N6-Methyladenosine-Related LncRNAs Are Potential Remodeling Indicators in the Tumor Microenvironment and Prognostic Markers in Osteosarcoma

Exploring gene biomarkers and targeted drugs for ferroptosis and cuproptosis in osteosarcoma: A bioinformatic approach

Osteosarcoma predominantly affects adolescents and young adults and is characterized as a malignant bone tumor. In recent decades, substantial advancements have been achieved in both diagnosing and treating osteosarcoma. Resulting in enhanced survival rates. Despite these advancements, the intricate relationship between ferroptosis and cuproptosis genes in osteosarcoma remains inadequately understood. Leveraging TARGET and GEO datasets, we conducted Cox regression analysis to select prognostic genes from a cohort of 71 candidates. Subsequently, a novel prognostic model was engineered using the LASSO algorithm. Kaplan-Meier analysis demonstrated that patients stratified as low risk had a substantially better prognosis compared with their high-risk counterparts. The model's validity was corroborated by the area under the receiver operating characteristic (ROC) curve. Additionally, we ascertained independent prognostic indicators, including clinical presentation, metastatic status, and risk scores, and crafted a clinical scoring system via nomograms. The tumor immune microenvironment was appraised through ESTIMATE, CIBERSORT, and single-sample gene set enrichment analysis. Gene expression within the model was authenticated through PCR validation. The prognostic model, refined by Cox regression and the LASSO algorithm, comprised two risk genes. Kaplan-Meier curves confirmed a significantly improved prognosis for the low-risk group in contrast to those identified as high-risk. For the training set, the ROC area under the curve (AUC) values stood at 0.636, 0.695, and 0.729 for the 1-, 3-, and 5-year checkpoints, respectively. Although validation set AUCs were 0.738, 0.668, and 0.596, respectively. Immune microenvironmental analysis indicated potential immune deficiencies in high-risk patients. Additionally, sensitivity to three small molecule drugs was investigated in the high-risk cohort, informing potential immunotherapeutic strategies for osteosarcoma. PCR analysis showed increased mRNA levels of the genes FDX1 and SQLE in osteosarcoma tissues. This study elucidates the interaction of ferroptosis and cuproptosis genes in osteosarcoma and paves the way for more targeted immunotherapy.

Integrated analysis of single-cell and bulk transcriptomics reveals cellular subtypes and molecular features associated with osteosarcoma prognosis

BACKGROUND

Osteosarcoma (OS) is the most common primary bone malignancy with variable molecular biology and prognosis. However, our understanding of the association between cell types and OS progression remains poor.

METHODS

We generated a human OS cell atlas by integrating over 110,000 single cells from 17 samples. Multiple machine learning algorithms were applied to develop tumor purity prediction models based on transcriptomic profile of OS. The Scissor algorithm and gene enrichment analyses were conducted to delve into cell-intrinsic molecular characteristics linked to OS prognosis. Moreover, the study investigated the impact of ATF6α in OS aggressiveness through genetic and pharmacological loss of function analyses. Lastly, the CellChat algorithm was employed to investigate cell-cell communications.

RESULTS

Utilizing the high-quality human OS cell atlas, we identified tumor purity as a prognostic indicator and developed a robust tumor purity prediction model. We respectively delineated cancer cell- and immune cell-intrinsic molecular characteristics associated with OS prognosis at single-cell resolution. Interestingly, tumor cells with activated unfolded protein response (UPR) pathway were significantly associated with disease aggressiveness. Notably, ATF6α emerged as the top-activated transcription factor for this tumor subcluster. Subsequently, we confirmed that ATF6α was markedly associated with OS progression, while both genetic and pharmacological inhibition of ATF6α impaired the survival of HOS cells. Lastly, we depicted the landscape of signal crosstalk between the UPR-related subcluster and other cell types within the tumor microenvironment.

CONCLUSION

In summary, our work provides novel insights into the molecular biology of OS, and offers valuable resource for OS biomarker discovery and treatment strategy development.

