Predictors and Survival of Patients with Osteosarcoma After Limb Salvage versus Amputation: A Population-Based Analysis with Propensity Score Matching

Comparison of survival between palliative surgery and no surgery for advanced tongue squamous cell carcinoma: an analysis of SEER data

The aim of this study was to investigate the survival effect of palliative surgery in advanced tongue squamous cell carcinoma (TSCC). A retrospective analysis of data in the SEER database for 6151 patients with stage III/IV TSCC (American Joint Committee on Cancer (AJCC) staging), diagnosed between 2004 and 2015, was performed. The patients were divided into two groups: palliative surgery and no surgery. Kaplan-Meier and Cox proportional hazards regression analyses were applied to determine risk factors for overall survival (OS) and cancer-specific survival (CSS). A further analysis was performed using 1:1 propensity score matching (PSM) to balance 13 patient variables (sex, age at diagnosis, race, marital status, primary tumour site, SEER stage, AJCC stage, pathological differentiation grade, tumour size, lymph node metastasis, previous lymph node removal, radiotherapy, and chemotherapy). Among the 6151 patients, 706 underwent palliative surgery; the other 5445 did not undergo any kind of surgery. Those who underwent palliative surgery had a higher 5-year survival rate. After PSM, 1274 patients were included in the matched cohort. Multivariate Cox regression analysis showed that patients who underwent palliative surgery had a lower risk of death than those who did not (OS: hazard ratio 0.58, 95% confidence interval 0.49-0.69, P < 0.001; CSS: hazard ratio 0.60, 95% confidence interval 0.49-0.74, P < 0.001). In this comparative study it was found that compared with no surgery, palliative surgery has a positive impact on the survival rate of patients with advanced TSCC.

Clinical Features, Risk Factors, and Prediction Nomogram for Primary Spinal Osteosarcoma: A Large-Cohort Retrospective Study

STUDY DESIGN

Retrospective cohort study.

OBJECTIVES

The goal of this study was to determine the clinical characteristics of patients with primary spinal osteosarcoma and to construct a practical clinical prediction model for patients to achieve an accurate prediction of overall survival.

METHODS

This study included 230 patients diagnosed between 2004-2015 from the Surveillance, Epidemiology, and End Results database. Independent risk factors were screened in the training set using Cox regression algorithms, and a prognostic model was developed. Internal and external validation sets were used to test the nomogram model's calibration, discrimination, and clinical utility. A risk classification system based on the nomogram was developed and validated.

RESULTS

Four independent prognostic factors were identified, and based on this a nomogram model was developed for predicting patient prognosis. The C-index of the training set was .737, while that of the validation set was .693. The time-varying area under the curve values was greater than .720 in both cohorts. The calibration curves proved that the prediction model has high prediction accuracy. The decision curve analysis showed that the nomogram is clinically useful. A risk classification system was established, which allows all patients to be divided into two different risk groups.

CONCLUSIONS

A nomogram and risk classification system was developed for patients with primary spinal osteosarcoma to accurately predict overall patient survival and achieve risk stratification of patient mortality. These tools are expected to play an important role in clinical practice, informing clinicians in making decisions.

Prognosis of limb‑salvage treatment of osteosarcoma in adolescent patients: a meta‑analysis

To evaluate the effectiveness of limb-salvage treatment for osteosarcoma in adolescent patients, a comprehensive search on PubMed, Embase and Cochrane Library was conducted. Studies with a clear diagnosis of osteosarcoma were included and duplicate publications, studies without full text or incomplete information, those with an inability to extract data, divergent definitions of exposure, animal experiments, reviews, and systematic reviews were excluded. The data were analyzed using STATA 15.1. The findings of the present study revealed that overall survival (OS) and progression-free survival (PFS) of patients with osteosarcoma in the limb-salvage treatment group were significantly longer than those in the amputation treatment group [hazard ratio (HR)=0.71; 95% confidence interval (CI): 0.63-0.80; P=0.000 vs. HR=0.60; 95% CI: 0.48-0.76; P=0.000]. Additionally, the five-year OS rate for patients in the limb-salvage treatment group was higher than that in the amputation group [odds ratio (OR)=4.48; 95% CI: 2.74-7.31; P=0.000]. However, the local recurrence rate was notably higher in the limb-salvage treatment group compared with the amputation treatment group (OR=2.68; 95% CI: 1.50-4.77; P=0.001). Furthermore, the results indicated no significant difference in distant metastasis rates between the limb-salvage treatment group and the amputation treatment group (OR=0.32; 95% CI: 0.10-1.06; P=0.062). In conclusion, the present meta-analysis underscores the potential of limb-salvage therapy for adolescent patients with osteosarcoma. The OS and PFS of patients undergoing limb-salvage surgery are longer than those of amputation, with a higher five-year OS rate and a similar rate of distant metastasis. However, the local recurrence rate of limb-salvage surgery is significantly higher than that of amputation.

