HELM-GPT: de novo macrocyclic peptide design using generative pre-trained transformer.

MOTIVATION: Macrocyclic peptides hold great promise as therapeutics targeting intracellular proteins. This stems from their remarkable ability to bind flat protein surfaces with high affinity and specificity while potentially traversing the cell membrane. Research has already explored their use in developing inhibitors for intracellular proteins, such as KRAS, a well-known driver in various cancers. However, computational approaches for de novo macrocyclic peptide design remain largely unexplored. RESULTS: Here, we introduce HELM-GPT, a novel method that combines the strength of the hierarchical editing language for macromolecules (HELM) representation and generative pre-trained transformer (GPT) for de novo macrocyclic peptide design. Through reinforcement learning (RL), our experiments demonstrate that HELM-GPT has the ability to generate valid macrocyclic peptides and optimize their properties. Furthermore, we introduce a contrastive preference loss during the RL process, further enhanced the optimization performance. Finally, to co-optimize peptide permeability and KRAS binding affinity, we propose a step-by-step optimization strategy, demonstrating its effectiveness in generating molecules fulfilling both criteria. In conclusion, the HELM-GPT method can be used to identify novel macrocyclic peptides to target intracellular proteins. AVAILABILITY AND IMPLEMENTATION: The code and data of HELM-GPT are freely available on GitHub (https://github.com/charlesxu90/helm-gpt).

LINC01605 promotes malignant phenotypes of cervical cancer via miR-149-3p/WNT7B axis.

BACKGROUND: Long non-coding RNAs (LncRNA) play a pivotal role in the progression of various malignancies. Despite recent identification as an oncogene associated with tumorigenesis. The precise role of LINC01605 in cervical cancer (CC) remains unclear. Therefore, the objective of this study was to investigate the influence of LINC01605 on proliferation and invasion of CC cells, while also exploring its potential underlying mechanisms. METHODS: The expression of LINC01605 in CC cell lines was analyzed using the TCGA database and qRT-PCR. Various assays, including CCK-8 and transwell analysis, were conducted on CC cells to assess the influence of LINC01605 on their proliferation, migration, and invasion capabilities. Bioinformatics and dual luciferase reporter gene assays were employed to analyze the target genes of LINC01605 and miR-149-3p. To further investigate the mechanism of action, transfection and investigation were performed using specific siRNA, miRNA mimics, or inhibitors. RESULTS: The expression of LINC01605 exhibited a significant increase in CC cell lines, and this upregulation was associated with an unfavorable prognosis. Modulating the expression of LINC01605, either by down-regulating or up-regulating it, exerted suppressive or stimulatory effects on the growth and invasion of HeLa and Siha cells. LINC01605 functioned as a competitive endogenous RNA (ceRNA) for miR-149-3p, with WNT7B being identified as a target gene of miR-149-3p. The involvement of LINC01605 in CC development is facilitated by its ability to regulate the expression of WNT7B through sequestering miR-149-3p. CONCLUSION: Our study demonstrates that LINC01605 acts as a competitive endogenous RNA in modulating the effects of WNT7B on the proliferation and invasion of CC cells by sequestering miR-149-3p. This research provides novel insights into the involvement of LINC01605 in the advancement of CC.

Facile synthesis of hierarchical W18O49 microspheres by solvothermal method and their optical absorption properties.

In this study, a simple route for the synthesis of hierarchical W18O49 assembled by nanowires is reported. The morphologies and formation of W18O49 single-crystal could be controlled by changing the concentration of WCl6-ethanol solution. This synthesis strategy has the advantages that the hierarchical W18O49 microspheres could be economic synthesized at 180 °C without adding additives. Furthermore, efficient optical absorption properties in ultraviolet, visible and near-infrared region were obtained for the hierarchical W18O49 microspheres comparing with nanowires. These results will further promote the research of tungsten-based oxide nanomaterials.

LINC02086 inhibits ferroptosis and promotes malignant phenotypes of pancreatic cancer via miR-342-3p/CA9 axis.

