Subtype Of Osteosarcoma Research Articles

The correlation of Alkaline Phosphatase, lactate dehydrogenase, C-Reactive protein, erythrocyte sedimentation rate, and apparent diffusion coefficient values with Enneking staging and osteosarcoma subtypes

Apparent diffusion coefficient (ADC) values obtained from Magnetic Resonance Imaging (MRI) have shown potential as predictors of osteosarcoma staging and subtype, along with laboratory results for alkaline phosphatase (ALP), lactate dehydrogenase (LDH), c-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). However, studies investigating this correlation are still relatively limited. These tests may be an alternative for osteosarcoma staging and subtyping, especially in low-resource settings. This study aims to investigate the correlation between the ADC value and laboratory findings with the staging and subtype of osteosarcoma. This retrospective study analyzed data from osteosarcoma patients from August 2021 to August 2023, including serum levels of ALP, LDH, CRP, ESR, and ADC values from MRI. A study of 39 osteosarcoma patients found that most were male (61.5%), with an average age of 19. The distal femur was the most common tumor location (33.3%), and osteosarcoma chondroblast type was the predominant subtype (30.8%). Enneking stage IIB was the most prevalent (79.5%). ALP, LDH, CRP, and ESR biomarkers significantly correlated with Enneking staging (p<0.05). However, no correlations were found between these biomarkers and osteosarcoma subtype (p>0.1). Additionally, no significant correlations were observed between the mean ADC and Enneking staging (p=0.061) or osteosarcoma subtype (p=0.084). ALP, LDH, CRP, and ESR levels have a strong and significant correlation to the staging of Enneking osteosarcoma. However, the mean ADC values on MRI do not have a significant correlation to the osteosarcoma subtype based on histopathology.

Integrated single-cell analysis reveals heterogeneity and therapeutic insights in osteosarcoma

Osteosarcoma (OSA) is a primary bone malignancy characterized by its aggressive nature and high propensity for metastasis. Despite advancements in multimodal therapies, the clinical outcomes for OSA patients remain suboptimal, necessitating deeper molecular insights for improved therapeutic strategies. Here, we employed single-cell RNA sequencing (scRNA-seq) to elucidate the cellular heterogeneity and transcriptional dynamics of OSA tumors. Our study identified eleven distinct tumor cell subpopulations, including osteoblastic, chondroblastic, and myeloid lineages, each exhibiting unique transcriptional profiles associated with disease progression and metastasis. Epithelial-mesenchymal transition (EMT) emerged as a critical process driving aggressive phenotypes, supported by gene set enrichment analyses (GSVA) and transcription factor regulatory network analyses. Integration of copy number variation (CNV) data highlighted genomic alterations in osteoblastic and chondroblastic cells, implicating potential therapeutic targets. Furthermore, immune cell infiltration analyses revealed distinct immune profiles across OSA subtypes, correlating with tumor mutational burden (TMB) and clinical outcomes. Our findings underscore the complexity of OSA biology and provide a foundation for developing personalized treatment strategies targeting tumor heterogeneity and immune interactions.

Chondroblastic Osteosarcoma of the Mandible: An Uncommon Site for Osteosarcoma

Osteosarcoma is one of the most common types of malignant bone tumors, typically involving long bones such as the femur, tibia, and humerus. However, osteosarcomas occurring in the jaws are exceptionally rare, accounting for approximately 7% of all osteosarcoma cases and just 1% of malignancies in the head and neck region. This type of tumor usually affects individuals in their second and third decades of life. The subtypes of osteosarcoma include osteoblastic, chondroblastic, fibroblastic, small cell, and epithelioid. Chondroblastic osteosarcoma is associated with a poor prognosis, marked by a high recurrence rate, metastatic potential, and poor long-term survival outcomes. Here, we present the case of a 65-year-old woman with a painless swelling over the left cheek for 1 year, which significantly increased in size over the past 3 months, accompanied by trismus, reduced oral intake, and weight loss. Examination revealed a non-tender, hard swelling on the left cheek measuring 20x20cm, with prominent dilated veins. The left external auditory canal was collapsed due to the mass effect. Histopathological examination resulted as chondroblastic osteosarcoma of the left mandible. Computer tomography showed a large lobulated enhancing mass occupying the left cheek, associated with bone erosion and an aggressive periosteal reaction resembling a 'sunburst' pattern involving the ramus extending to the angle of the left mandible. The patient undergone open tracheostomy, left temporary tarsorrhaphy, wide local excision of tumor, left hemimandibulectomy, left partial maxillectomy and anterolateral thigh free flap reconstruction as patient unable to tolerate neoadjuvant chemotherapy.

