Microbes mediated immunogenic cell death in cancer immunotherapy.

Immunogenic cell death (ICD) is one of the 12 distinct cell death forms, which can trigger immune system to fight against cancer cells. During ICD, a number of cellular changes occur that can stimulate an immune response, including the release of molecules called damage-associated molecular patterns (DAMPs), signaling to immune cells to recognize and attack cancer cells. By virtue of their pivotal role in immune surveillance, ICD-based drug development has been a new approach to explore novel therapeutic combinations and personalized strategies in cancer therapy. Several small molecules and microbes can induce ICD-relevant signals and cause cancer cell death. In this review, we highlighted the role of microbe-mediate ICD in cancer immunotherapy and described the mechanisms through which microbes might serve as ICD inducers in cancer treatment. We also discussed current attempts to combine microbes with chemotherapy regimens or immune checkpoint inhibitors (ICIs) in the treatment of cancer patients. We surmise that manipulation of microbes may guide personalized therapeutic interventions to facilitate anticancer immune response.

Holistic immunomodulation for small cell lung cancer.

Small cell lung cancer (SCLC) is characterized by a high mortality rate, rapid growth, and early metastasis, which lead to a poor prognosis. Moreover, limited clinical treatment options further lower the survival rate of patients. Therefore, novel technology and agents are urgently required to enhance clinical efficacy. In this review, from a holistic perspective, we summarized the therapeutic targets, agents and strategies with the most potential for treating SCLC, including chimeric antigen receptor (CAR) T therapy, immunomodulating antibodies, traditional Chinese medicines (TCMs), and the microbiota, which have been found recently to improve the clinical outcomes and prognosis of SCLC. Multiomics technologies can be integrated to develop effective diagnostic methods and identify new targets for new drug discovery in SCLC. We discussed in depth the feasibility, potential, and challenges of these new strategies, as well as their combinational treatments, which may provide promising alternatives for enhancing the clinical efficacy of SCLC in the future.

TRP channels in cancer: Therapeutic opportunities and research strategies.

The influence of gut microbiota on transient receptor potential (TRP) channels has been identified as an important element in the development of gastrointestinal conditions, yet its involvement in cancer progression is not as thoroughly understood. This review explores the multifaceted roles of TRP channels in oncogenesis and emphasizes their significance in cancer progression and therapeutic outcomes. Critical focus was placed on the influence of traditional medicines, such as traditional Chinese medicine (TCM) related aromatic medicines, on TRP channel functions. Moreover, we explored the interplay between the gut microbiota and TRP channels in cancer signaling, highlighting the therapeutic potential of targeting this axis in cancer treatment. The impact of current therapies on TRP channel function was examined, demonstrating the need for a comprehensive understanding of how different modalities affect TRP channels in cancer. Technological advancements, including artificial intelligence (AI) tools and computer-aided drug development (CADD), have been discussed in the context of leveraging TRP channels for innovative cancer therapies. Future directions emphasize the potential applications of TRP channel research in advancing cancer treatment and enhancing patients' well-being.

Harnessing natural product polysaccharides against lung cancer and revisit its novel mechanism.

The incidence and mortality of lung cancer are on the rise worldwide. However, the benefit of clinical treatment in lung cancer is limited. Owning to important sources of drug development, natural products have received constant attention around the world. Main ingredient polysaccharides in natural products have been found to have various activities in pharmacological research. In recent years, more and more scientists are looking for the effects and mechanisms of different natural product polysaccharides on lung cancer. In this review, we focus on the following aspects: First, natural product polysaccharides have been discovered to directly suppress the growth of lung cancer cells, which can be effective in limiting tumor progression. Additionally, polysaccharides have been considered to enhance immune function, which can play a pivotal role in fighting lung cancer. Lastly, polysaccharides can improve the efficacy of drugs in lung cancer treatment by regulating the gut microbiota. Overall, the research of natural product polysaccharides in the treatment of lung cancer is a promising area that has the potential to lead to new clinical treatments. With better understanding, natural product polysaccharides have the potential to become important components of future lung cancer treatments.