Long noncoding RNAs (lncRNAs) play important roles in modulating the tumorigenesis and progression of malignant tumors. LINC02086 is a newly identified oncogene associated with tumorigenesis, but its role in pancreatic cancer (PC) has not been fully elucidated. In this study we examined the expression levels of LINC02086, miR-342-3p, and CA9 in PC. The relationship of ferroptosis with these factors was analyzed by detecting the expression levels of Fe2+, reactive oxygen species (ROS), and ferroptosis marker proteins. The expression of these genes was altered to observe their effects on cell proliferation, migration, and invasion ability. Bioinformatics was used to predict target genes, and the binding relationship was verified luciferase reporter assay. Finally, the function of LINC02086 was evaluated in vivo. The findings suggest that LINC02086 is highly expressed in PC tissues and cell lines and is correlated with a poor prognosis. In vitro experiments demonstrated that LINC02086 knockdown promoted ferroptosis in PC cells to suppress their malignant phenotype. LINC02086 acts as a competitive endogenous RNA that adsorbed miR-342-3p. miR-342-3p hinders the malignant progression of PC by promoting ferroptosis. In addition, miR-342-3p targets CA9 and affects its function. Further mechanistic studies revealed that LINC02086 inhibits ferroptosis and promotes PC progression by acting as a sponge for miR-342-3p to upregulate CA9 expression. In vivo experiments further confirmed this mechanism. Taken together, LINC02086 upregulates CA9 expression by competitively binding with miR-342-3p, thereby inhibiting ferroptosis in PC cells and promoting their malignant phenotype. The results of our study provide new insights into how LINC02086 contributes to the progression of PC.

PractiCPP: a deep learning approach tailored for extremely imbalanced datasets in cell-penetrating peptide prediction.

MOTIVATION: Effective drug delivery systems are paramount in enhancing pharmaceutical outcomes, particularly through the use of cell-penetrating peptides (CPPs). These peptides are gaining prominence due to their ability to penetrate eukaryotic cells efficiently without inflicting significant damage to the cellular membrane, thereby ensuring optimal drug delivery. However, the identification and characterization of CPPs remain a challenge due to the laborious and time-consuming nature of conventional methods, despite advances in proteomics. Current computational models, however, are predominantly tailored for balanced datasets, an approach that falls short in real-world applications characterized by a scarcity of known positive CPP instances. RESULTS: To navigate this shortfall, we introduce PractiCPP, a novel deep-learning framework tailored for CPP prediction in highly imbalanced data scenarios. Uniquely designed with the integration of hard negative sampling and a sophisticated feature extraction and prediction module, PractiCPP facilitates an intricate understanding and learning from imbalanced data. Our extensive computational validations highlight PractiCPP's exceptional ability to outperform existing state-of-the-art methods, demonstrating remarkable accuracy, even in datasets with an extreme positive-to-negative ratio of 1:1000. Furthermore, through methodical embedding visualizations, we have established that models trained on balanced datasets are not conducive to practical, large-scale CPP identification, as they do not accurately reflect real-world complexities. In summary, PractiCPP potentially offers new perspectives in CPP prediction methodologies. Its design and validation, informed by real-world dataset constraints, suggest its utility as a valuable tool in supporting the acceleration of drug delivery advancements. AVAILABILITY AND IMPLEMENTATION: The source code of PractiCPP is available on Figshare at https://doi.org/10.6084/m9.figshare.25053878.v1.

Clinical significance of tumor suppressor genes methylation in circulating tumor DNA of patients with pancreatic cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a potential diagnostic and prognostic biomarker in various tumors. However, the role of tumor suppressor genes (TSGs) methylation in ctDNA of patients with pancreatic cancer (PC) remains largely unclear. METHODS: Patients with PC (n = 43), pancreatic benign diseases (n = 39), and healthy controls (n = 20) were enrolled in the study. Quantitative analysis of methylation pattern of five candidate TSGs including NPTX2, RASSF1A, EYA2, p16, and ppENK in ctDNA was performed by next generation sequencing (NGS). The diagnostic performances of these 5-TSGs methylation were assessed by the operating characteristic (ROC) curve and clinicopathological features correlation analysis. Meanwhile, the changes in methylation levels of these 5-TSGs on the 7th postoperative day were evaluated in 23 PC patients who underwent radical resection. RESULTS: The methylation levels of RASSF1A, EYA2, ppENK and p16 genes in patients with PC were significantly higher than those in healthy controls. EYA2, p16 and ppENK genes showed significantly hypermethylation in PC than those in pancreatic benign diseases. NPTX2, RASSF1A, EYA2, p16 and ppENK genes showed significantly hypermethylation in pancreatic benign diseases than those in healthy controls (P < 0.05). The methylation levels of these 5 candidate TSGs were not correlated with the tumor size, nerve invasion, lymph node metastasis and TNM stage of PC. The AUC of these biomarkers for diagnosis of PC ranged from 0.65 to 0.96. The AUC values of these methylated genes and CpG sites for differentiating malignant and benign pancreatic diseases were ranging from 0.68 to 0.92. Combined the hypermethylated genes improved the detective ability of PC than single gene. The methylation levels of NPTX2, EYA2 and ppENK genes were significantly decreased after radical resection of PC. CONCLUSION: Quantitative analysis of methylation pattern of NPTX2, RASSF1A, EYA2, p16 and ppENK in ctDNA by NGS could be a valuable non-invasive tool for detection and monitoring of PC.

