Evaluation of the efficacy and safety of immunotherapy in sarcoma: a two-center study.

Background: Sarcoma is a highly heterogeneous malignancy with a poor prognosis. Although chemotherapy and targeted therapy have improved the prognosis to some extent, the efficacy remains unsatisfactory in some patients. The efficacy and safety of immunotherapy in sarcoma need further evaluation. Methods: We conducted a two-center study of sarcoma patients receiving PD-1 immunotherapy at Tianjin Medical University Cancer Institute and Hospital and Henan Provincial Cancer Hospital. The treatment regimens included PD-1 inhibitor monotherapy and combination therapy based on PD-1 inhibitors. The observed primary endpoints were median progression-free survival (mPFS) and median overall survival (mOS). Survival curves were compared using the Kaplan-Meier method. Results: A total of 43 patients were included from the two centers. The median follow-up time for all patients was 13 months (range, 1-48 months). In the group of 37 patients with advanced or unresectable sarcoma, the mPFS was 6 months (95%CI: 5-12 months), and the mOS was 16 months (95%CI: 10-28 months). The ORR was 10.8% (4/37), and the DCR was 18.9% (7/37). Subgroup analysis showed no significant differences in mPFS (p=0.11) and mOS (p=0.88) between patients with PD-L1 negative/positive expression. There were also no significant differences in mPFS (p=0.13) or mOS (p=0.72) between PD-1 inhibitor monotherapy and combination therapy. Additionally, there were no significant differences in mPFS (p=0.52) or mOS (p=0.49) between osteogenic sarcoma and soft tissue sarcoma. Furthermore, the results showed no significant differences in mPFS (p=0.66) or mOS (p=0.96) between PD-1 inhibitors combined with targeted therapy and PD-1 inhibitors combined with AI chemotherapy. Among the 6 patients receiving adjuvant therapy after surgery, the mPFS was 15 months (95%CI: 6-NA months), and the mOS was not reached. In terms of safety, most adverse events were mild (grade 1-2) and manageable. The most severe grade 4 adverse events were bone marrow suppression, which occurred in 4 patients but resolved after treatment. There was also one case of a grade 4 adverse event related to hypertension. Conclusion: Immunotherapy is an effective treatment modality for sarcoma with manageable safety. Further inclusion of more patients or prospective clinical trials is needed to validate these findings.

Tumoral C2 Regulates the Tumor Microenvironment by Increasing the Ratio of M1/M2 Macrophages and Tertiary Lymphoid Structures to Improve Prognosis in Melanoma.

Immunotherapy is an essential therapy for individuals with advanced melanoma. However, not all patients respond to such treatment due to individual differences. We conducted a multidimensional analysis using transcriptome data from our center, as well as publicly available databases. We found that effective nivolumab treatment led to an upregulation of C2 levels, and higher levels following treatment are indicative of a good outcome. Through bioinformatics analyses and immunofluorescence, we identified a correlation between C2 and M1 macrophages. To further investigate the role of C2 in melanoma, we constructed subcutaneous tumorigenic models in C57BL/6 mice. The tumors in the C2 overexpression group exhibited significantly smaller sizes. Flow cytometric analysis of the mouse tumors demonstrated enhanced recruitment of macrophages, particularly of the M1 subtype, in the overexpression group. Moreover, single-cell RNA sequencing analysis revealed that C2-positive tumor cells exhibited enhanced communication with immune cells. We co-cultured tumor cell supernatants with macrophages in vitro and observed the induction of M1 subtype polarization. In addition, we discovered a close correlation between C2 and tertiary lymphoid structures. C2 has been demonstrated to exert a protective effect, mediated by its ability to modulate the tumor microenvironment. C2 serves as a prognostic marker for melanoma and can be employed to monitor the efficacy of immunotherapy.

Landscape of enhancer disruption and functional screen in melanoma cells.

BACKGROUND: The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma. RESULTS: Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions. CONCLUSIONS: Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

Randomised Controlled Trial of Self-Affirmation Intervention on Students' Academic Performance: Promising Impacts on Students from Migrant Hukou Status.