Dual inhibitors of DNMT and HDAC remodels the immune microenvironment of colorectal cancer and enhances the efficacy of anti-PD-L1 therapy.

Colorectal cancer is the second most prevalent and deadly cancer worldwide. The emergence of immune checkpoint therapy has provided a revolutionary strategy for the treatment of solid tumors. However, less than 5 % of colorectal cancer patients respond to immune checkpoint therapy. Thus, it is of great scientific significance to develop "potentiators" for immune checkpoint therapy. In this study, we found that knocking down different DNMT and HDAC isoforms could increase the expression of IFNs in colorectal cancer cells, which can enhance the effectiveness of immune checkpoint therapy. Therefore, the combined inhibition of DNMT and HDAC cloud synergistically enhance the effect of immunotherapy. We found that dual DNMT and HDAC inhibitors C02S could inhibit tumor growth in immunocompetent mice but not in immunocompromised nude mice, which indicates that C02S exerts its antitumor effects through the immune system. Mechanistically, C02S could increase the expression of ERVs, which generated the intracellular levels of dsRNA in tumor cells, and then promotes the expression of IFNs through the RIG-I/MDA5-MAVS signaling pathway. Moreover, C02S increased the immune infiltration of DCs and T cells in microenvironment, and enhanced the efficacy of anti-PD-L1 therapy in MC38 and CT26 mice model. These results confirmed that C02S can activate IFNs through the RIG-I/MDA5-MAVS signaling pathway, remodel the tumor immune microenvironment and enhance the efficacy of immune checkpoint therapy, which provides new evidence and solutions for the development of "potentiator" for colorectal cancer immunotherapy.

MMP14high macrophages orchestrate progressive pulmonary fibrosis in SR-Ag-induced hypersensitivity pneumonitis.

Fibrotic hypersensitivity pneumonitis (FHP) is a fatal interstitial pulmonary disease with limited treatment options. Lung macrophages are a heterogeneous cell population that exhibit distinct subsets with divergent functions, playing pivotal roles in the progression of pulmonary fibrosis. However, the specific macrophage subpopulations and underlying mechanisms involved in the disease remain largely unexplored. In this study, a decision tree model showed that matrix metalloproteinase-14 (MMP14) had higher scores for important features in the up-regulated genes in macrophages from mice exposed to the Saccharopolyspora rectivirgula antigen (SR-Ag). Using single-cell RNA sequencing (scRNA-seq) analysis of hypersensitivity pneumonitis (HP) mice profiles, we identified MMP14high macrophage subcluster with a predominant M2 phenotype that exhibited higher activity in promoting fibroblast-to myofibroblast transition (FMT). We demonstrated that suppressing toll-like receptor 2 (TLR2) and nuclear factor kappa-B (NF-κB) could attenuate MMP14 expression and exosome secretion in macrophages stimulation with SR-Ag. The exosomes derived from MMP14-overexpressing macrophages were found to be more effective in regulating the transition of fibroblasts through exosomal MMP14. Importantly, it was observed that the transfer of MMP14-overexpressing macrophages into mice promoted lung inflammation and fibrosis induced by SR-Ag. NSC-405020 binding to the hemopexin domain (PEX) of MMP-14 ameliorated lung inflammation and fibrosis induced by SR-Ag in mice. Thus, MMP14-overexpressing macrophages may be an important mechanism contributing to the exacerbation of allergic reactions. Our results indicated that MMP14 in macrophages has the potential to be a therapeutic target for HP.

Comparative Genomics Reveals Insights into the Divergent Evolution of Astigmatic Mites and Household Pest Adaptations.