Immunotherapy of osteosarcoma based on immune microenvironment modulation

Osteosarcoma is a highly malignant tumor with unsatisfactory therapeutic outcomes achieved by chemotherapy, radiotherapy, and surgery. As an emerging oncological treatment, immunotherapy has shown potential in the clinical management of many tumors but has a poor response rate in osteosarcoma. The immunosuppressive microenvironment in osteosarcoma is the main reason for the ineffectiveness of immunotherapy, in which the low immune response rate of immune effector cells and the high activation of immunosuppressive cells contribute to this outcome. Therefore, modulating the function of the immune microenvironment in osteosarcoma is expected to remodel the immunosuppressive microenvironment of osteosarcoma and enhance the efficacy of immunotherapy. This article reviews the role of immune cells in the progression of osteosarcoma, describes the corresponding regulatory tools for the characteristics of different cells to enhance the efficacy of osteosarcoma immunotherapy, and concludes the prospects and future challenges of osteosarcoma immunotherapy.

T cell receptor signaling pathway subgroups and construction of a novel prognostic model in osteosarcoma

Background

T cell receptor (TCR) signaling pathway is closely related to tumor progress and immunotherapy. This study aimed to explore the clinical significance, prognosis, immune infiltration and chemotherapy sensitivity of TCR in osteosarcoma (OS).

Material and methods

OS data were obtained from TARGET and GEO database. TCR signaling pathway-related genes (TCRGs) were extracted from Molecular Signatures Database. Unsupervised non-negative matrix factorization clustering analysis was used to identify OS molecular subtypes. Differential expressed TCRGs between molecular subtypes were screened with univariate Cox regression, LASSO regression and multivariate Cox regression. Subsequently, an OS-associated prognostic model was constructed and validated. Nomogram was established and verified. Immune landscape analysis including immune infiltration analysis, ESTIMATE algorithm and immune checkpoints expression levels of molecular subtypes and different risk groups were analyzed. Finally, chemotherapy sensitivity and potential therapeutic agents between different risk groups was identified.

Results

Two TCRGs related subclusters were identified. Two hundred and seventy-two Differential expressed TCRGs were screened between two subclusters. A robust prognostic model were constructed. High and low risk groups were stratified. Low risk group showed higher ESTIMATE, immune and stromal scores, while high risk group exhibited higher tumor purity and the lower expression levels of immune checkpoints. A nomogram comprising metastasis and risk score was successfully built. The sensitivity to chemotherapy agents were different across high and low risk groups.

Conclusions

Our study proposed TCR related molecular subtypes and provided a prognostic model for OS. Our findings may bring a new insight into the immunotherapy for OS patients.

m6A methylation modification: Potential pathways to suppress osteosarcoma metastasis

Osteosarcoma is a highly aggressive malignant bone tumor prone to metastasis, and its metastatic process is one of the main reasons for treatment failure and poor prognosis. Recent studies have demonstrated that modification of m6A methylation plays an important role in osteosarcoma metastasis, influencing both invasion and metastasis through various signaling pathways. Therefore, clarification of the specific effects of m6A methylation modification in osteosarcoma may reveal ways to improve the prognosis of osteosarcoma patients. The roles of various components involved in the m6A methylation modification process in osteosarcoma have been investigated, with studies focusing more on their effects than on their mechanisms. In this review, we focus on the interactions between the "writers," "erasers," and "readers" of m6A methylation and tumor metastasis-related factors to enhance the understanding of osteosarcoma and m6A methylation modification, with the aim of identifying clinical diagnostic biomarkers and potential therapeutic targets for osteosarcoma metastasis.