Is the Number of National Database Research Studies in Musculoskeletal Sarcoma Increasing, and Are These Studies Reliable?

BACKGROUND

Large national databases have become a common source of information on patterns of cancer care in the United States, particularly for low-incidence diseases such as sarcoma. Although aggregating information from many hospitals can achieve statistical power, this may come at a cost when complex variables must be abstracted from the medical record. There is a current lack of understanding of the frequency of use of the Surveillance, Epidemiology, and End Results (SEER) database and the National Cancer Database (NCDB) over the last two decades in musculoskeletal sarcoma research and whether their use tends to produce papers with conflicting findings.

QUESTIONS/PURPOSES

(1) Is the number of published studies using the SEER and NCDB databases in musculoskeletal sarcoma research increasing over time? (2) What are the author, journal, and content characteristics of these studies? (3) Do studies using the SEER and the NCDB databases for similar diagnoses and study questions report concordant or discordant key findings? (4) Are the administrative data reported by our institution to the SEER and the NCDB databases concordant with the data in our longitudinally maintained, physician-run orthopaedic oncology dataset?

METHODS

To answer our first three questions, PubMed was searched from 2001 through 2020 for all studies using the SEER or the NCDB databases to evaluate sarcoma. Studies were excluded from the review if they did not use these databases or studied anatomic locations other than the extremities, nonretroperitoneal pelvis, trunk, chest wall, or spine. To answer our first question, the number of SEER and NCDB studies were counted by year. The publication rate over the 20-year span was assessed with simple linear regression modeling. The difference in the mean number of studies between 5-year intervals (2001-2005, 2006-2010, 2011-2015, 2016-2020) was also assessed with Student t-tests. To answer our second question, we recorded and summarized descriptive data regarding author, journal, and content for these studies. To answer our third question, we grouped all studies by diagnosis, and then identified studies that shared the same diagnosis and a similar major study question with at least one other study. We then categorized study questions (and their associated studies) as having concordant findings, discordant findings, or mixed findings. Proportions of studies with concordant, discordant, or mixed findings were compared. To answer our fourth question, a coding audit was performed assessing the concordance of nationally reported administrative data from our institution with data from our longitudinally maintained, physician-run orthopaedic oncology dataset in a series of patients during the past 3 years. Our orthopaedic oncology dataset is maintained on a weekly basis by the senior author who manually records data directly from the medical record and sarcoma tumor board consensus notes; this dataset served as the gold standard for data comparison. We compared date of birth, surgery date, margin status, tumor size, clinical stage, and adjuvant treatment.

RESULTS

The number of musculoskeletal sarcoma studies using the SEER and the NCDB databases has steadily increased over time in a linear regression model (β = 2.51; p < 0.001). The mean number of studies per year more than tripled during 2016-2020 compared with 2011-2015 (39 versus 13 studies; mean difference 26 ± 11; p = 0.03). Of the 299 studies in total, 56% (168 of 299) have been published since 2018. Nineteen institutions published more than five studies, and the most studies from one institution was 13. Orthopaedic surgeons authored 35% (104 of 299) of studies, and medical oncology journals published 44% (130 of 299). Of the 94 studies (31% of total [94 of 299]) that shared a major study question with at least one other study, 35% (33 of 94) reported discordant key findings, 29% (27 of 94) reported mixed key findings, and 44% (41 of 94) reported concordant key findings. Both concordant and discordant groups included papers on prognostic factors, demographic factors, and treatment strategies. When we compared nationally reported administrative data from our institution with our orthopaedic oncology dataset, we found clinically important discrepancies in adjuvant treatment (19% [15 of 77]), tumor size (21% [16 of 77]), surgery date (23% [18 of 77]), surgical margins (38% [29 of 77]), and clinical stage (77% [59 of 77]).