Purpose: Drawing from the sociocultural-self model, this study aims to examine the influence of self-affirmation on the academic outcomes of lower-class migrant students, as well as the psychological mechanism underlying this phenomenon. Patients and Methods: A field experiment was conducted at a comprehensive secondary school in the southern region of China. Our study sample comprised 1534 immigrant students from diverse regions across the country, with an average proportion of 59.6% of students registered with a rural hukou. The hukou system plays a pivotal role in measuring social class in China, thus it was used as a proxy for lower and higher social class, with rural hukou students considered to be lower-class and urban hukou students considered to be higher-class. Prior to the English test, students in the self-affirmed group were engaged in a brief writing exercise that focused on their core values, whereas the control group wrote about a neutral topic. Results: The primary outcome of interest was the effect of self-affirmation on English test scores, whereas the secondary outcome was the students' survey stereotype threat. The results exhibit that self-affirmation more significantly improved the English test performance of lower-class students compared to higher-class students, and this positive effect was mediated by reducing stereotype threat. Conclusion: Our findings unravel the impact of self-affirmation on the academic performance of migrant students from different social classes and signify the mediating role of stereotype threat in this process. The present study extends previous findings to students from immigrant families in the Chinese cultural context, and these findings demonstrate that self-affirmation can constitute a promising intervention for stereotype threat and achievement gaps due to social class differences in immigrant family groups. Considering that this intervention takes only about 15 minutes of time, entails almost zero cost, does no harm, and that it focuses on disadvantaged immigrant students, it may provide valuable insights for educational policies to be implemented in a new type of migrant city such as Shenzhen.

Donor-derived CAR-T therapy improves the survival of relapsed B-ALL after allogeneic transplantation compared with donor lymphocyte infusion.

Chimeric antigen receptor (CAR)-T cell therapy revolutionized treatment for various hematologic malignances. However, limited studies were reported to compare the efficacy and safety of CAR-T and donor lymphocyte infusion (DLI) for patients with relapsed B-cell acute lymphoblastic leukemia (B-ALL) after hematopoietic stem cell transplantation (HSCT) comprehensively. We conducted a single-center, retrospective comparative study that consisted of 12 patients who were treated with DLI (control group) and 12 patients treated with donor-derived CD19 CAR-T cells (experimental group, 6 patients also received CD22 or CD123 CAR-T cells sequentially) with 3 overlaps. The event-free survival (EFS) of patients in experimental group was superior to that of the control group: 516 days versus 98 days (p = 0.0415). Compared with 7 of 12 patients treated with DLI suffered grades III-IV acute graft versus host disease (aGVHD), one grade III aGVHD developed in patients treated with CAR-T therapy. No significant difference in the incidence of infection was identified between these two groups. Most patients in the experimental group had only mild cytokine release syndrome and none developed neurotoxicity. The univariate analysis of patients in the experiment group revealed that earlier CAR-T therapy for post-transplantation relapse was associated with better EFS. There was no significant difference in EFS between patients treated with dual-target CAR-T with those with single CD19 CAR-T. In this study, our data supported that donor-derived CAR-T therapy is a safe and potentially effective treatment for relapsed B-ALL after HSCT and may be superior to DLI.

The value of machine learning based radiomics model in preoperative detection of perineural invasion in gastric cancer: a two-center study.

Purpose: To establish and validate a machine learning based radiomics model for detection of perineural invasion (PNI) in gastric cancer (GC). Methods: This retrospective study included a total of 955 patients with GC selected from two centers; they were separated into training (n=603), internal testing (n=259), and external testing (n=93) sets. Radiomic features were derived from three phases of contrast-enhanced computed tomography (CECT) scan images. Seven machine learning (ML) algorithms including least absolute shrinkage and selection operator (LASSO), naïve Bayes (NB), k-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), random forest (RF), eXtreme gradient boosting (XGBoost) and support vector machine (SVM) were trained for development of optimal radiomics signature. A combined model was constructed by aggregating the radiomic signatures and important clinicopathological characteristics. The predictive ability of the radiomic model was then assessed with receiver operating characteristic (ROC) and calibration curve analyses in all three sets. Results: The PNI rates for the training, internal testing, and external testing sets were 22.1, 22.8, and 36.6%, respectively. LASSO algorithm was selected for signature establishment. The radiomics signature, consisting of 8 robust features, revealed good discrimination accuracy for the PNI in all three sets (training set: AUC = 0.86; internal testing set: AUC = 0.82; external testing set: AUC = 0.78). The risk of PNI was significantly associated with higher radiomics scores. A combined model that integrated radiomics and T stage demonstrated enhanced accuracy and excellent calibration in all three sets (training set: AUC = 0.89; internal testing set: AUC = 0.84; external testing set: AUC = 0.82). Conclusion: The suggested radiomics model exhibited satisfactory prediction performance for the PNI in GC.