Bioinformatics-based analysis of the relationship between disulfidptosis and prognosis and treatment response in pancreatic cancer.

Tumor formation is closely associated with disulfidptosis, a new form of cell death induced by disulfide stress-induced. The exact mechanism of action of disulfidptosis in pancreatic cancer (PCa) is not clear. This study analyzed the impact of disulfidptosis-related genes (DRGs) on the prognosis of PCa and identified clusters of DRGs, and based on this, a risk score (RS) signature was developed to assess the impact of RS on the prognosis, immune and chemotherapeutic response of PCa patients. Based on transcriptomic data and clinical information from PCa tissue and normal pancreatic tissue samples obtained from the TCGA and GTEx databases, differentially expressed and differentially surviving DRGs in PCa were identified from among 15 DRGs. Two DRGs clusters were identified by consensus clustering by merging the PCa samples in the GSE183795 dataset. Analysis of DRGs clusters about the PCa tumor microenvironment and differential analysis to obtain differential genes between the two DRG clusters. Patients were then randomized into the training and testing sets, and a prognostic prediction signature associated with disulfidptosis was constructed in the training set. Then all samples were divided into high-disulfidptosis-risk (HDR) and low-disulfidptosis-risk (LDR) subgroups based on the RS calculated from the signature. The predictive efficacy of the signature was assessed by survival analysis, nomograms, correlation analysis of clinicopathological characteristics, and the receiver operating characteristic (ROC) curves. To assess differences between different risk subgroups in immune cell infiltration, expression of immune checkpoint molecules, somatic gene mutations, and effectiveness of immunotherapy and chemotherapy. The GSE57495 dataset was used as external validation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of DRGs. A total of 12 DRGs with differential expression and prognosis in PCa were identified, based on which a risk-prognosis signature containing five differentially expressed genes (DEGs) was developed. The signature was a good predictor and an independent risk factor. The nomogram and calibration curve shows the signature's excellent clinical applicability. Functional enrichment analysis showed that RS was associated with tumor and immune-related pathways. RS was strongly associated with the tumor microenvironment, and analysis of response to immunotherapy and chemotherapy suggests that the signature can be used to assess the sensitivity of treatments. External validation further demonstrated the model's efficacy in predicting the prognosis of PCa patients, with RT-qPCR and immunohistochemical maps visualizing the expression of each gene in PCa cell lines and the tissue. Our study is the first to apply the subtyping model of disulfidptosis to PCa and construct a signature based on the disulfidptosis subtype, which can provide an accurate assessment of prognosis, immunotherapy, and chemotherapy response in PCa patients, providing new targets and directions for the prognosis and treatment of PCa.

A novel necroptosis-related long non-coding RNA signature predicts prognosis and immune response in cervical cancer patients.

