bioavailability and tumor targeting. The nanoemulsions exhibited dual functionality by directly inducing direct cancer cell death and enhancing the tumoral immunogenicity, while also synergistically reprogramming the TME through reversing the activated CAFs, decreasing collagen deposition and restoring tumor vessels. Consequently, these nanemulsions successfully facilitated the CTLs infiltration and suppressing the recruitment of immunosuppressive cells. A combination of AE-MGNPs and anti-CTLA-4 antibody greatly elicited a striking level of antitumor T-cell response to suppress tumor growth in CAFs-rich colorectal tumor models. Our work emphasized the integration of the ICD induction with simultaneous modulation of the TME to enhance the sensitivity of patients to checkpoint blockade immunotherapy.