Highly diversified astigmatic mites comprise many medically important human household pests such as house dust mites causing ∼1-2% of all allergic diseases globally; however, their evolutionary origin and diverse lifestyles including reversible parasitism have not been illustrated at the genomic level, which hampers allergy prevention and our exploration of these household pests. Using six high-quality assembled and annotated genomes, this study not only refuted the monophyly of mites and ticks, but also thoroughly explored the divergence of Acariformes and the diversification of astigmatic mites. In monophyletic Acariformes, Prostigmata known as notorious plant pests first evolved, and then rapidly evolving Astigmata diverged from soil oribatid mites. Within astigmatic mites, a wide range of gene families rapidly expanded via tandem gene duplications, including ionotropic glutamate receptors, triacylglycerol lipases, serine proteases and UDP glucuronosyltransferases. Gene diversification after tandem duplications provides many genetic resources for adaptation to sensing environmental signals, digestion, and detoxification in rapidly changing household environments. Many gene decay events only occurred in the skin-burrowing parasitic mite Sarcoptes scabiei. Throughout the evolution of Acariformes, massive horizontal gene transfer events occurred in gene families such as UDP glucuronosyltransferases and several important fungal cell wall lytic enzymes, which enable detoxification and digestive functions and provide perfect drug targets for pest control. This comparative study sheds light on the divergent evolution and quick adaptation to human household environments of astigmatic mites and provides insights into the genetic adaptations and even control of human household pests.

Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?

Machine-learning (ML)-based scoring functions (MLSFs) have gradually emerged as a promising alternative for protein-ligand binding affinity prediction and structure-based virtual screening. However, clouds of doubts have still been raised against the benefits of this novel type of scoring functions (SFs). In this study, to benchmark the performance of target-specific MLSFs on a relatively unbiased dataset, the MLSFs trained from three representative protein-ligand interaction representations were assessed on the LIT-PCBA dataset, and the classical Glide SP SF and three types of ligand-based quantitative structure-activity relationship (QSAR) models were also utilized for comparison. Two major aspects in virtual screening campaigns, including prediction accuracy and hit novelty, were systematically explored. The calculation results illustrate that the tested target-specific MLSFs yielded generally superior performance over the classical Glide SP SF, but they could hardly outperform the 2D fingerprint-based QSAR models. Although substantial improvements could be achieved by integrating multiple types of protein-ligand interaction features, the MLSFs were still not sufficient to exceed MACCS-based QSAR models. In terms of the correlations between the hit ranks or the structures of the top-ranked hits, the MLSFs developed by different featurization strategies would have the ability to identify quite different hits. Nevertheless, it seems that target-specific MLSFs do not have the intrinsic attributes of a traditional SF and may not be a substitute for classical SFs. In contrast, MLSFs can be regarded as a new derivative of ligand-based QSAR models. It is expected that our study may provide valuable guidance for the assessment and further development of target-specific MLSFs.

Do we need different machine learning algorithms for QSAR modeling? A comprehensive assessment of 16 machine learning algorithms on 14 QSAR data sets.

Although a wide variety of machine learning (ML) algorithms have been utilized to learn quantitative structure-activity relationships (QSARs), there is no agreed single best algorithm for QSAR learning. Therefore, a comprehensive understanding of the performance characteristics of popular ML algorithms used in QSAR learning is highly desirable. In this study, five linear algorithms [linear function Gaussian process regression (linear-GPR), linear function support vector machine (linear-SVM), partial least squares regression (PLSR), multiple linear regression (MLR) and principal component regression (PCR)], three analogizers [radial basis function support vector machine (rbf-SVM), K-nearest neighbor (KNN) and radial basis function Gaussian process regression (rbf-GPR)], six symbolists [extreme gradient boosting (XGBoost), Cubist, random forest (RF), multiple adaptive regression splines (MARS), gradient boosting machine (GBM), and classification and regression tree (CART)] and two connectionists [principal component analysis artificial neural network (pca-ANN) and deep neural network (DNN)] were employed to learn the regression-based QSAR models for 14 public data sets comprising nine physicochemical properties and five toxicity endpoints. The results show that rbf-SVM, rbf-GPR, XGBoost and DNN generally illustrate better performances than the other algorithms. The overall performances of different algorithms can be ranked from the best to the worst as follows: rbf-SVM > XGBoost > rbf-GPR > Cubist > GBM > DNN > RF > pca-ANN > MARS > linear-GPR ≈ KNN > linear-SVM ≈ PLSR > CART ≈ PCR ≈ MLR. In terms of prediction accuracy and computational efficiency, SVM and XGBoost are recommended to the regression learning for small data sets, and XGBoost is an excellent choice for large data sets. We then investigated the performances of the ensemble models by integrating the predictions of multiple ML algorithms. The results illustrate that the ensembles of two or three algorithms in different categories can indeed improve the predictions of the best individual ML algorithms.