BACKGROUND: Necroptosis has been linked to the development of tumors. Long non-coding RNAs (IncRNAs) have been identified as having a major role in numerous biological and pathological procedures. Despite this, the precise role that necroptosis-related lncRNAs (NRLs) have in cervical cancer (CC) and their potential for predicting its prognosis is still to a large extent unclear. METHODS: Gene expression RNA-sequencing data, mutational data, and clinical profiles for 309 CC patients were obtained from the Cancer Genome Atlas (TCGA) database. The NRLs were then identified with Pearson correlation analysis followed by splitting of the patients into training and validation sets in a 3:2 ratio. Cox and LASSO regression models were performed to construct a cervical cancer prognostic signature based on NRLs. This 5-NRLs signature was then verified by Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, and nomogram for prognostic prediction. Further, a correlation study between the risk score (RS) and immune cell infiltration, immune checkpoint molecules, tumor mutation burden (TMB), and the sensitivity of chemotherapy drug was conducted. To validate the 5-NRLs, a quantitative reverse transcription polymerase chain reaction (qRT-PCR) was finally performed. RESULTS: The 5-NRLs signature was designed to accurately predict the prognosis of CC. It consists of AC092153.1, AC007686.3, LINC01281, AC009097.2, and RUSC1-AS1 and was found to be highly predictive using ROC and Kaplan-Meier curves. Furthermore, when analyzed through stratified survival analysis, it was confirmed to be an independent risk factor for prognosis. The nomogram and calibration curves further validated its clinical utility. Moreover, distinct differences between two risk groups were observed when examining immune cell infiltration, immune checkpoint molecules, somatic gene alterations and half-inhibitory concentration of anticancer drug. CONCLUSIONS: The 5-NRLs signature is a novel and valuable tool for evaluating the prognosis of CC patients, providing clinicians with an informed decision-making framework to formulate tailored treatment plans for their patients.

Establishment of a novel signature to predict prognosis and immune characteristics of pancreatic cancer based on necroptosis-related long non-coding RNA.

BACKGROUND: Necroptosis plays an important role in tumorigenesis and tumour progression. Long noncoding RNAs (lncRNAs) have been proven to be regulatory factors of necroptosis in various tumours. However, the real role of necroptosis-related lncRNAs (NRLs) and their potential to predict the prognosis of pancreatic cancer (PC) remain largely unclear. The goal of this study was to identify NRLs and create a predictive risk signature in PC, explore its prognostic predictive performance, and further assess immunotherapy and chemotherapy responses. METHODS: RNA sequencing data, tumour mutation burden (TMB) data, and clinical profiles of 178 PC patients were downloaded from The Cancer Genome Atlas (TCGA) database. NRLs were identified using Pearson correlation analysis. Then, patients were divided into the training set and the validation set at a 1:1 ratio. Subsequently, Cox and LASSO regression analyses were conducted to establish a prognostic NRL signature in the training set and validation set. The predictive efficacy of the 5-NRL signature was assessed by survival analysis, nomogram, Cox regression, clinicopathological feature correlation analysis, and receiver operating characteristic (ROC) curve analysis. Furthermore, correlations between the risk score (RS) and immune cell infiltration, immune checkpoint molecules, somatic gene mutations, and anticancer drug sensitivity were analysed. Finally, we used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the 5-NRLs. RESULTS: A 5-NRL signature was established to predict the prognosis of PC, including LINC00857, AL672291.1, PTPRN2-AS1, AC141930.2, and MEG9. The 5-NRL signature demonstrated a high degree of predictive power according to ROC and Kaplan‒Meier curves and was revealed to be an independent prognostic risk factor via stratified survival analysis. Nomogram and calibration curves indicated the clinical adaptability of the signature. Immune-related pathways were linked to the 5-NRL signature according to enrichment analysis. Additionally, immune cell infiltration, immune checkpoint molecules, somatic gene mutations and the half-maximal inhibitory concentration (IC50) of chemotherapeutic agents were significantly different between the two risk subgroups. These results suggested that our model can be used to evaluate the effectiveness of immunotherapy and chemotherapy, providing a potential new strategy for treating PC. CONCLUSIONS: The novel 5-NRL signature is helpful for assessing the prognosis of PC patients and improving therapy options, so it can be further applied clinically.

Identification of cuproptosis-related lncRNA for predicting prognosis and immunotherapeutic response in cervical cancer.