Tumor necrosis drives prognosis in osteosarcoma: No difference in chemotherapy response and survival between chondroblastic and osteoblastic osteosarcoma

IntroductionThe percentage of tumor necrosis is a crucial prognostic factor in osteosarcoma. Many studies adopt a 90 % cutoff based on osteoblastic osteosarcoma, but these findings are generalized to all conventional subtypes, including chondroblastic osteosarcoma. We sought to answer these questions: (1) Is tumor necrosis ≥90 % associated with better overall survival (OS) and disease-free survival (DFS) in osteoblastic and chondroblastic osteosarcoma? (2) Does the osteosarcoma subtype impact tumor necrosis? (3) Does the osteosarcoma subtype in “good” responders (tumor necrosis ≥90 %) affect OS and DFS?. Materials and methodsWe conducted a retrospective study of 156 patients with osteoblastic and chondroblastic osteosarcoma treated at our institution. All patients received a standardized chemotherapy protocol and underwent surgery with the goal of achieving negative margins (R0 resection). Propensity-score matching was performed to adjust for potential confounders. Kaplan-Meier survival analysis and Cox proportional hazards modeling were performed. ResultsPatients with osteoblastic osteosarcoma and tumor necrosis ≥90 % had higher 5- and 10-year OS and DFS compared to those with necrosis <90 %. In chondroblastic osteosarcoma, a trend towards higher OS and DFS was seen in patients with tumor necrosis ≥90 %; this, however, was not significant. Chondroblastic osteosarcoma was not a risk factor for either tumor necrosis <90 % (p = 0.89) or tumor necrosis <70 % (p = 0.57). Patients with osteoblastic or chondroblastic osteosarcoma that were deemed “good” responders (tumor necrosis ≥90 %) had similar OS and DFS at the 5- and 10-year marks. ConclusionConventional osteosarcoma subtype was not a risk factor for “poor” response. Survival outcomes (OS and DFS) were similar for osteoblastic and chondroblastic osteosarcoma with good response to chemotherapy.

Imaging of Osteosarcoma: Presenting Findings, Metastatic Patterns, and Features Related to Prognosis

Background: Osteosarcomas are rare malignancies (&lt;1% of all cancers) that produce an osteoid matrix. Osteosarcomas are the second most frequent type of primary bone tumor after multiple myeloma and the most prevalent primary bone tumor in children. The spectrum of imaging findings of these malignancies varies significantly, reflecting different histological subtypes. For instance, conventional osteosarcoma typically presents with a mixed radiological pattern (lytic and bone mineralization) or with a completely eburneous one; aggressive periosteal reactions such as sunburst, Codman triangle, and soft-tissue components are frequently displayed. On the other hand, telangiectatic osteosarcoma usually presents as a purely lytic lesion with multiple fluid–fluid levels on MRI fluid-sensitive sequences. Other typical and atypical radiological patterns of presentation in other subtypes of osteosarcomas are described in this review. In addition to the characteristics associated with osteosarcoma subtyping, this review article also focuses on imaging features that have been associated with patient outcomes, namely response to chemotherapy and event-free and overall survivals. This includes simple semantic radiological features (such as tumor dimensions, anatomical location with difficulty of radical surgery, occurrence of pathological fractures, and presence of distant metastases), but also quantitative imaging parameters from diffusion-weighted imaging, dynamic contrast-enhanced MRI, and 18F-FDG positron emission tomography and radiomics approaches. Other particular features are described in the text. Overall, this comprehensive literature review aims to be a practical tool for oncologists, pathologists, surgeons, and radiologists involved in these patients’ care.

Multi-omics and Single Cell Sequencing Analyses Reveal Associations of Mitophagy-Related Genes Predicting Clinical Prognosis and Immune Infiltration Characteristics in Osteosarcoma.