Upgrade of chrysomycin A as a novel topoisomerase II inhibitor to curb KRAS-mutant lung adenocarcinoma progression.

A primary strategy employed in cancer therapy is the inhibition of topoisomerase II (Topo II), implicated in cell survival. However, side effects and adverse reactions restrict the utilization of Topo II inhibitors. Thus, investigations focus on the discovery of novel compounds that are capable of inhibiting the Topo II enzyme and feature safer toxicological profiles. Herein, we upgrade an old antibiotic chrysomycin A from Streptomyces sp. 891 as a compelling Topo II enzyme inhibitor. Our results show that chrysomycin A is a new chemical entity. Notably, chrysomycin A targets the DNA-unwinding enzyme Topo II with an efficient binding potency and a significant inhibition of intracellular enzyme levels. Intriguingly, chrysomycin A kills KRAS-mutant lung adenocarcinoma cells and is negligible cytotoxic to normal cells at the cellular level, thus indicating a capability of potential treatment. Furthermore, mechanism studies demonstrate that chrysomycin A inhibits the Topo II enzyme and stimulates the accumulation of reactive oxygen species, thereby inducing DNA damage-mediated cancer cell apoptosis. Importantly, chrysomycin A exhibits excellent control of cancer progression and excellent safety in tumor-bearing models. Our results provide a chemical scaffold for the synthesis of new types of Topo II inhibitors and reveal a novel target for chrysomycin A to meet its further application.

CERS4 predicts positive anti-PD-1 response and promotes immunomodulation through Rhob-mediated suppression of CD8+Tim3+ exhausted T cells in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the main malignant tumors with high mortality and short survival time. Immunotherapy has become the standard treatment for advanced NSCLC, but it has the problems of drug resistance and low response rate. Therefore, obtaining effective biomarkers to predict and enhance immune checkpoint inhibitors (ICIs) efficacy in NSCLC is important. Sphingolipid metabolism is recently found to be closely involved in tumor immunotherapy. CERS4, an important sphingolipid metabolizing enzyme, is positively correlated with the efficacy of anti-PD-1 therapy for NSCLC. Upregulation of CERS4 expression could improve the efficacy of anti-PD-1 therapy for NSCLC. High expression of CERS4 could downregulate the expression of Rhob in tumor. Significantly, the ratio of CD4+/CD8+ T cell increased and the ratio of Tim-3+/CD8+ T cell decreased in spleen and peripheral blood cells. When Rhob was knocked out, the efficacy of PD-1 mAb treatment increased, and the frequency of Tim-3+ CD8+ T cell decreased. This finding further confirmed the role of sphingolipid metabolites in regulating the immunotherapeutic function of NSCLC. These metabolites may improve the efficacy of PD-1 mAb in NSCLC by regulating the CERS4/Rhob/Tim-3 axis. Overall, this study provided a potential and effective target for predicting and improving the efficacy of ICIs for NSCLC. It also provided a new perspective for the study on the mechanisms of ICIs resistance for NSCLC.

ß-Elemene enhances erlotinib sensitivity through induction of ferroptosis by upregulating lncRNA H19 in EGFR-mutant non-small cell lung cancer.