Patients diagnosed with advanced cervical cancer (CC) have poor prognosis after primary treatment, and there is a lack of biomarkers for predicting patients with an increased risk of recurrence of CC. Cuproptosis is reported to play a role in tumorigenesis and progression. However, the clinical impacts of cuproptosis-related lncRNAs (CRLs) in CC remain largely unclear. Our study attempted to identify new potential biomarkers to predict prognosis and response to immunotherapy with the aim of improving this situation. The transcriptome data, MAF files, and clinical information for CC cases were obtained from the cancer genome atlas, and Pearson correlation analysis was utilized to identify CRLs. In total, 304 eligible patients with CC were randomly assigned to training and test groups. LASSO regression and multivariate Cox regression were performed to construct a cervical cancer prognostic signature based on cuproptosis-related lncRNAs. Afterwards, we generated Kaplan-Meier curves, receiver operating characteristic curves and nomograms to verify the ability to predict prognosis of patients with CC. Genes for assessing differential expression among risk subgroups were also evaluated by functional enrichment analysis. Immune cell infiltration and the tumour mutation burden were analysed to explore the underlying mechanisms of the signature. Furthermore, the potential value of the prognostic signature to predict response to immunotherapy and sensitivity to chemotherapy drugs was examined. In our study, a risk signature containing eight cuproptosis-related lncRNAs (AL441992.1, SOX21-AS1, AC011468.3, AC012306.2, FZD4-DT, AP001922.5, RUSC1-AS1, AP001453.2) to predict the survival outcome of CC patients was developed, and the reliability of the risk signature was appraised. Cox regression analyses indicated that the comprehensive risk score is an independent prognostic factor. Moreover, significant differences were found in progression-free survival, immune cell infiltration, therapeutic response to immune checkpoint inhibitors, and IC50 for chemotherapeutic agents between risk subgroups, suggesting that our model can be well employed to assess the clinical efficacy of immunotherapy and chemotherapy. Based on our 8-CRLs risk signature, we were able to independently assess the outcome and response to immunotherapy of CC patients, and this signature might benefit clinical decision-making for individualized treatment.

Distribution characteristics and clinical significance of infiltrating T cells in the tumor microenvironment of pancreatic cancer.

Tumor-infiltrating lymphocytes (TILs) are important components of the tumor microenvironment (TME). However, the distribution characteristics of TILs and their significance in pancreatic cancer (PC) remain largely unexplored. The levels of TILs, including the total number of T cells, cluster of differentiation (CD)4+ T cells, CD8+ cytotoxic T lymphocytes (CTLs), regulatory T-cells (Tregs), programmed cell death protein 1+ T cells and programmed cell death ligand 1 (PD-L1)+ T cells, in the TME of patients with PC were detected using multiple fluorescence immunohistochemistry. The associations between the number of TILs and the clinicopathological characteristics were investigated using χ2 tests. In addition, Kaplan-Meier survival and Cox regression analyses were used to assess the prognostic value of these TIL types. Compared with paracancerous tissues, in PC tissues, the proportions of total T cells, CD4+ T cells and CD8+ CTLs were markedly decreased, while those of Tregs and PD-L1+ T cells were significantly increased. The levels of CD4+ T cell and CD8+ CTL infiltrates were inversely associated with tumor differentiation. Higher infiltrates of Tregs and PD-L1+ T cells were closely associated with advanced N and TNM stages. It is important to note that the infiltrates of total T cells, CD4+ T cells, Tregs and PD-L1+ T cells in the TME were independent risk factors for the prognosis of PC. PC was characterized by an immunosuppressive TME with a decrease in the number of CD4+ T cells and CD8+ CTLs, and an increase in the number of Tregs and PD-L1+ T cells. Overall, the number of total T cells, CD4+ T cells, Tregs and PD-L1+ T cells in the TME was a potential predictive marker for the prognosis of PC.

Efficacy of adjuvant TACE on the prognosis of patients with HCC after hepatectomy: a multicenter propensity score matching from China.