Unlocking the tumor-immune microenvironment in osteosarcoma: insights into the immune landscape and mechanisms

Osteosarcoma has a unique tumor microenvironment (TME), which is characterized as a complex microenvironment comprising of bone cells, immune cells, stromal cells, and heterogeneous vascular structures. These elements are intricately embedded in a mineralized extracellular matrix, setting it apart from other primary TMEs. In a state of normal physiological function, these cell types collaborate in a coordinated manner to maintain the homeostasis of the bone and hematopoietic systems. However, in the pathological condition, i.e., neoplastic malignancies, the tumor-immune microenvironment (TIME) has been shown to promote cancer cells proliferation, migration, apoptosis and drug resistance, as well as immune escape. The intricate and dynamic system of the TIME in osteosarcoma involves crucial roles played by various infiltrating cells, the complement system, and exosomes. This complexity is closely associated with tumor cells evading immune surveillance, experiencing uncontrolled proliferation, and facilitating metastasis. In this review, we elucidate the intricate interplay between diverse cell populations in the osteosarcoma TIME, each contributing uniquely to tumor progression. From chondroblastic and osteoblastic osteosarcoma cells to osteoclasts, stromal cells, and various myeloid and lymphoid cell subsets, the comprehensive single-cell analysis provides a detailed roadmap of the complex osteosarcoma ecosystem. Furthermore, we summarize the mutations, epigenetic mechanisms, and extracellular vesicles that dictate the immunologic landscape and modulate the TIME of osteosarcoma. The perspectives of the clinical implementation of immunotherapy and therapeutic approaches for targeting immune cells are also intensively discussed.

The Role of m6A Methylation in Tumor Immunity and Immune-Associated Disorder

N6-methyladenosine (m6A) represents the most prevalent and significant internal modification in mRNA, with its critical role in gene expression regulation and cell fate determination increasingly recognized in recent research. The immune system, essential for defense against infections and maintaining internal stability through interactions with other bodily systems, is significantly influenced by m6A modification. This modification acts as a key post-transcriptional regulator of immune responses, though its effects on different immune cells vary across diseases. This review delineates the impact of m6A modification across major system-related cancers-including those of the respiratory, digestive, endocrine, nervous, urinary reproductive, musculoskeletal system malignancies, as well as acute myeloid leukemia and autoimmune diseases. We explore the pathogenic roles of m6A RNA modifications within the tumor immune microenvironment and the broader immune system, highlighting how RNA modification regulators interact with immune pathways during disease progression. Furthermore, we discuss how the expression patterns of these regulators can influence disease susceptibility to immunotherapy, facilitating the development of diagnostic and prognostic models and pioneering new therapeutic approaches. Overall, this review emphasizes the challenges and prospective directions of m6A-related immune regulation in various systemic diseases throughout the body.

Exploring the Role of Neutrophil-Related Genes in Osteosarcoma via an Integrative Analysis of Single-Cell and Bulk Transcriptome

BACKGROUND

The involvement of neutrophil-related genes (NRGs) in patients with osteosarcoma (OS) has not been adequately explored. In this study, we aimed to examine the association between NRGs and the prognosis as well as the tumor microenvironment of OS.

METHODS

The OS data were obtained from the TARGET-OS and GEO database. Initially, we extracted NRGs by intersecting 538 NRGs from single-cell RNA sequencing (scRNA-seq) data between aneuploid and diploid groups, as well as 161 up-regulated differentially expressed genes (DEGs) from the TARGET-OS datasets. Subsequently, we conducted Least Absolute Shrinkage and Selection Operator (Lasso) analyses to identify the hub genes for constructing the NRG-score and NRG-signature. To assess the prognostic value of the NRG signatures in OS, we performed Kaplan-Meier analysis and generated time-dependent receiver operating characteristic (ROC) curves. Gene enrichment analysis (GSEA) and gene set variation analysis (GSVA) were utilized to ascertain the presence of tumor immune microenvironments (TIMEs) and immunomodulators (IMs). Additionally, the KEGG neutrophil signaling pathway was evaluated using ssGSEA. Subsequently, PCR and IHC were conducted to validate the expression of hub genes and transcription factors (TFs) in K7M2-induced OS mice.

RESULTS

FCER1G and C3AR1 have been identified as prognostic biomarkers for overall survival. The findings indicate a significantly improved prognosis for OS patients. The effectiveness and precision of the NRG signature in prognosticating OS patients were validated through survival ROC curves and an external validation dataset. The results clearly demonstrate that patients with elevated NRG scores exhibit decreased levels of immunomodulators, stromal score, immune score, ESTIMATE score, and infiltrating immune cell populations. Furthermore, our findings substantiate the potential role of SPI1 as a transcription factor in the regulation of the two central genes involved in osteosarcoma development. Moreover, our analysis unveiled a significant correlation and activation of the KEGG neutrophil signaling pathway with FCER1G and C3AR1. Notably, PCR and IHC demonstrated a significantly higher expression of C3AR1, FCER1G, and SPI1 in Balb/c mice induced with K7M2.