Distribution, source investigation, and risk assessment of topsoil heavy metals in areas with intensive anthropogenic activities using the positive matrix factorization (PMF) model coupled with self-organizing map (SOM).

Over the past decade, heavy metal (HMs) contamination in soil environments has become severe worldwide. However, their resulting ecological and health risks remained elusive across a variety of soil ecosystems due to the complicated distributions and sources. This study investigated the HMs (Cr, As, Cu, Pb, Zn, Ni, Cd, and Hg) in areas with multi-mineral resources and intensive agricultural activities to study their distribution and source apportionment using a positive matrix factorization (PMF) model coupled with self-organizing map (SOM). The potential ecological and health risks were assessed in terms of distinct sources of HMs. The results disclosed that the spatial distribution of HM contaminations in the topsoil was region-dependent, primarily located in areas with high population intensity. The geo­accumulation index (Igeo) and enrichment factor (EF) values collectively displayed that the topsoils were severely contaminated by Hg, Cu, and Pb, particularly in residential farmland areas. The comprehensive analysis combined with PMF and SOM identified both geogenic and anthropogenic sources of HMs including natural, agricultural, mining, and mixed sources (caused by multi-anthropogenic factors), accounting for 24.9%, 22.6%, 45.9%, and 6.6% contribution rates, respectively. The potential ecological risk was predominantly due to the enrichment of Hg, followed by Cd. The non-carcinogenic risks were mostly below the acceptable risk level, while the potential carcinogenic health risks caused by As and Cr should be paid prime attention to, particularly for children. In addition to the 40% geogenic sources, agricultural activities contributed to 30% of the non-carcinogenic risk, whereas mining activities contributed to nearly half of the carcinogenic health risks.

Generative pretraining from large-scale transcriptomes for single-cell deciphering.

Exponential accumulation of single-cell transcriptomes poses great challenge for efficient assimilation. Here, we present an approach entitled generative pretraining from transcriptomes (tGPT) for learning feature representation of transcriptomes. tGPT is conceptually simple in that it autoregressive models the ranking of a gene in the context of its preceding neighbors. We developed tGPT with 22.3 million single-cell transcriptomes and used four single-cell datasets to evalutate its performance on single-cell analysis tasks. In addition, we examine its applications on bulk tissues. The single-cell clusters and cell lineage trajectories derived from tGPT are highly aligned with known cell labels and states. The feature patterns of tumor bulk tissues learned by tGPT are associated with a wide range of genomic alteration events, prognosis, and treatment outcome of immunotherapy. tGPT represents a new analytical paradigm for integrating and deciphering massive amounts of transcriptome data and it will facilitate the interpretation and clinical translation of single-cell transcriptomes.

Efficacy of salvage therapies after failure of adjuvant anti-PD-1 monotherapy for melanoma in the Chinese population: a multi-institutional cohort study.