Nearly half of all Asian non-small cell lung cancer (NSCLC) patients harbour epidermal growth factor receptor (EGFR) mutations, and first-generation EGFR tyrosine kinase inhibitors (TKIs) are one of the first-line treatments that have improved the outcomes of these patients. Unfortunately, 20% of these patients can not benefit from the treatment. The basis of this primary resistance is poorly understood. Therefore, overcoming EGFR-TKI primary resistance and maintaining the efficacy of TKIs has become a key issue. ß-Elemene, a sesquiterpene compound extracted from Curcuma aromatica Salisb. (wenyujing), has shown potent antitumor effects. In this research, we found that ß-elemene combined with erlotinib enhanced the cytotoxicity of erlotinib to primary EGFR-TKI-resistant NSCLC cells with EGFR mutations and that ferroptosis was involved in the antitumor effect of the combination treatment. We found that lncRNA H19 was significantly downregulated in primary EGFR-TKI-resistant NSCLC cell lines and was upregulated by the combination treatment. Overexpression or knockdown of H19 conferred sensitivity or resistance to erlotinib, respectively, in both in vitro and in vivo studies. The high level of H19 enhanced the cytotoxicity of erlotinib by inducing ferroptosis. In conclusion, our data showed that ß-elemene combined with erlotinib could enhance sensitivity to EGFR-TKIs through induction of ferroptosis via H19 in primary EGFR-TKI-resistant lung cancer, providing a promising strategy to overcome EGFR-TKI resistance in NSCLC patients.

Natural Anticancer Molecules and Their Therapeutic Potential.

Cancer poses a significant global public health challenge [...].

Ginseng polysaccharides alter the gut microbiota and kynurenine/tryptophan ratio, potentiating the antitumour effect of antiprogrammed cell death 1/programmed cell death ligand 1 (anti-PD-1/PD-L1) immunotherapy.

OBJECTIVE: Programmed death 1 and its ligand 1 (PD-1/PD-L1) immunotherapy is promising for late-stage lung cancer treatment, however, the response rate needs to be improved. Gut microbiota plays a crucial role in immunotherapy sensitisation and Panax ginseng has been shown to possess immunomodulatory potential. In this study, we aimed to investigate whether the combination treatment of ginseng polysaccharides (GPs) and αPD-1 monoclonal antibody (mAb) could sensitise the response by modulating gut microbiota. DESIGN: Syngeneic mouse models were administered GPs and αPD-1 mAb, the sensitising antitumour effects of the combination therapy on gut microbiota were assessed by faecal microbiota transplantation (FMT) and 16S PacBio single-molecule real-time (SMRT) sequencing. To assess the immune-related metabolites, metabolomics analysis of the plasma samples was performed. RESULTS: We found GPs increased the antitumour response to αPD-1 mAb by increasing the microbial metabolites valeric acid and decreasing L-kynurenine, as well as the ratio of Kyn/Trp, which contributed to the suppression of regulatory T cells and induction of Teff cells after combination treatment. Besides, the microbial analysis indicated that the abundance of Parabacteroides distasonis and Bacteroides vulgatus was higher in responders to anti-PD-1 blockade than non-responders in the clinic. Furthermore, the combination therapy sensitised the response to PD-1 inhibitor in the mice receiving microbes by FMT from six non-responders by reshaping the gut microbiota from non-responders towards that of responders. CONCLUSION: Our results demonstrate that GPs combined with αPD-1 mAb may be a new strategy to sensitise non-small cell lung cancer patients to anti-PD-1 immunotherapy. The gut microbiota can be used as a novel biomarker to predict the response to anti-PD-1 immunotherapy.

Down-regulating Nrf2 by tangeretin reverses multiple drug resistance to both chemotherapy and EGFR tyrosine kinase inhibitors in lung cancer.