CONCLUSIONS

Our research emphasizes the significant contribution of neutrophils within the TIME of osteosarcoma. The newly developed NRG signature could serve as a good instrument for evaluating the prognosis and therapeutic approach for OS.

High-dimensional deconstruction of ovarian cancer at single-cell precision reveals HEBP2 that reshape the TIME and drive carboplatin resistance

BACKGROUND

Single-cell sequencing was employed to analyze the tumor immune microenvironment in ovarian cancer (OC) patients, exploring the evolutionary roles of various macrophage subgroups in OC progression and their correlation with fatty acid metabolism-related genes in contributing to drug resistance.

METHODS

This study aimed to decipher the mechanisms underlying OC chemoresistance (OC-CR) and carboplatin resistance by integrating and analyzing multiple single-cell RNA sequencing datasets from OC patients. The tumor immune microenvironment in OC-CR patients exhibited notable alterations in cellular interactions and the proportions of different immune cell populations, in contrast to the cohort sensitive to OC chemotherapy.

RESULTS

The study demonstrates that the fatty acid-associated gene HEBP2 not only accelerates OC progression but also modifies the immune landscape of OC, driving the polarization from M0_TAM to M2_TAM. This shift results in a diminished efficacy of chemotherapy in OC. Furthermore, both in vitro and in vivo experiments underscored HEBP2's role in boosting the proliferation of OC-resistant cell lines and suppressing apoptosis, thereby facilitating carboplatin resistance.

CONCLUSION

In conclusion, the immune microenvironments of OC-CR significantly differ from those sensitive to chemotherapy, underscoring HEBP2's role in fostering OC resistance. This establishes HEBP2 as a promising prognostic marker and a novel target for therapeutic strategies against OC resistance.

Research trends and hotspots in the immune microenvironment related to osteosarcoma and tumor cell aging: a bibliometric and visualization study

Background

It is well known that cancers have a common feature that even if the environment is extremely poor in nutrients, they can still make good use of them to maintain viability as well as to produce new biomass, which is one of the reasons why tumor cells are powerfully less susceptible to senescence and death. The microenvironment has a profound impact on the senescence as well as the growth and development of tumor cells, and it is also the focus of scientists' research because it may even affect the discovery of the treatment and pathogenesis of cancer. And so the study of the microenvironment in the tumor cells is of great significance to the analysis of the tumor cells as well as to the impact of their senescence. Similarly, the microenvironment of osteosarcoma is also crucial for its impact, but to our knowledge, there is no bibliometric study that systematically analyzes and describes the trends and future hotspots in this field of research as we do, and we are going to fill this gap in this study.

Methods

We searched the Web Science Core Collection 2010-2023 in WOS on August 1, 2023. Based on the criteria needed for the search, we retained articles that matched the topic, excluded studies other than articles and reviews, and selected only studies whose language was English. We performed an intuitive visualization and bibliometric approach to analyze the research content in this field and a systematic visualization of global trends and hotspots in the research of osteosarcoma and the microenvironment, for which we used multiple specialized For this purpose, we used several specialized software packages, such as VOSviewer and the Bibliometrix package for R software. Because research in this area of osteosarcoma and the microenvironment has begun to gain popularity in the last 10 years or so, and is a very novel piece of research, there were almost no studies in this area prior to 2010 and they were not very informative, and in the end, we chose to look at studies from after 2010.

Results

Based on the criteria needed for the search, resulting in a final selection of 821 articles. In the research area related to osteosarcoma and microenvironment, we found that China in Asia and the United States in North America and Italy in Europe were the three countries or regions with the highest number of published articles. In addition, the institution that published the most research in this area was Shanghai Jiao Tong University. In terms of publications in the field of osteosarcoma and microenvironmental research, Baldini, Heymann, and Avnet are among the top 3 authors. The terms "cancer", "cells" and "expression" are found to be more commonly employed.