CONCLUSION

Appropriate use of databases in musculoskeletal cancer research is essential to promote clear interpretation of findings, as almost two-thirds of studies we evaluated that asked similar study questions produced discordant or mixed key findings. Readers should be mindful of the differences in what each database seeks to convey because asking the same questions of different databases may result in different answers depending on what information each database captures. Likewise, differences in how studies determine which patients to include or exclude, how they handle missing data, and what they choose to emphasize may result in different messages getting drawn from large-database studies. Still, given the rarity and heterogeneity of sarcomas, these databases remain particularly useful in musculoskeletal cancer research for nationwide incidence estimations, risk factor/prognostic factor assessment, patient demographic and hospital-level variable assessment, patterns of care over time, and hypothesis generation for future prospective studies.

LEVEL OF EVIDENCE

Level III, therapeutic study.

A new model of preoperative systemic inflammatory markers predicting overall survival of osteosarcoma: a multicenter retrospective study

BACKGROUND

The purpose of this study was to investigate the significance of preoperative C-reactive protein-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting overall survival (OS) of osteosarcoma, to establish a nomogram of an individualized prognostic prediction model for osteosarcoma.

METHODS

Two hundred thirty-five patients with osteosarcoma from multiple centers were included in this study. Receiver operating characteristic (ROC) and Youden index were used to determine the optimal cutoff values ​​for CAR, NLR, and PLR. Univariate analysis using COX proportional hazards model to identify factors associated with OS in osteosarcoma, and multivariate analysis of these factors to identify independent prognostic factors. R software (4.1.3-win) rms package was used to build a nomogram, and the concordance index (C-index) and calibration curve were used to assess model accuracy and discriminability.

RESULTS

Univariate analysis revealed that the OS of osteosarcoma is significantly correlated (P < 0.05) with CAR, NLR, PLR, Enneking stage, tumor size, age, neoadjuvant chemotherapy (NACT), and high alkaline phosphatase. Multivariate analysis confirmed that CAR, NLR, Enneking stage, NACT and tumor size are independent prognostic factors for OS of osteosarcoma. The calibration curve shows that the nomogram constructed from these factors has acceptable consistency and calibration capability.

CONCLUSION

Preoperative CAR and NLR were independent predictors of osteosarcoma prognosis, and the combination of nomogram model can realize individualized prognosis prediction and guide medical practice.

Risk stratification system and web-based nomogram constructed for predicting the overall survival of primary osteosarcoma patients after surgical resection

Background

Previous prediction models of osteosarcoma have not focused on survival in patients undergoing surgery, nor have they distinguished and compared prognostic differences among amputation, radical and local resection. This study aimed to establish and validate the first reliable prognostic nomogram to accurately predict overall survival (OS) after surgical resection in patients with osteosarcoma. On this basis, we constructed a risk stratification system and a web-based nomogram.

Methods

We enrolled all patients with primary osteosarcoma who underwent surgery between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. In patients with primary osteosarcoma after surgical resection, univariate and multivariate cox proportional hazards regression analyses were utilized to identify independent prognostic factors and construct a novel nomogram for the 1-, 3-, and 5-year OS. Then the nomogram's predictive performance and clinical utility were evaluated by the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Result

This study recruited 1,396 patients in all, with 837 serving as the training set (60%) and 559 as the validation set (40%). After COX regression analysis, we identified seven independent prognostic factors to develop the nomogram, including age, primary site, histological type, disease stage, AJCC stage, tumor size, and surgical method. The C-index indicated that this nomogram is considerably more accurate than the AJCC stage in predicting OS [Training set (HR: 0.741, 95% CI: 0.726–0.755) vs. (HR: 0.632, 95% CI: 0.619–0.645); Validation set (HR: 0.735, 95% CI: 0.718–0.753) vs. (HR: 0.635, 95% CI: 0.619–0.652)]. Moreover, the area under ROC curves, the calibration curves, and DCA demonstrated that this nomogram was significantly superior to the AJCC stage, with better predictive performance and more net clinical benefits.

Conclusion

This study highlighted that radical surgery was the first choice for patients with primary osteosarcoma since it provided the best survival prognosis. We have established and validated a novel nomogram that could objectively predict the overall survival of patients with primary osteosarcoma after surgical resection. Furthermore, a risk stratification system and a web-based nomogram could be applied in clinical practice to assist in therapeutic decision-making.

Interpretable clinical visualization model for prediction of prognosis in osteosarcoma: a large cohort data study

Background

Currently, the clinical prediction model for patients with osteosarcoma was almost developed from single-center data, lacking external validation. Due to their low reliability and low predictive power, there were few clinical applications. Our study aimed to set up a clinical prediction model with stronger predictive ability, credibility, and clinical application value for osteosarcoma.