Despite recent advances in clinical treatments, identifying high-risk osteosarcoma (OS) patients remains an unresolved clinical challenge. Mitophagy, a specialized form of cellular autophagy, selectively reduces the number of mitochondria or repairs their abnormal functions in response to external stress, thereby ensuring mitochondrial quality and maintaining mitochondrial function. Mitophagy plays a crucial role in cancer development, including processes such as mitochondrial repair, homeostasis maintenance, and tumor metabolism. However, its impact on OS has not yet been reported. In this study, we collected 58 mitophagy-related genes (MPRGs) from the TARGET and GEO databases and bioinformatically screened for those associated with OS prognosis. By LASSO-multivariable Cox regression algorithm, we subsequently developed a novel scoring system, the MPRG score, and validated its significance in predicting OS prognosis. Immune landscape analysis showed patients in the low MPRG group had a higher immune infiltration level than those in the high MPRG group. Drug sensitivity differences highlighted the potential need for alternative therapeutic strategies based on MPRG scoring system. The distribution characteristics of the MPRG signature in different cell subtypes of OS were explored by single-cell sequencing analyses. In vitro experiments further confirmed the abnormal expression of screened targets in OS. Our findings highlight the role of mitophagy in OS and its potential as a therapeutic target.

Distinct Gene Expression and Immune Features Between Different Neutrophil Extracellular Trap-Related Osteosarcoma Subtypes.

We sought to determine neutrophil extracellular trap (NET)-related genes' potential value in improving the efficacy of diagnosis and identifying novel therapeutic targets for osteosarcoma. Data were obtained from TARGET, GEO, and CCLE database. Differentially expressed genes were identified between the subtypes based on NET-related genes. PPI network was constructed using STRING, following by ClueGO enrichment analysis. Infiltration of immune cells was calculated by ssGSEA. Risk Score model was built by LASSO Cox regression analysis. Western blot and qRT-PCR were applied to validate the expression of genes used in the model. We identified 19 NET-related genes with prognostic potential in osteosarcoma using univariate Cox regression analysis. Patients from TARGET were clustered into two subtypes with distinct prognosis and immune features. 381 DEGs were identified between the two NET subtypes. Risk Score based on BST1, SELPLG, FPR1 and TNFRSF10C was reliable to predict the prognosis of osteosarcoma patients. The four genes expressed significantly lower in osteosarcoma than normal cells. Low Risk Score individuals only existed in C1 subtype with better prognosis. Osteosarcoma were clustered into two subtypes based on NET-related genes. Risk Score model constructed by four NET-related gene was able to independently predict the prognosis of osteosarcoma.

Targeting WNT5B and WNT10B in osteosarcoma.

WNT signaling regulates osteosarcoma proliferation. However, there is controversy in the field of osteosarcoma as to whether WNT signaling is pro- or anti-tumorigenic. WNT-targeting therapeutics, both activators and inhibitors, are compared. WNT5B, a β-catenin-independent ligand, and WNT10B, a β-catenin-dependent WNT ligand, are each expressed in osteosarcomas, but they are not expressed in the same tumors. Furthermore, WNT10B and WNT5B regulate different histological subtypes of osteosarcomas. Using WNT signaling modulators as therapeutics may depend on the WNT ligand and/or the activated signaling pathway.

Identification of a pro-protein synthesis osteosarcoma subtype for predicting prognosis and treatment

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor that is aggressive and has a poor prognosis. Although combining surgery and chemotherapy has significantly improved patient outcomes, the prognosis for OS patients with metastatic or recurrent OS has remained unsatisfactory. Therefore, it is imperative to gain a fresh perspective on OS development mechanisms and treatment strategies. After studying single-cell RNA sequencing (scRNA-seq) data in public databases, we identified seven OS subclonal types based on intra-tumor heterogeneity. Subsequently, we constructed a prognostic model based on pro-protein synthesis osteosarcoma (PPS-OS)-associated genes. Correlation analysis showed that the prognostic model performs extremely well in predicting OS patient prognosis. We also demonstrated that the independent risk factors for the prognosis of OS patients were tumor primary site, metastatic status, and risk score. Based on these factors, nomograms were constructed for predicting the 3- and 5-year survival rates. Afterward, the investigation of the tumor immune microenvironment (TIME) revealed the vital roles of γδ T-cell and B-cell activation. Drug sensitivity analysis and immune checkpoint analysis identified drugs that have potential application value in OS. Finally, the jumping translocation breakpoint (JTB) gene was selected for experimental validation. JTB silencing suppressed the proliferation, migration, and invasion of OS cells. Therefore, our research suggests that PPS-OS-related genes facilitate the malignant progression of OS and may be employed as prognostic indicators and therapeutic targets in OS.