Conclusion

Using a variety of highly specialized software, we have undertaken a visual and bibliometric study of the current state of research and potential future hotspots in the field of osteosarcoma and microenvironment research. The microenvironment has a profound impact on the senescence and growth and development of cells in tumors, including osteosarcoma, and may even influence the discovery of cancer treatment and pathogenesis, and is also a hotspot and focus that scientists have begun to gradually study in recent years. This analysis and visualization will help guide future research in the field.

Novel chemokine related LncRNA signature correlates with the prognosis, immune landscape, and therapeutic sensitivity of esophageal squamous cell cancer

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is closely correlated with malignant biological characteristics and poor survival. Recently, chemokines have been reported to be involved in the progression of tumors, and they can also regulate the tumor microenvironment. However, it is unclear whether chemokine-related long noncoding RNAs (lncRNAs) affect the prognosis of ESCC.

METHODS

We downloaded RNA-seq and clinical data from the Gene Expression Omnibus (GEO database. Chemokine-related lncRNAs were screened by differential analysis and Pearson correlation analysis. Then, prognosis-related lncRNAs were screened by using univariate COX regression, and risk models were constructed after the least absolute shrinkage and selection operator (LASSO) regression and multivariate COX regression. The predictive value of the signature was assessed using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves, decision curve analysis (DCA) and calibration curve. Moreover, a nomogram to predict patients' 1-year 3-year and 5-year prognosis was constructed. Gene set enrichment analyses (GSEA), Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG), evaluation of immune cell infiltration, and estimation of drug sensitivity were also conducted.

RESULTS

In this study, 677 chemokine-related lncRNAs were first obtained by differential analysis and Pearson correlation. Then, six chemokine-related lncRNAs were obtained by using univariate COX, LASSO and multivariate COX to construct a novel chemokine-related lncRNAs risk model. The signature manifested favorable predictive validity and accuracy both in the testing and training cohorts. The chemokine-related signature could classify ESCC patients into two risk groups well, which indicated that high-risk group exhibited poor prognostic outcome. In addition, this risk model played an important role in predicting signaling pathways, immune cell infiltration, stromal score, and drug sensitivity in ESCC patients.

CONCLUSIONS

These findings elucidated the critical role of novel prognostic chemokine-related lncRNAs in prognosis, immune landscape, and drug therapy, thus throwing light on prognostic evaluation and therapeutic targets for ESCC patients.

Novel insights into the multifaceted roles of m6A-modified LncRNAs in cancers: biological functions and therapeutic applications

N6-methyladenosine (m⁶A) is considered as the most common and important internal transcript modification in several diseases like type 2 diabetes, schizophrenia and especially cancer. As a main target of m⁶A methylation, long non-coding RNAs (lncRNAs) have been proved to regulate cellular processes at various levels, including epigenetic modification, transcriptional, post-transcriptional, translational and post-translational regulation. Recently, accumulating evidence suggests that m⁶A-modified lncRNAs greatly participate in the tumorigenesis of cancers. In this review, we systematically summarized the biogenesis of m⁶A-modified lncRNAs and the identified m⁶A-lncRNAs in a variety of cancers, as well as their potential diagnostic and therapeutic applications as biomarkers and therapeutic targets, hoping to shed light on the novel strategies for cancer treatment.

Immune cells regulate matrix metalloproteinases to reshape the tumor microenvironment to affect the invasion, migration, and metastasis of pancreatic cancer