BACKGROUND: The survival benefit of adjuvant transarterial chemoembolization (TACE) in patients with hepatectomy for hepatocellular carcinoma (HCC) after hepatectomy remains controversial. We aimed to investigate the survival efficacy of adjuvant TACE after hepatectomy for HCC. METHODS: 1491 patients with HCC who underwent hepatectomy between January 2018 and September 2021 at four medical centers in China were retrospectively analyzed, including 782 patients who received adjuvant TACE and 709 patients who did not receive adjuvant TACE. Propensity score matching (PSM) (1:1) was performed to minimize selection bias, which balanced the clinical characteristics of the two groups. RESULTS: A total of 1254 patients were enrolled after PSM, including 627 patients who received adjuvant TACE and 627 patients who did not receive adjuvant TACE. Patients who received adjuvant TACE had higher disease-free survival (DFS, 1- ,2-, and 3-year: 78%-68%-62% vs. 69%-57%-50%, p < 0.001) and overall survival (OS, 1- ,2-, and 3-year: 96%-88%-80% vs. 90%-77%-66%, p < 0.001) than those who did not receive adjuvant TACE (Median DFS was 39 months). Among the different levels of risk factors affecting prognosis [AFP, Lymphocyte-to-monocyte ratio, Maximum tumor diameter, Number of tumors, Child-Pugh classification, Liver cirrhosis, Vascular invasion (imaging), Microvascular invasion, Satellite nodules, Differentiation, Chinese liver cancer stage II-IIIa], the majority of patients who received adjuvant TACE had higher DFS or OS than those who did not receive adjuvant TACE. More patients who received adjuvant TACE accepted subsequent antitumor therapy such as liver transplantation, re-hepatectomy and local ablation after tumor recurrence, while more patients who did not receive adjuvant TACE accepted subsequent antitumor therapy with TACE after tumor recurrence (All p < 0.05). CONCLUSIONS: Adjuvant TACE may be a potential way to monitor early tumor recurrence and improve postoperative survival in patients with HCC.

Postoperative adjuvant transarterial chemoembolisation improves survival of hepatocellular carcinoma patients with microvascular invasion: A multicenter retrospective cohort.

BACKGROUND: We aimed to investigate the efficacy of postoperative adjuvant transarterial chemoembolisation (PA-TACE) in patients with hepatocellular carcinoma (HCC) complicated by microvascular invasion (MVI). METHODS: A retrospective analysis of 1505 patients with HCC who underwent hepatectomy at four medical centers, including 782 patients who received PA-TACE and 723 patients who did not receive adjuvant PA-TACE, has been conducted. Propensity score matching (PSM) (1:1) was performed on the data to minimise selection bias, which resulted in a balanced clinical profile between groups. RESULTS: After PSM, 620 patients who received PA-TACE and 620 patients who did not receive PA-TACE were included. Disease-free survival (DFS, 1-, 2-, and 3-year: 88%-68%-61% vs. 70%-58%-51%, p < 0.001) and overall survival (OS, 1-, 2-, and 3-year: 96%-89%-82% vs. 89%-77%-67%, p < 0.001) were significantly higher in patients who received PA-TACE than in those who did not. Patients with MVI who received PA-TACE had significantly higher DFS (1-, 2-, and 3-year: 68%-57%-48% vs. 46%-31%-27%, p < 0.001) and OS (1-, 2-, and 3-year: 96%-84%-77% vs. 79%-58%-40%, p < 0.001) than those who did not receive PA-TACE. Among the six different liver cancer stages, MVI-negative patients did not have significant survival outcomes from PA-TACE (p > 0.05), whereas MVI-positive patients achieved higher DFS and OS from it (p < 0.05). Liver dysfunction, fever, and nausea/vomiting were the most common adverse events in patients receiving PA-TACE. There was no significant difference in grade 3 or 4 adverse events between the groups (p > 0.05). CONCLUSIONS: Postoperative adjuvant transarterial chemoembolisation has a good safety profile and may be a potentially beneficial treatment modality for survival outcomes in patients with HCC, especially those with concomitant MVI.

Prediction of Prognosis and Molecular Mechanism of Ferroptosis in Hepatocellular Carcinoma Based on Bioinformatics Methods.

Background: As an iron-dependent type of programmed cell death, ferroptosis plays an important role in the pathogenesis and progression of hepatocellular carcinoma (HCC). Long noncoding RNAs (lncRNAs) have been linked to the prognosis of patients with HCC in a number of studies. Nevertheless, the predictive value of lncRNAs (FRLs) associated with ferroptosis in HCC has not been fully elucidated. Methods: Download RNA sequencing data and clinical profiles of HCC patients from The Cancer Genome Atlas (TCGA) database. The FRLs associated with prognosis were determined by Pearson's correlation analysis. After that, prognostic signature for FRLs was established using Cox and LASSO regression analyses. Meanwhile, survival analysis, correlation analysis of clinicopathological features, Cox regression, receiver operating characteristic (ROC) curve, and nomogram were used to analyze the FRL signature's predictive capacity. The relationship between signature risk score, immune cell infiltration, and chemotherapy drug sensitivity is further studied. Results: In total, 93 FRLs were found to be of prognostic value in patients with HCC. A five-FRL signature comprising AC015908.3, LINC01138, AC009283.1, Z83851.1, and LUCAT1 was created in order to enhance the prognosis prediction with HCC patients. The signature demonstrated a good predictive potency, according to the Kaplan-Meier and ROC curves. The five-FRL signature was found to be a risk factor independent of various clinical factors using Cox regression and stratified survival analysis. The high-risk group was shown to be enriched in tumorigenesis and immune-related pathways according to GSEA analysis. Additionally, immune cell infiltration, immune checkpoint molecules, and half-inhibitory concentrations differed considerably between risk groups, implying that this signature could be used to evaluate the clinical efficacy of chemotherapy and immunotherapy. Conclusion: The five-FRL risk signature is helpful for assessing the prognosis of HCC patients and improving therapy options, so it can be further applied clinically.