Evaluation of tumor immune microenvironment for PD-L1 score and tumor infiltrating lymphocytes in high grade osteosarcomas and their correlation with disease progression.

e23510 Background: Tumor Immune Micro-environment is being increasingly recognised as a potential target for improving overall survival for osteosarcomas, especially in the metastatic setting. Our study purpose was to evaluate the PD- L1 (Programmed cell Death- Ligand 1) expression in neoplastic cells well as Tumor Infiltrating Lymphocyte (TIL) density of osteosarcoma specimens and correlate it with oncological outcomes. Materials &amp; Methods: A prospective cohort study was conducted between March 2017 and March 2022 among osteosarcoma patients who underwent primary biopsy and neo-adjuvant chemotherapy followed by surgical excision at our centre. We excluded patients who had alternative diagnoses such as low grade osteosarcoma, secondary osteosarcoma, recurrent osteosarcoma as well as patients who had undergone initial treatment (chemotherapy/ surgery) outside our institute. De-paraffinized sections (4μ) incubated with primary antibody (PDL1) and a universal secondary detection kit used. Average percentage of positive cells calculated from at least 10 representative fields at 400X magnification. Positive staining was considered when ≥1% cells showed positivity. IHC scoring of PD-L1 was graded as negative, low positive and high positive. We calculated the number of TILs under 400X magnification in ten fields and then took their average. TILs staining was scored semi quantitatively using a 3 tiered scale. Results: Forty patients who fulfilled the inclusion &amp; exclusion criteria were included in the study with most common age group being 10 to 19 years (27 patient, 68%). The male: female ratio was 1.6: 1 and the most common location of tumor was distal femur. Majority of patients had the histological subtype of conventional osteosarcoma (37 patients, 92.5%). Lung metastasis was present at time of initial diagnosis in 27 patients (67.5%). At the end of 2 years, 27 patients were alive (60%) while 13 patients had died due to disease. PD-L1 expression was negative in 17.5%, low positive in 15% and high positive in 67.5%. Among TIL category, 19 patients belonged to category 1, 10 belonged to category 2 &amp; 11 belonged to category 3. There was significant correlation between PD-L1 expression score &amp; TIL category. PD-L1 score did not correlate with percentage of necrosis following chemotherapy, metastasis on presentation or overall survival. Conclusions: PD-L1 score had significant correlation with density of Tumor Infiltrating lymphocytes (TIL). However, PD-L1 score did not correlate with overall survival, tumor-free survival, progression of metastasis or local recurrence.

High-grade surface osteosarcoma: A National Cancer Database study of demographic characteristics.