This study aimed to identify author, country, institutional, and journal collaborations and assess their impact, along with knowledge base, as well as identify existing trends, and uncover emerging topics related to matrix metalloproteinase and pancreatic-cancer research. A total of 1474 Articles and reviews were obtained from the Web of Science Core Collection and analyzed by Citespace and Vosviewer. CANCER RESEARCH, CLINICAL CANCER RESEARCH, and FRONTIERS IN IMMUNOLOGY are the most influential journals. The three main aspects of research in matrix metalloproteinases-pancreatic cancer-related fields included the pathogenesis mechanism of pancreatic cancer, how matrix metalloproteinases affect the metastasis of pancreatic cancer, and what role matrix metalloproteinases play in pancreatic cancer treatment. Tumor microenvironment, pancreatic stellate cells, drug resistance, and immune cells have recently emerged as research hot spots. In the future, exploring how immune cells affect matrix metalloproteinases and reshape the tumor microenvironment may be the key to curing pancreatic cancer. This study thus offers a comprehensive overview of the matrix metalloproteinases-pancreatic cancer-related field using bibliometrics and visual methods, providing a valuable reference for researchers interested in matrix metalloproteinases-pancreatic cancer.

Advanced nanoparticles that can target therapy and reverse drug resistance may be the dawn of leukemia treatment: A bibliometrics study

With the development of nanomedicine, more and more nanoparticles are used in the diagnosis and treatment of leukemia. This study aimed to identify author, country, institutional, and journal collaborations and their impacts, assess the knowledge base, identify existing trends, and uncover emerging topics related to leukemia research. 1825 Articles and reviews were obtained from the WoSCC and analyzed by Citespace and Vosviewer. INTERNATIONAL JOURNAL OF NANOMEDICINE is the journal with the highest output. The contribution of FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY is also noteworthy. The three main aspects of research in Nanoparticles-leukemia-related fields included nanoparticles for the diagnosis and treatment of leukemia, related to the type and treatment of leukemia, the specific molecular mechanism, and existing problems of the application of nanoparticles in leukemia. In the future, synthesize nano-drugs that have targeted therapy and chemotherapy resistance according to the mechanism, which may be the dawn of the solution to leukemia. This study offers a comprehensive overview of the Nanoparticles-leukemia-related field using bibliometrics and visual methods for the first time, providing a valuable reference for researchers interested in Nanoparticles-leukemia.

Identification of m6A-related long non-coding RNAs for predicting prognosis and immune characterizations in gastric cancer

Background: N6-methyladenosine (m⁶A) mRNA modification triggers malignant behavior in tumor cells, which promotes malignant progression and migration of gastric cancer (GC). Nevertheless, studies on the prognostic value of m⁶A-related long non-coding RNA (MRlncRNA) in GC remain quite restricted. The study aimed to develop a reasonable predictive model to explore the prognostic potential of MRlncRNAs in predicting the prognosis of GC patients and monitoring the efficacy of immunotherapy.

Methods: Transcriptomic and clinical data for GC were derived from TCGA. Next, univariate Cox, LASSO and multivariate Cox regression analyses were next used to identify prognostic MRlncRNAs, calculate risk scores and build risk assessment models. The predictive power of the risk models was then validated by Kaplan-Meier analysis, ROC curves, DCA, C-index, and nomogram. We attempted to effectively differentiate between groups in terms of immune cell infiltration status, ICI-related genes, immunotherapy responses, and common anti-tumor drug sensitivity.

Results: A risk model based on 11 MRlncRNAs was developed with an AUC of 0.850, and the sensitivity and specificity of this model in predicting survival probability is satisfactory. The Kaplan-Meier analysis revealed that the low-risk group in the model had a significantly higher survival rate, and the model was highly associated with survival status, clinical features, and clinical stage. Furthermore, the model was verified to be an independent prognostic risk factor, and the low-risk group in the model had a remarkable positive correlation with a variety of immune cell infiltrates. The expression levels of ICI-related genes differed significantly between the different groups. Lastly, immunotherapy responses and common anti-tumor drug sensitivity also differed significantly between different groups.

Conclusion: The risk model on the basis of 11-MRlncRNAs can serve as independent predictors of GC prognosis and may be useful in developing personalized treatment strategies for patients.

Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma

Background

Despite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel.

Methods

Single cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel.

Results

The malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel.

Conclusions

Overall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.