Methods

Clinical information related to osteosarcoma patients from 2010 to 2016 was collected in the SEER database and four different Chinese medical centers. Factors were screened using three models (full subset regression, univariate Cox, and LASSO) via minimum AIC and maximum AUC values in the SEER database. The model was selected by the strongest predictive power and visualized by three statistical methods: nomogram, web calculator, and decision tree. The model was further externally validated and evaluated for its clinical utility in data from four medical centers.

Results

Eight predicting factors, namely, age, grade, laterality, stage M, surgery, bone metastases, lung metastases, and tumor size, were selected from the model based on the minimum AIC and maximum AUC value. The internal and external validation results showed that the model possessed good consistency. ROC curves revealed good predictive ability (AUC &gt; 0.8 in both internal and external validation). The DCA results demonstrated that the model had an excellent clinical predicted utility in 3 years and 5 years for North American and Chinese patients.

Conclusions

The clinical prediction model was built and visualized in this study, including a nomogram and a web calculator (https://dr-lee.shinyapps.io/osteosarcoma/), which indicated very good consistency, predictive power, and clinical application value.

A novel clinical tool to predict cancer-specific survival in patients with primary pelvic sarcomas: A large population-based retrospective cohort study

BACKGROUND

Primary osseous sarcoma of the pelvis is rare and has a particularly sinister outcome. This study aims to identify independent prognostic factors of cancer-specific survival (CSS) in patients with primary pelvic sarcoma (PS) and develop a nomogram to predict 3-, 5-, and 10-year probability of CSS in these patients.

METHODS

The Surveillance, Epidemiology, and End Results (SEER) database was used to identify 416 patients with primary PS, who were divided into two groups: a training cohort and a validation cohort. Univariate and multivariate Cox analyses were used to screen independent prognostic factors in patients with primary PS. Based on these independent prognostic factors, a prognostic nomogram was developed to predict 3-, 5-, and 10-year probability of CSS. The nomogram's predictive performance and clinical value were evaluated using the calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Finally, a mortality risk stratification system was developed.

RESULTS

Tumor size, tumor stage, histological type, surgery, and chemotherapy were identified as independent prognostic factors for the CSS of primary PS patients. Based on these factors, a nomogram was created to predict the 3-, 5-, and 10-year probability of CSS in these patients. The calibration curve, ROC, and DCA indicated that the nomogram performed well and was appropriate for clinical use, with 3-, 5-, and 10-year areas under ROC curve all higher than 0.800. Furthermore, the nomogram-based mortality risk stratification system could effectively divide these patients into three risk subgroups.

CONCLUSIONS

The nomogram constructed in this study could accurately predict 3-, 5-, and 10-year probability of CSS in patients with primary PS. Clinicians can use the nomogram to categorize these patients into risk subgroups and provide personalized treatment plans.

A predictive model with a risk-classification system for cancer-specific survival in patients with primary osteosarcoma of long bone

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Seven clinical factors were significantly related to the prognosis of patients with long bone osteosarcoma.

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The established nomogram can help surgeons evaluate the prognosis of osteosarcoma patients in the most common sites.

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High-risk individuals can be identified through risk-stratification system.

Background

Osteosarcoma (OS), most commonly occurring in long bone, is a group of malignant tumors with high incidence in adolescents. No individualized model has been developed to predict the prognosis of primary long bone osteosarcoma (PLBOS) and the current AJCC TNM staging system lacks accuracy in prognosis prediction. We aimed to develop a nomogram based on the clinicopathological factors affecting the prognosis of PLBOS patients to help clinicians predict the cancer-specific survival (CSS) of PLBOS patients.

Method

We studied 1199 PLBOS patients from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and randomly divided the dataset into training and validation cohorts at a proportion of 7:3. Independent prognostic factors determined by stepwise multivariate Cox analysis were included in the nomogram and risk-stratification system. C-index, calibration curve, and decision curve analysis (DCA) were used to verify the performance of the nomogram.

Results

Age, Histological type, Surgery of primary site, Tumor size, Local extension, Regional lymph node (LN) invasion, and Distant metastasis were identified as independent prognostic factors. C-indexes, calibration curves and DCAs of the nomogram indicating that the nomogram had good discrimination and validity. The risk-stratification system based on the nomogram showed significant differences (P < 0.05) in CSS among different risk groups.

Conclusion

We established a nomogram with risk-stratification system to predict CSS in PLBOS patients and demonstrated that the nomogram had good performance. This model can help clinicians evaluate prognoses, identify high-risk individuals, and give individualized treatment recommendation of PLBOS patients.