e23508 Background: High-grade surface osteosarcoma (HGSO) is an extremely rare malignant subtype of osteosarcoma. HGSO often affects long bones, particularly the femur, and is the rarest subtype of surface osteosarcomas. Though data is limited, current information suggests this cancer presents with a poor prognosis, generally affecting adults aged 20 to 40. Current treatment standards involve wide resection and chemotherapy. The National Cancer Database (NCDB) was examined to establish the demographic factors among HGSO patients and identify diagnostic and treatment trends. Methods: A retrospective cohort study from 2005-2020 was conducted using the NCDB. A total of 99 patients were found with a histologically confirmed diagnosis of high-grade surface osteosarcoma (ICD-9194-3). Factors such as gender, age, race, insurance status, rural/urban residence, treatments, mortality rates, and Charles/Deyo scores were analyzed using descriptive statistics, and trends in incidence were interpreted via regression analysis. Results: Yearly HGSO incidence rates increased from 2005 to 2020 (R2 = 0.19). The average age of diagnosis was 41 years (SD = 24.9, range = 10-90) with men diagnosed (54%) slightly more than women. The majority of patients were non-Hispanic white (73%), had private insurance (55%), and lived in a metropolitan area with over 250,000 in population (89%). The average patient was diagnosed at a hospital 40.4 miles away from their home (SD = 84.9, range 0.4-648.4 miles). Most patients (55%) were in stage II at diagnosis, and 86% of patients had a Charlson-Deyo comorbidity score of 0. The most common primary site of this malignancy was the long bones of the lower limb and associated joints (67%), while the upper extremities (8%) and pelvic bone (8%) served as less common primary sites. Surgery was the most common primary treatment (62%). Data from 69 patients revealed the 90-day mortality post-surgery was 3%. The mean survival rate was 70% at two years and 52% at five years. Conclusions: To the best of our knowledge, this study represents the first NCDB analysis of HGSO. Our analysis demonstrated that HGSO occurs most often, but not exclusively, within the lower extremity long bones, which may be an important diagnostic distinction. It was previously indicated that the average age at HGSO diagnosis is 20-40 years, but our analysis suggested it is closer to 40. Our analysis revealed a five-year survival rate of 52% which is worse than prior studies have indicated. Demographic data has revealed the majority of patients were non-Hispanic white, privately insured, and living within a metropolitan area. This trend may suggest access to healthcare resources is influencing this cancer’s diagnosis and treatment. Further research is warranted to explore whether the demographic patterns seen in HGSO are indicative of biological causes or socioeconomic factors that are significantly influencing diagnosis.

High expression of DEC2 distinguishes chondroblastic osteosarcoma and promotes tumour growth by activating the VEGFC/VEGFR2 signalling pathway.

Osteosarcoma (OS) is the most common primary malignant bone tumour in children and young adults. Account for 80% of all OS cases, conventional OS are characterized by the presence of osteoblastic, chondroblastic and fibroblastic cell types. Despite this heterogeneity, therapeutic treatment and prognosis of OS are essentially the same for all OS subtypes. Here, we report that DEC2, a transcriptional repressor, is expressed at higher levels in chondroblastic OS compared with osteoblastic OS. This difference suggests that DEC2 is disproportionately involved in the progression of chondroblastic OS, and thus, DEC2 may represent a possible molecular target for treating this type of OS. In the human chondroblastic-like OS cell line MNNG/HOS, we found that overexpression of DEC2 affects the proliferation of the cells by activating the VEGFC/VEGFR2 signalling pathway. Enhanced expression of DEC2 increased VEGFR2 expression, as well as increased the phosphorylation levels at sites Y951 and Y1175 of VEGFR2. On the one hand, activation of VEGFR2Y1175 enhanced cell proliferation through VEGFR2Y1175-PLCγ1-PKC-SPHK-MEK-ERK signalling. On the other hand, activation of VEGFR2Y951 decreased mitochondria-dependent apoptosis rate through VEGFR2Y951-VARP-PI3K-AKT signalling. Activation of these two signalling pathways resulted in enhanced progression of chondroblastic OS. In conclusion, DEC2 plays a pivotal role in cell proliferation and apoptosis-resistance in chondroblastic OS via the VEGFC/VEGFR2 signalling pathway. These findings lay the groundwork for developing focused treatments that target specific types of OS.

Development of a novel six DNA damage response-related prognostic signature in osteosarcoma.

DNA damage response (DDR) plays a vital role in the development of cancer. Nevertheless, in osteosarcoma, the potential of DDR-related genes (DDRGs) remains unclear. Thus, the current research is intended to investigate the mechanisms of DDRGs in the development of osteosarcoma and to explore potential DDR-related biomarkers in forecasting the prognosis of osteosarcoma patients. The osteosarcoma genomic data from TCGA, GEO and cBioPortal databases were utilized for screening and identification of differentially expressed DDRGs (DEDDRGs). Consensus clustering analysis was performed to identify different subtypes of osteosarcoma based on the expressions of DDRGs. Key DEDRRGs were identified by overlapping DEDRRGs between different subtypes and DEDRRGs between tumor and control samples. Univariate, as well as LASSO regressions, were further applied to obtain robust prognostic signatures. GSVA and ssGSEA analysis were implemented to explore the underlying mechanisms of prognostic DDRG signature in regulating osteosarcoma. In addition, the drug sensitivity of patients in low- and high-risk groups was evaluated using pRRophetic algorithm. A total of 43 key DEDRRGs were identified. Followed by univariate Cox along with LASSO regression analyses, CDK6, CSF1R, EGFR, ERBB4, GATA3 and SOCS1 were identified as prognostic signatures in osteosarcoma. Cox regressions revealed that the risk score was an independent prognostic factor in osteosarcoma. DDR may affect osteosarcoma via regulating immune microenvironment along with influencing cell proliferation, migration, adhesion and apoptosis. The chemotherapeutic response between patients in low- and high-risk groups was much different. The role of DDRGs in osteosarcoma and identified six DDR-linked biomarkers for forecasting the prognosis of osteosarcoma patients. Our outcomes enhanced the understanding of DDR-related molecular mechanisms involved in osteosarcoma and provided potential therapeutic targets for osteosarcoma patients.