The hypoxia-related signature predicts prognosis, pyroptosis and drug sensitivity of osteosarcoma

Osteosarcoma (OS) is one of the most common types of solid sarcoma with a poor prognosis. Solid tumors are often exposed to hypoxic conditions, while hypoxia is regarded as a driving force in tumor recurrence, metastasis, progression, low chemosensitivity and poor prognosis. Pytoptosis is a gasdermin-mediated inflammatory cell death that plays an essential role in host defense against tumorigenesis. However, few studies have reported relationships among hypoxia, pyroptosis, tumor immune microenvironment, chemosensitivity, and prognosis in OS. In this study, gene and clinical data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases were merged to develop a hypoxia risk model comprising four genes (PDK1, LOX, DCN, and HMOX1). The high hypoxia risk group had a poor prognosis and immunosuppressive status. Meanwhile, the infiltration of CD8+ T cells, activated memory CD4+ T cells, and related chemokines and genes were associated with clinical survival outcomes or chemosensitivity, the possible crucial driving forces of the OS hypoxia immune microenvironment that affect the development of pyroptosis. We established a pyroptosis risk model based on 14 pyroptosis-related genes to independently predict not only the prognosis but also the chemotherapy sensitivities. By exploring the various connections between the hypoxic immune microenvironment and pyroptosis, this study indicates that hypoxia could influence tumor immune microenvironment (TIM) remodeling and promote pyroptosis leading to poor prognosis and low chemosensitivity.

CEMIP Promotes Osteosarcoma Progression and Metastasis Through Activating Notch Signaling Pathway

Cell migration inducing protein (CEMIP) has been linked to carcinogenesis in several types of cancers. However, the role and mechanism of CEMIP in osteosarcoma remain unclear. This study investigated the role of CEMIP in the progression and metastasis of osteosarcoma, CEMIP was found to be overexpressed in osteosarcoma tissues when compared to adjacent non-tumor tissues, and its expression was positively associated with a poor prognosis in osteosarcoma patients. Silencing CEMIP decreased osteosarcoma cells proliferation, migration, and invasion, but enhanced apoptosis in vitro, and suppressed tumor growth and metastasis in vivo. Mechanistically, CEMIP promoted osteosarcoma cells growth and metastasis through activating Notch signaling pathway, silencing CEMIP would reduce the protein expression and activation of Notch/Jagged1/Hes1 signaling pathway in vitro and in vivo, activation of Notch signaling pathway could partially reversed cell proliferation and migration in shCEMIP osteosarcoma cells. In conclusion, our study demonstrated that CEMIP plays a substantial role in the progression of osteosarcoma via Notch signaling pathway, providing a promising therapeutic target in osteosarcoma.

An inflammatory response-related gene signature associated with immune status and prognosis of acute myeloid leukemia

OBJECTIVE

To determine the prognostic significance of inflammatory response-associated genes in acute myeloid leukemia (AML).

METHODS

Transcriptomic profiles and related clinical information of AML patients were acquired from a public database. To establish a multi-gene prognosis signature, we performed least absolute shrinkage and selection operator Cox analysis for the TCGA cohort and evaluated the ICGC cohort for verification. Subsequently, Kaplan-Meier analysis was carried out to compare the overall survival (OS) rates between high- and low-risk groups. Biological function and single-sample gene set enrichment (ssGSEA) analyses were employed to investigate the association of risk score with immune status and the tumor microenvironment. Prognostic gene expression levels in AML samples and normal controls were confirmed by qRT-PCR and immunofluorescence.

RESULTS

We identified a potential inflammatory response-related signature comprising 11 differentially expressed genes, including ACVR2A, CCL22, EBI3, EDN1, FFAR2, HRH1, ICOSLG, IL-10, INHBA, ITGB3, and LAMP3, and found that AML patients with high expression levels in the high-risk group had poor OS rates. Biological function analyses revealed that prognostic genes mainly participated in inflammation and immunity signaling pathways. Analyses of cancer-infiltrating immunocytes indicated that in high-risk patients, the immune suppressive microenvironment was significantly affected. The expression of the inflammation reaction-associated signature was found to be associated with susceptibility to chemotherapy. There was a significant difference in prognostic gene expression between AML and control tissues.

CONCLUSION

A novel inflammatory response-related signature was developed with 11 candidate genes to predict prognosis and immune status in AML patients.