The majority of melanoma patients experience relapse during adjuvant therapy or after the end of therapy. Sixty-one patients from 3 melanoma centres who experienced recurrence and received adjuvant pembrolizumab for resected stage III/IV melanoma were enrolled. Disease characteristics, recurrence characteristics, subsequent management and outcomes were retrospectively analysed. Sixty-one patients were enrolled in this study. The median time to first relapse from the commencement of adjuvant pembrolizumab was 8 months (1-22 months). The first recurrences were locoregional alone in 25 patients (41%), distant alone in 29 (47.5%) and concurrent locoregional and distant relapse in 7 (11.5%). At the first recurrence, 4 patients (80%) who underwent resection alone experienced further relapse of disease. Three (60%) patients who were treated with adjuvant pembrolizumab following surgery, 2 (100%) patients who were treated with adjuvant chemotherapy, 2 (66.7%) patients who were treated with adjuvant chemotherapy and pembrolizumab combined and 3 (100%) patients who were treated with adjuvant radiotherapy and pembrolizumab combined had further recurrence. Of the three patients treated with adjuvant BRAF/MEKi following the first relapse, none had yet recurred. Of the 8 patients treated with pembrolizumab alone, only one patient (12.5%) who recurred after ceasing adjuvant PD1 had a partial response. The overall response rate to BRAF/MEKi was 75%, 3/4; to pembrolizumab in combination with an oral multitargeted receptor tyrosine kinase inhibitor, it was 22.2%, 2/9; to chemotherapeutic agents alone, it was 33.3%, 1/3; and to chemotherapeutic agents combined with pembrolizumab, it was 37.5%, 3/8. The patient treated with imatinib had progressive disease after 3 months of treatment. Of the 6 patients who received temozolomide combined with pembrolizumab, 3 (3/6, 50%) had a partial response. The median OS of the patients who relapsed locoregionally only was longer than that of the patients who relapsed distally at the first recurrence (35 months and 14 months, respectively; P < 0.01). The outcomes of the patients with disease recurrence during or after the completion of 1 year of adjuvant anti-PD1 therapy were poor despite multimodality treatment.

Clinicopathologic features, prognostic factors, and outcomes of visceral sarcomas: A retrospective 12-year single-center study.

Background: Visceral sarcomas are a rare form of soft tissue sarcoma. This study aimed to evaluate the survival and prognostic factors and effective treatments for visceral sarcomas. Methods: All patients with visceral sarcoma referred to our center between January 2010 and December 2021 were retrospectively analyzed. The Kaplan-Meier method and a log-rank test were used for survival analysis. Results: A total of 53 patients with visceral sarcoma were analyzed in this study with the median age at diagnosis of 57 (range, 24-77) years. Among them, 37 (69.8%) and 16 (30.2%) patients had localized and metastatic diseases at the initial presentation, respectively, and 44 patients underwent surgical resection. The median follow-up, event-free survival (EFS) and overall survival (OS) were 63.0 (range, 2-130), 42.0 months (95% confidence interval [CI] 10.879-73.121) and 45.0 months (95% CI 9.938-80.062), respectively. The 5-year EFS and OS rates were 44% and 46%, respectively. Univariate analysis of prognostic indicators illustrated that metastasis at presentation, surgery, surgical margin and the types of surgery were significantly associated with OS and EFS. In this study, combined chemotherapy or radiotherapy had no effects on EFS and OS. Conclusion: Primary visceral sarcoma is an uncommon and aggressive malignant tumor with a higher rate of local recurrence. In the largest cohort of visceral sarcomas in China to date, we identified metastases at presentation, surgery, surgical margin, and the types of surgery as independent predictors of survival. The combination of chemotherapy and radiotherapy did not affect survival.

A single-cell analysis reveals tumor heterogeneity and immune environment of acral melanoma.

Acral melanoma is a dismal subtype of melanoma occurring in glabrous acral skin, and has a higher incidence in East Asians. We perform single-cell RNA sequencing for 63,394 cells obtained from 5 acral and 3 cutaneous melanoma samples to investigate tumor heterogeneity and immune environment. We define 5 orthogonal functional cell clusters that are involved in TGF-beta signaling, Type I interferon, Wnt signaling, Cell cycle, and Cholesterol efflux signaling. Signatures of enriched TGF-beta, Type I interferon, and cholesterol efflux signaling are significantly associated with good prognosis of melanoma. Compared with cutaneous melanoma, acral melanoma samples have significantly severe immunosuppressive state including depletion of cytotoxic CD8+ T cells, enrichment of Treg cells, and exhausted CD8+ T cells. PD1 and TIM-3 have higher expression in the exhaustive CD8+ T cells of acral melanoma. Key findings are verified in two independent validation sets. This study contributes to our better understanding of acral melanoma.

A novel inflammatory signature for evaluating immune microenvironment status in soft tissue sarcoma.