Abstract 5370: Tumor-intrinsic cGAS-STING activation promotes anti-tumor inflammatory response in osteosarcoma

Abstract A “cold” tumor microenvironment (TME) is often seen in patients with osteosarcoma (OS). Genomic instability, characteristic of OS, can stimulate the cGAS-STING pathway and activate the innate immune system. Tumor-intrinsic STING pathway silencing mechanisms can link genomic instability to immune evasion in OS. We hypothesize that dysregulation of the cGAS-STING pathway suppresses an innate immune response to genomic instability and plays a key role in tumor progression through establishing an immunosuppressive TME in OS. Using a novel panel of 11 OS patient-derived cell lines, we have identified two groups in terms of capacity for tumor-intrinsic STING activation, and we aim to unravel the mechanism of STING repression in a subset of OS tumors. To investigate the effects of tumor-intrinsic STING activation on macrophage polarization we employed tumor conditioned media (TCM) assays with murine-derived macrophages and tumor lines treated with cGAS-STING agonism. Tumor-intrinsic STING activation resulted in a significant increase in pro-inflammatory macrophages in a manner dependent on tumor STING. Lastly, we performed bulk RNA seq of OS PDX cell lines treated with STING agonist, defining for the first time the OS-specific STING activation signature. We then evaluated primary patient samples for evidence of this signature by single sample GSEA and performed survival analysis after stratifying samples as high or low for this signature, which demonstrated a significant protective effect of the STING activation signature on progression-free and overall survival. We have defined two subtypes of OS in terms of responsiveness to STING activation and demonstrated that STING activation has a protective effect in the human disease, which is the foundation of current efforts to identify targetable mechanism to reverse STING unresponsiveness and activate immune surveillance in this cancer. Citation Format: Elizabeth "Betsy" Peale Young, Christine Johnson, Alex G. Lee, Eric Alejandro Sweet-Cordero. Tumor-intrinsic cGAS-STING activation promotes anti-tumor inflammatory response in osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5370.

Abstract B036: cGAS-STING activation promotes anti-tumor inflammatory response in osteosarcoma: Implications for tumor microenvironment reprogramming and tumor progression in patients