Hsa_circ_0046523 Mediates an Immunosuppressive Tumor Microenvironment by Regulating MiR-148a-3p/PD-L1 Axis in Pancreatic Cancer.

Background: Circular RNAs (circRNAs) are a novel type of non-coding RNA, play an important role in the progression of tumors. However, the function and mechanism of circRNAs in regulating immune microenvironment of pancreatic cancer (PC) remain largely unclear. Methods: The effects of hsa_circ_0046523 expression on proliferation, migration and invasion of PC cells were analyzed by CCK8 and Transwell assays. Flow cytometry was used to detect the proportion of CD4+ T cells, CD8+ T cells and Tregs in peripheral blood mononuclear cells (PBMCs) after co-culture, and the apoptosis, depletion and function of CD8+ T cells. The expression levels of immunoregulatory cytokines were detected by enzyme linked immunosorbent assay (ELISA). The dual-luciferase reporter was performed to determine the interaction between hsa_circ_0046523, miR-148a-3p, and PD-L1. Rescue experiments and PD-L1 blocking experiments were employed to investigate whether hsa_circ_0046523 exerts its biological function by miR-148a-3p/PD-L1 in PC. Furthermore, an immunocompetent murine PC model was established to confirm these findings. Results: Hsa_circ_0046523 expression was remarkably upregulated in PC tissues and cell lines. Moreover, high expression of hsa_circ_0046523 was correlated with advanced pathological stage and poorer prognosis. Hsa_circ_0046523 overexpression promoted the proliferation, migration and invasion of PC cells in vitro. Co-culture experiments confirmed that forced expression of hsa_circ_0046523 could decrease the proportion of CD4+ and CD8+ T cells, as well as increase the proportion of Tregs among peripheral blood mononuclear cells (PBMCs). Meanwhile, hsa_circ_0046523 overexpression promoted the apoptosis and exhaustion of CD8+ T cells, inhibited CD8+ T cell function, increased the secretion of immunosuppressive cytokines IL-10 and TGF-ß, and decreased the secretion of immune effector cytokines IFN-γ and IL-2 among PBMCs. Mechanistically, hsa_circ_0046523 exerted its biological function by binding to miR-148a-3p to upregulate PD-L1 expression in PC. Moreover, these immune modulating functions of miR-148a-3p/PD-L1 axis were also confirmed in an immunocompetent murine PC model. Conclusions: Our study suggests that hsa_circ_0046523/miR-148a-3p/PD-L1 regulatory axis mediates PC immunosuppressive microenvironment and these molecules are expected to be new targets for remodeling tumor immune microenvironment of PC.

Organ-Sparing Pancreatectomy for Benign or Low-Grade Malignant Pancreatic Tumors: A Single-Center Experience with 101 Consecutive Patients.