Multiple drug resistance (MDR) is the major obstacle for both chemotherapy and molecular-targeted therapy for cancer, which is mainly caused by overexpression of ABC transporters or genetic mutation of drug targets. Based on previous studies, we hypothesized that ROS/Nrf2 is the common target for overcoming acquired drug resistance to both targeted therapy and chemotherapy treatments. In this study, we firstly proved that the levels of ROS and Nrf2 were remarkably up-regulated in both H1975 (Gefitinib-resistant lung cancer cells with T790M) and A549/T (paclitaxel-resistant) cells, which is consistent with the clinical database analysis results of lung cancer patients that Nrf2 expression level is negatively related to survival rate. Nrf2 Knockdown with siRNA or tangeretin (TG, a flavonoid isolated from citrus peels) inhibited the MDR cell growth by suppressing the Nrf2 pathway, and efficiently enhanced the anti-tumor effects of paclitaxel and AZD9291 (the third generation of TKI) in A549/T or H1975, respectively. Moreover, TG sensitized A549/T cells-derived xenografts to paclitaxel via inhibiting Nrf2 and its downstream target P-gp, leading to an increased paclitaxel concentration in tumors. Collectively, targeting Nrf2 to enhance ROS may be a common target for overcoming the acquired drug resistance and enhancing the therapeutic effects of chemotherapy and molecular-targeted therapy.

Integrated analysis of single-cell and bulk RNA sequencing reveals pro-fibrotic PLA2G7high macrophages in pulmonary fibrosis.

Pulmonary fibrosis (PF) is the pathological change of end-stage interstitial lung diseases with high mortality and limited therapeutic options. Lung macrophages have distinct subsets with divergent functions, and play critical roles in the pathogenesis of PF. In this study, integrative analysis of lung single-cell and bulk RNA-seq data from patients with fibrotic hypersensitivity pneumonitis and idiopathic pulmonary fibrosis was utilized to identify particular macrophage subsets during the development of PF. We find a specific macrophage subpopulation highly expressing PLA2G7 in fibrotic lungs. We performed additional single-cell RNA-seq analysis to identify analogous macrophage population in bleomycin (BLM)-induced mouse pulmonary fibrosis models. By in vitro and in vivo experiments, we further reveal the pro-fibrotic role for this PLA2G7high macrophage subset in fibroblast-to-myofibroblast transition (FMT) during pulmonary fibrosis. PLA2G7 promotes FMT via LPC/ATX/LPA/LPA2 axis in macrophages. Moreover, PLA2G7 is regulated by STAT1, and pharmacological inhibition of PLA2G7 by Darapladib ameliorates pulmonary fibrosis in BLM-induced mice. The results of this study support the view that PLA2G7high macrophage subpopulation contributes importantly to the pathogenesis of PF, which provides a potential way for targeted therapy.

Bacteria-based nanodrug for anticancer therapy.

Bacteria-based immunotherapy has become a promising strategy to induce innate and adaptive responses for fighting cancer. The advantages of bacteriolytic tumor therapy mainly lie in stimulation of innate immunity and colonization of some bacteria targeting the tumor microenvironment (TME). These bacteria have cytotoxic proteins and immune modulating factors that can effectively restrain tumor growth. However, cancer is a multifactorial disease and single therapy is typically unable to eradicate tumors. Rapid progress has been made in combining bacteria with nanotechnology. Using the nanomolecular properties of bacterial products for tumor treatment preserves many features from the original bacteria while providing some unique advantages. Nano-bacterial therapy can enhance permeability and retention of drugs, increase the tolerability of the targeted drugs, promote the release of immune cell mediators, and induce immunogenic cell death pathways. In addition, combining nano-bacterial mediated antitumor therapeutic systems with modern therapy is an effective strategy for overcoming existing barriers in antitumor treatment and can achieve satisfactory therapeutic efficacy. Overall, exploring the immune antitumor characteristics of adjuvant clinical treatment with bacteria can provide potential efficacious treatment strategies for combatting cancer.

Andrographolide suppresses non-small-cell lung cancer progression through induction of autophagy and antitumor immune response.