Abstract A “cold” tumor microenvironment (TME) is often seen in pediatric patients with osteosarcoma (OS). Genomic instability, characteristic of OS, can stimulate the cGAS-STING pathway and activate the innate immune system. However, tumor-intrinsic STING pathway silencing mechanisms link genomic instability to immune evasion in OS. We hypothesized that dysregulation of the cGAS-STING pathway suppresses an innate immune response to genomic instability and plays a key role in tumor progression by shaping an immunosuppressive TME in pediatric OS patients. Using a panel of 11 OS patient-derived xenograft (PDX)-derived cell lines, we characterized cGAS-STING pathway function and observed heterogeneity in STING responsiveness. Comprehensive biochemical evaluation of the inflammatory signaling response to STING agonism revealed two groups (6 responsive and 5 unresponsive) among our panel of 11 OS PDX-derived cell lines. To investigate the effects of OS tumor-intrinsic STING activation on macrophage polarization, we used tumor conditioned media (TCM) assays. We hypothesized that cGAS-STING activation in OS cell lines would be sufficient to shift macrophage phenotype ratios, enriching for a higher proportion of inflammatory macrophages, through the secretion of inflammatory factors that stimulate innate immune cells. A cGAS agonist, G3-YSD, was used to stimulate the STING pathway in murine OS lines. Addition of the TCM to macrophages resulted in a decrease in CD206+ “M2-like” macrophages and an increase in MHC II+ “M1-like” macrophages, measured via flow cytometry, in a manner dependent on tumor STING. Lastly, we performed bulk RNA sequencing of OS PDX cell lines treated with a STING agonist, defining for the first time the OS-specific STING activation signature. We then evaluated primary OS patient samples for evidence of this signature by gene set enrichment analysis and performed Kaplan-Meier survival analysis after stratifying samples as high or low for this signature, which demonstrated a significant protective effect of the STING activation signature on progression-free and overall survival. Together, we have shown that dysregulation of the cGAS-STING pathway represses the innate immune response to the genomic instability present in many OS cells and represents a key factor in the establishment of aggressive behavior in OS tumors. We have defined two subtypes of OS in terms of responsiveness to STING activation and demonstrated that STING activation has a protective effect in the human disease, which is the foundation of current efforts to explore targetable mechanisms to reverse STING unresponsiveness and activate immune surveillance in this cancer. Citation Format: Elizabeth P Young, Christine A Johnson, Alex G Lee, Courtney R Schott, E. Alejandro Sweet-Cordero. cGAS-STING activation promotes anti-tumor inflammatory response in osteosarcoma: Implications for tumor microenvironment reprogramming and tumor progression in patients [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B036.

Construction of a 5-gene prognostic signature based on oxidative stress related genes for predicting prognosis in osteosarcoma.

The understanding of the complex biological scenario of osteosarcoma will open the way to identifying new strategies for its treatment. Oxidative stress is a cancer-related biological scenario. At present, it is not clear the oxidative stress genes in affecting the prognosis and progression of osteosarcoma, the underlying mechanism as well as their impact on the classification of osteosarcoma subtypes. We selected samples and sequencing data from TARGET data set and GSE21257 data set, and downloaded oxidative stress related-genes (OSRGs) from MsigDB. Univariate Cox analysis of OSRG was conducted using TARGET data, and the prognostic OSRG was screened to conduct unsupervised clustering analysis to identify the molecular subtypes of osteosarcoma. Through least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression analysis of differentially expressed genes (DEGs) between subgroups, a risk assessment system for osteosarcoma was developed. 45 prognosis-related OSRGs genes were acquired, and two molecular subtypes of osteosarcoma were clustered. C2 cluster displayed prolonged overall survival (OS) accompanied with high degree of immune infiltration and enriched immune pathways. While cell cycle related pathways were enriched in C2 cluster. Based on DEGs between subgroups and Lasso analysis, 5 hub genes (ZYX, GJA5, GAL, GRAMD1B, and CKMT2) were screened to establish a robust prognostic risk model independent of clinicopathological features. High-risk group had more patients with cancer metastasis and death as well as C1 subtype with poor prognosis. Low-risk group exhibited favorable OS and high immune infiltration status. Additionally, the risk assessment system was optimized by building decision tree and nomogram. This study defined two molecular subtypes of osteosarcoma with different prognosis and tumor immune microenvironment status based on the expression of OSRGs, and provided a new risk assessment system for the prognosis of osteosarcoma.

Osteosarcoma Multi-Omics Landscape and Subtypes.

Osteosarcoma (OS) is the most common primary bone malignancy that exhibits remarkable histologic diversity and genetic heterogeneity. The complex nature of osteosarcoma has confounded precise molecular categorization, prognosis, and prediction for this disease. In this study, we performed a comprehensive multiplatform analysis on 86 osteosarcoma tumors, including somatic copy-number alteration, gene expression and methylation, and identified three molecularly distinct and clinically relevant subtypes of osteosarcoma. The subgrouping criteria was validated on another cohort of osteosarcoma tumors. Previously unappreciated osteosarcoma-type-specific changes in specific genes' copy number, expression and methylation were revealed based on the subgrouping. The subgrouping and novel gene signatures provide insights into refining osteosarcoma therapy and relationships to other types of cancer.

Comparative Shotgun Proteomics Reveals the Characteristic Protein Signature of Osteosarcoma Subtypes.