BACKGROUND Pancreaticoduodenectomy (PD) and distal pancreatectomy with splenectomy (DPS) are considered the standard procedures for pancreatic lesions. However, long-term metabolic consequences of PD and DPS applied for benign or low-grade malignant tumors need to be addressed. This study aimed to investigate the short- and long-term outcomes of organ-sparing pancreatectomy for benign or low-grade malignant pancreatic tumors in our institution. MATERIAL AND METHODS The clinical data of 101 patients with benign or low-grade malignant pancreatic tumors who underwent organ-sparing pancreatectomy from January 2009 to September 2021 were retrospectively analyzed, including 40 tumor enucleations (EN), 22 central pancreatectomies (CP), 25 spleen-preserving distal pancreatectomies (SPDP), 7 pylorus-preserving pancreaticoduodenectomies (PPPD) and 7 duodenum-preserving pancreatic head resections (DPPHR). RESULTS The mean operative time, intraoperative blood loss, and length of hospital stay were 182.9±74.6 min, 191.9±127.8 mL, and 11.6±8.1 days, respectively. EN had the shortest operative time, while DPPHR had the longest operative time. The mean intraoperative blood loss of DPPHR and PPPD was significantly greater than the others (all P<0.05). The length of hospital stay of PPPD was longest. The overall morbidity was 33.6%. The reoperation rate was 1.0% and there was no mortality. The incidence of pancreatic endocrine insufficiency and exocrine insufficiency were 5.9% and 6.9%, respectively. None patients had tumor recurrence during the follow-up period. CONCLUSIONS Organ-sparing pancreatectomy is associated with acceptable perioperative risk and postoperative complications and better long-term outcomes in the aspects of preservation of function and curability in benign or low-grade malignant pancreatic tumors.

A community challenge for a pancancer drug mechanism of action inference from perturbational profile data.

The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with ∼400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource serves as the basis for a DREAM Challenge assessing the accuracy and sensitivity of computational algorithms for de novo drug polypharmacology predictions. Dose-response and perturbational profiles for 32 kinase inhibitors are provided to 21 teams who are blind to the identity of the compounds. The teams are asked to predict high-affinity binding targets of each compound among ∼1,300 targets cataloged in DrugBank. The best performing methods leverage gene expression profile similarity analysis as well as deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessments of drug mechanisms of action.

Immune checkpoint inhibitor-induced myocarditis and myositis in liver cancer patients: A case report and literature review.

With the development of immunotherapy, immune checkpoint inhibitors (ICIs) are widely used in clinical oncology and have achieved good results. ICIs could induce immune-related adverse events (irAEs) in cancer treatment, which warrant sufficient attention. Among them, immune myositis can manifest severe symptoms affecting the whole body, and immune myocarditis occurs with a low incidence but high fatality rate. Here we report a case of grade 3/4 adverse reactions in a patient with partial hepatectomy for malignancy after using ICIs and describe the clinical presentation, laboratory results, treatment, and prognosis. It emphasizes that clinicians should focus on being alert to irAEs in liver cancer patients who have received ICI therapy. The case we present is a 56-year-old male diagnosed with hepatocellular carcinoma. Right hepatic lobectomy was performed in April 2019. Postoperative follow-up showed that transcatheter arterial chemoembolization (TACE) combined with sorafenib (400 mg twice daily) failed to stop the recurrence of the tumor. In December 2020, the patient started to use Camrelizumab injections (200mg/injection every 21 days as a cycle). After 3 cycles, the patient had decreased muscle strength in both lower extremities with chest tightness, dyspnea, and expectoration (whitish sputum). The diagnosis was ICIs injection-induced immune myocarditis and myositis accompanied. The patient's condition improved considerably by steroid pulse therapy timely. The case emphasizes that clinicians should focus on being alert to irAEs in liver cancer patients who have received ICI therapy.

Modeling multi-species RNA modification through multi-task curriculum learning.

N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological processes are regulated by this critical post-transcriptional mark, such as gene expression, RNA stability, RNA structure and translation. Recently, various experimental techniques and computational methods have been developed to characterize the transcriptome-wide landscapes of m6A modification for understanding its underlying mechanisms and functions in mRNA regulation. However, the experimental techniques are generally costly and time-consuming, while the existing computational models are usually designed only for m6A site prediction in a single-species and have significant limitations in accuracy, interpretability and generalizability. Here, we propose a highly interpretable computational framework, called MASS, based on a multi-task curriculum learning strategy to capture m6A features across multiple species simultaneously. Extensive computational experiments demonstrate the superior performances of MASS when compared to the state-of-the-art prediction methods. Furthermore, the contextual sequence features of m6A captured by MASS can be explained by the known critical binding motifs of the related RNA-binding proteins, which also help elucidate the similarity and difference among m6A features across species. In addition, based on the predicted m6A profiles, we further delineate the relationships between m6A and various properties of gene regulation, including gene expression, RNA stability, translation, RNA structure and histone modification. In summary, MASS may serve as a useful tool for characterizing m6A modification and studying its regulatory code. The source code of MASS can be downloaded from https://github.com/mlcb-thu/MASS.