Despite recent advances in diagnosis and therapeutic strategies, treatment of non-small-cell lung cancer (NSCLC) remains unsatisfactory in terms of prognosis. Andrographolide (AD), a principal active component of Andrographis paniculata (Burm.f.) Nees, exerts anti-cancer therapeutic properties. AD has been used for centuries in China for clinical treatment of viral infections. However, the pharmacological biology of AD in NSCLC remains unknown. In this study, AD regulated autophagy and PD-L1 expression in NSCLC. Molecular dynamics simulations indicated that AD bound directly to signal transducer and activator of transcription-3 (STAT3) with high affinity. Proteomics analysis indicated that AD reduced the expression of tumour PD-L1 in NSCLC by suppressing JAK2/STAT3 signalling. AD modulated the P62-dependent selective autophagic degradation of PD-L1 by inhibiting STAT3 phosphorylation. In vivo study revealed that AD suppressed tumour growth in H1975 xenograft mice and Lewis lung carcinoma cell models, and better efficacy was obtained at higher concentrations. AD prolonged the survival time of the mice and enhanced the treatment efficacy of anti-PD-1 mAb immunotherapy by stimulating CD8+ T cell infiltration and function. This work elucidated the specific mechanism by which AD inhibited NSCLC. Treatment with the combination of AD and anti-PD-1 mAb immunotherapy could be a potential strategy for patients with NSCLC.

In Silico Study of the Acquired Resistance Caused by the Secondary Mutations of KRAS G12C Protein Using Long Time Molecular Dynamics Simulation and Markov State Model Analysis.

Kirsten rat sarcoma viral oncogene homolog (KRAS) is a small GTPase protein which plays an important role in the treatment of KRAS mutant cancers. The FDA-approved AMG510 and MRTX849 (phase III clinical trials) are two potent KRASG12C-selective inhibitors that target KRAS G12C. However, the drug resistance caused by the second-site mutation in KRAS has emerged, and the mechanisms of drug resistance at atom level are still unclear. To clarify the mechanisms of drug resistance, we conducted long time molecular dynamics simulations (75 µs in total) to study the structural and energetic features of KRAS G12C and its four drug resistant variants to inhibitors. The combined binding free energy calculation and protein-ligand interaction fingerprint revealed that these second-site mutations indeed caused KRAS to produce different degrees of resistance to AMG510 and MRTX849. Furthermore, Markov State Models and 2D-free energy landscapes analysis revealed the difference in conformational changes of mutated KRAS bound with and without inhibitors. Furthermore, the comparative analysis of these systems showed that there were differences in their allosteric signal pathways. These findings provide the molecular mechanism of drug resistance, which helps to guide novel KRAS G12C inhibitor design to overcome drug resistance.

Potential prognostic factors in progression-free survival for patients with cervical cancer.

BACKGROUND: Cervical cancer continues to be one of the leading causes of cancer deaths among females in low and middle-income countries. In this study, we aimed to assess the independent prognostic value of clinical and potential prognostic factors in progression-free survival (PFS) in cervical cancer. METHODS: We conducted a retrospective study on 92 cervical cancer patients treated from 2017 to 2019 at the Zhuhai Hospital of Traditional Chinese and Western Medicine. Tumor characteristics, treatment options, progression-free survival and follow-up information were collected. Kaplan-Meier method was used to assess the PFS. RESULTS: Results showed that the number of retrieved lymph nodes had a statistically significant effect on PFS of cervical cancer patients (P = 0.002). Kaplan-Meier survival curve analysis showed that cervical cancer patients with initial symptoms age 25-39 had worse survival prognoses (P = 0.020). And the using of uterine manipulator in laparoscopic treatment showed a better prognosis (P < 0.001). A novel discovery of our study was to verify the prognostic values of retrieved lymph nodes count combining with FIGO staging system, which had never been investigated in cervical cancer before. According to the Kaplan-Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis, significant improvements were found after the combination of retrieved lymph nodes count and FIGO stage in predicting PFS for cervical cancer patients (P < 0.001, AUC = 0.826, 95% CI: 0.689-0.962). CONCLUSION: Number of retrieved lymph nodes, initial symptoms age, uterine manipulator, and retrieved lymph nodes count combining with FIGO staging system could be potential prognostic factors for cervical cancer patients.