Osteosarcoma is a primary malignant bone tumor affecting adolescents and young adults. This study aimed to identify proteomic signatures that distinguish between different osteosarcoma subtypes, providing insights into their molecular heterogeneity and potential implications for personalized treatment approaches. Using advanced proteomic techniques, we analyzed FFPE tumor samples from a cohort of pediatric osteosarcoma patients representing four various subtypes. Differential expression analysis revealed a significant proteomic signature that discriminated between these subtypes, highlighting distinct molecular profiles associated with different tumor characteristics. In contrast, clinical determinants did not correlate with the proteome signature of pediatric osteosarcoma. The identified proteomics signature encompassed a diverse array of proteins involved in focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathways, and proteoglycans in cancer, among the top enriched pathways. These findings underscore the importance of considering the molecular heterogeneity of osteosarcoma during diagnosis or even when developing personalized treatment strategies. By identifying subtype-specific proteomics signatures, clinicians may be able to tailor therapy regimens to individual patients, optimizing treatment efficacy and minimizing adverse effects.

Tumor microenvironment phenotypes and prognostic evaluation tools for osteosarcoma characterized by different prognostic outcomes and immunotherapy responses.

The physiological and immunological characteristics of the tumor microenvironment (TME) have a profound impact on the effectiveness of immunotherapy. The present study aimed to define the TME subtype of osteosarcoma according to the signatures representing the global TME of the tumor, as well as create a new prognostic assessment tool to monitor the prognosis, TME activity and immunotherapy response of patients with osteosarcoma. The enrichment scores of 29 functional gene expression signatures in osteosarcoma samples were calculated by single sample gene set enrichment analysis (ssGSEA). TME classification of osteosarcoma was performed and a prognostic assessment tool was created based on 29 ssGSEA scores to comprehensively correlate them with TME components, immunotherapy efficacy and prognosis of osteosarcoma. Three TME subtypes were generated that differed in survival, TME activity and immunotherapeutic response. Four differentially expressed genes between TME subtypes were involved in the development of prognostic assessment tools. The established prognosis assessment tool had strong performance in both training and verification cohorts, could be effectively applied to the survival prediction of samples of different ages, genders and transfer states, and could well distinguish the TME status of different samples. The present study describes three different TME phenotypes in osteosarcoma, provides a risk stratification tool for osteosarcoma prognosis and TME status assessment, and provides additional information for clinical decision-making of immunotherapy.

Development of a novel vasculogenic mimicry-associated gene signature for the prognostic assessment of osteosarcoma patients.

Osteosarcoma (OS) is a form of primary bone malignancy associated with poor prognostic outcomes. Recent work has highlighted vasculogenic mimicry (VM) as a key mechanism that supports aggressive tumor growth. The patterns of VM-associated gene expression in OS and the relationship between these genes and patient outcomes, however, have yet to be defined. Here, 48 VM-related genes were systematically assessed to examine correlations between the expression of these genes and OS patient prognosis in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) cohort. Patients were classified into three OS subtypes. Differentially expressed genes for these three OS subtypes were then compared with hub genes detected in a weighted gene co-expression network analysis, leading to the identification of 163 overlapping genes that were subject to further biological activity analyses. A three-gene signature (CGREF1, CORT, and GALNT14) was ultimately constructed through a least absolute shrinkage and selection operator Cox regression analysis, and this signature was used to separate patients into low- and high-risk groups. The K-M survival analysis, receiver operating characteristic analysis, and decision curve analysis were adopted to evaluate the prognostic prediction performance of the signature. Furthermore, the expression patterns of three genes derived from the prognostic model were validated by quantitative real-time polymerase chain reaction (RT-qPCR). VM-associated gene expression patterns were successfully established, and three VM subtypes of OS that were associated with patient prognosis and copy number variants were defined. The developed three-gene signature was constructed, which served as independent prognostic markers and prediction factors for the clinicopathological features of OS. Finally, lastly, the signature may also have a guiding effect on the sensitivity of different chemotherapeutic drugs. Overall, these analyses facilitated the development of a prognostic VM-associated gene signature capable of predicting OS patient outcomes. This signature may be of value for both studies of the mechanistic basis for VM and clinical decision-making in the context of OS patient management.