Background: Tumorigenesis and progression are intimately associated with inflammation. However, the inflammatory landscape in soft tissue sarcoma (STS) and its clinical consequences are yet unknown, and more investigation is needed. Methods: RNA-seq expression data for STS and corresponding normal tissues were downloaded from The Cancer Genome Atlas database and the Genotype-Tissue Expression Portal. Differential and prognostic analyses were performed based on known inflammatory response genes from Gene Set Enrichment Analysis (GSEA). We utilized LASSO-Cox analysis to determine hub genes and built an inflammatory score (INFscore) and risk stratification model. Furthermore, a nomogram, including the risk stratification model, was established to predict the prognosis. We further elucidated the characteristics among different risk STS patients by GSEA, gene set variation analysis, and detailed immune infiltration analysis. Finally, the INFscore and risk stratification model in predicting prognosis and depicting immune microenvironment status were verified by pan-cancer analysis. Results: Five hub genes (HAS2, IL1R1, NMI, SERPINE1, and TACR1) were identified and were used to develop the INFscore. The risk stratification model distinguished the immune microenvironment status and evaluated the efficacy of immunotherapy and chemotherapy in STS. The novel nomogram had good efficacy in predicting the prognosis of STS patients. Finally, a pan-cancer investigation verified the association of INFscore with prognosis and immunity. Conclusions: According to the present study, the risk stratification model can be used to evaluate STS prognosis, tumor microenvironment status, immunotherapy, and chemotherapy efficacy. The novel nomogram has an excellent predictive value. Thus, the INFscore and risk stratification model has potential value in assessing the prognosis and immune status of multiple malignancies.

Pan-Soft Tissue Sarcoma Analysis of the Incidence, Survival, and Metastasis: A Population-Based Study Focusing on Distant Metastasis and Lymph Node Metastasis.

Background: The rarity and complexity of soft tissue sarcoma (STS) make it a challenge to determine the incidence, survival, and metastasis rates. In addition, the clinicopathological risk factors for lymph node metastasis have rarely been reported. Methods: Data on patients diagnosed with STS in the SEER database from 2000 to 2018 were extracted by SEER*Stat 8.3.9.1, and the incidence trend was calculated by Joinpoint 4.9 software. The KM method was used to calculate the survival curve, and the log-rank method was used to compare differences in the survival curves. The clinicopathological risk factors for lymph node metastasis were screened by logistic regression. Results: Among the 35987 patients, 4299 patients (11.9%) had distant metastasis. The overall lymph node metastasis rate was 6.02%, which included patients suffering from both lymph node and distant metastasis. Considering that some lymph node metastases might be accompanying events of distant metastasis, the rate of only lymph node metastasis in STS patients decreased to 3.42% after excluding patients with distant metastasis. Patients with only lymph node metastases (N1/2M0) had a significantly worse prognosis than those without metastases (N0M0) but a better prognosis than those with only distant metastases (N0M1) (p<0.0001). In the multivariate logistic analysis, STS patients with larger tumors located in the head and neck, viscera, retroperitoneum, and certain specific pathological subtypes (compared with the liposarcoma), such as undifferentiated pleomorphic sarcoma, rhabdomyosarcoma, endometrial stromal sarcoma, gastrointestinal stromal tumor, synovial sarcoma, and angiosarcoma, had a higher risk of lymph node metastasis. Conclusions: Lymph node metastasis is rare in STS, and the metastasis rate is significantly different among the different pathological types. Tumor size, location, and pathological subtype are significantly associated with the risk of lymph node metastasis. The overall survival of patients with lymph node metastasis is better than that of patients with distant metastasis, which suggests a more precise prognosis evaluation should be performed in these AJCC stage IV STS patients.

Identification of significant genes with a poor prognosis in skin cutaneous malignant melanoma based on a bioinformatics analysis.

Background: Skin cutaneous malignant melanoma (SKCM) is a deadly mutated malignancy that arises from melanocytes in the basal layer of the skin. This study sought to identify effective treatment targets that could serve as prospective therapeutic targets to improve patient outcomes. Methods: The GSE83583, GSE111766, and GSE104849 data sets from the GPL10558 platform in the Gene Expression Omnibus (GEO) were used in this study. The candidate genes were identified using the GEO2R tool and a Venn diagram. The Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Gene and Genome (KEGG) preliminary analyses of the differentially expressed genes (DEGs) were conducted using the Database for Annotation, Visualization and Integrated Discovery, and R software. The protein-protein interaction (PPI) network was examined using Cytoscape software. The survminer package was used to examine the overall survival of patients with the identified genes. The Human Protein Atlas (HPA) was used to verify the protein levels of significant genes with poor prognosis. The highly expressed genes in the melanoma tissues were visualized using the ggplot2 package. Results: In total, 160 DEGs from 124 melanoma tissues and 9 normal melanocyte tissues were examined in this study. Cytoscape displayed 19 central nodes from the 160 DEGs. The re-analysis showed that the cytochrome P450 family 1 subfamily B member 1 (CYP1B1) and protein kinase C beta (PRKCB) were significantly enriched in the micro ribonucleic acids (RNAs) in cancer. Conclusions: CYP1B1 and PRKCB were overexpressed in and correlated with the poor prognosis of SKCM. Our findings might help explore the prognosis and diagnostic markers of SKCM.

An electrochemical biosensor for the assessment of tumor immunotherapy based on the detection of immune checkpoint protein programmed death ligand-1.

Although immunotherapy is now well established in cancer management, not every patient responds. Existing methods for assessing tumor immunotherapy responses, such as immunohistochemistry of the immune checkpoint protein programmed death ligand-1 (PD-L1), require destructive tissue analysis; furthermore, real-time in vivo monitoring would be beneficial for assessing tumor responses. Here we establish an electrochemical biosensor which was developed based on molybdenum disulfide (MoS2) and multi-wall carbon nanotubes (MWCNTs) used to modify the electrode and PD-L1 antibody-quantum dot (QD) conjugate as a dual optical and electrochemical label. The compositions, electrochemical performance, specificity of nanocomposite and probe were characterized. Paving the way for clinical application, the prepared biosensor detects differences in PD-L1 levels in diverse tumor cell types, tumors derived from mice or cancer patients, and it is reproducible and selective in both phosphate-buffered saline and serum. This study demonstrates that electrochemical sensing is a desirable technology for the in-situ and dynamic determination of biomarkers on the cellular level of for the assessment of tumor immunotherapy.

m6A regulator-mediated methylation modification patterns and tumor immune microenvironment in sarcoma.

BACKGROUND: Studies have shown that the RNA N6-methyladenosine (m6A) modification patterns are extensively involved in the development of multiple tumors. However, the association between the m6A regulator expression patterns and the sarcoma tumor immune microenvironment (TIME) remains unclear. METHODS: We systematically evaluated the m6A regulator expression patterns in patients with sarcoma based on known 23 m6A regulators. Different m6A regulator expression patterns were analyzed using gene set variation analysis and a single-sample gene set enrichment analysis algorithm. According to the results of consensus clustering, we classified the patients into four different clusters. Next, we subjected the four clusters to differential genetic analysis and established m6A-related differentially expressed genes (DEGs). We then calculated the m6A-related DEGs score and constructed the m6A-related gene signature, named m6A score. Finally, the 259 sarcoma samples were divided into high- and low-m6A score groups. We further evaluated the TIME landscape between the high- and low-m6A score groups. RESULTS: We identified four different m6A modification clusters and found that each cluster had unique metabolic and immunological characteristics. Based on the 19 prognosis-related DEGs, we calculated the principal component analysis scores for each patient with sarcoma and classified them into high- and low-m6A score groups. CONCLUSIONS: The m6A regulator expression patterns and complexity of the sarcoma TIME landscape are closely related to each other. Systematic evaluation of m6A regulator expression patterns and m6A scores in patients with sarcoma will enhance our understanding of TIME characteristics.

Understanding China's changing engagement in global climate governance: a struggle for identity.

This article offers a novel understanding of China's changing engagement in global climate governance over the past decade. This article argues that China has embedded the construction of its international identity, which has been transforming towards what this article conceptualizes to be a 'Yinling leading power', in promoting and leading global climate governance. China's transforming identity construction has contributed to changing its construction of climate justice and led China to proactively undertake more responsibilities, provide international public goods and promote international climate cooperation. Global climate governance has become one of China's prototypical discursive frames in constructing its new international identity, an important platform where China seeks to share leadership with other major powers and the climate leadership in turn constitutes China's new identity. However, China's inadequate response to international expectations and lack of self-reflection in its climate policy have influenced international recognition on its climate leadership and new identity. In general, China's transforming identity construction and its reconstruction of climate justice have far-reaching implications for China and Europe to cooperate and coordinate in strengthening global climate justice and promoting global climate governance.