Prognosis of radiotherapy in medullary thyroid carcinoma patients without distant metastasis

Background

Medullary thyroid carcinoma (MTC) is an advanced disease with a poor prognosis. Although radiotherapy is widely utilized to treat MTC, it is still controversial. MTC patients without distant metastases have not been investigated to explore indications for adjuvant radiotherapy. This study aims to investigate the impact of radiotherapy on the survival of MTC patients without distant metastases.

Methods

Data of MTC patients without distant metastasis who underwent total thyroidectomy between 2010 and 2015 were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Propensity score matching was performed to analyze the relationship between radiotherapy and cancer-specific survival (CSS).

Results

Seventy-four of 718 MTC patients without distant metastases received radiotherapy and underwent total thyroidectomy. A total of 148 patients were screened via propensity score matching analysis. Multivariate Cox regression indicated that factors including age, sex, radiotherapy and chemotherapy were independent predictors of CSS. Based on these factors, MTC patients without distant metastasis were classified into two risk groups using a nomogram and risk classification system. The C-index of the nomogram was 0.791. The calibration curves showed good consistency of CSS between the actual observation and the nomogram prediction, and decision curve analysis (DCA) showed great clinical usefulness of the nomogram. The three-year CSS of the radiotherapy group was 85.3%, and that of the surgery group was 95%. Particularly, compared with the surgery group, the three-year CSS of subgroups of the radiotherapy group, including male patients and those aged >48 years, was decreased.

Conclusions

Radiotherapy results in worse CSS for MTC patients without distant metastases. To maximize benefits, decisions about individual radiotherapy should weigh its advantages and disadvantages.

Current Status and Prospects of Clinical Treatment of Osteosarcoma

Osteosarcoma, one of the common malignant tumors in the skeletal system, originates in mesenchymal tissue, and the most susceptible area of occurrence is the metaphysis with its abundant blood supply. Tumors are characterized by highly malignant spindle stromal cells that can produce bone-like tissue. Most of the osteosarcoma are primary, and a few are secondary. Osteosarcoma occurs primarily in children and adolescents undergoing vigorous bone growth and development. Most cases involve rapid tumor development and early blood metastasis. In recent years, research has grown in the areas of molecular biology, imaging medicine, biological materials, applied anatomy, surgical techniques, biomechanics, and comprehensive treatment of tumors. With developments in molecular biology and tissue bioengineering, treatment methods have also made great progress, especially in comprehensive limb salvage treatment, which significantly enhances the quality of life after surgery and improves the 5-year survival rate of patients with malignant tumors. This article provides a review of limb salvage, immunotherapy, gene therapy, and targeted therapy from traditional amputation to neoadjuvant chemotherapy, providing a reference for current clinical treatments for osteosarcoma.

Limb-salvage surgery using personalized 3D-printed porous tantalum prosthesis for distal radial osteosarcoma: A case report

RATIONALE

Three-dimensional (3D) printing has been widely utilized for treating the tumors of bone and soft tissue. We herewith report a unique case of distal radial osteosarcoma who was treated with a 3D printed porous tantalum prosthesis.Patient concerns: A 58-year-old Chinese male patient presented to our clinic complaining about a 6-month history of a progressive pain at his right hand, associated with a growing lump 2 months later.

DIAGNOSIS

Osteosarcoma of distal radius confirmed by percutaneous biopsy and tumor biopsy.

INTERVENTIONS

A limb-salvage surgery was performed with a 3D printed porous tantalum prosthesis, combined with the postoperative chemotherapy for 4 cycles.

OUTCOMES

At 2-year follow-up, complete pain relief and satisfactory functional recovery of his right wrist were observed.

LESSONS

Personalized 3D printed prosthesis is an effective and feasible method for treating the osteosarcoma and reconstruction of complex bone defects.

Functional interplay between long non-coding RNAs and the Wnt signaling cascade in osteosarcoma

Osteosarcoma is a common and highly malignant bone tumor among children, adolescents and young adults. However, the underlying molecular mechanisms remain largely unexplored. LncRNAs are transcripts with no or limited protein-coding capacity in human genomes, and have been demonstrated to play crucial functions in initiation, progression, therapeutic resistance, recurrence and metastasis of tumor. Considerable studies revealed a dysregulated lncRNA expression pattern in osteosarcoma, which may act as oncogenes or suppressors to regulate osteosarcoma progression. Wnt signaling pathway is an important cascade in tumorigenesis by modulation of pleiotropic biological functions including cell proliferation, apoptosis, differentiation, stemness, genetic stability and chemoresistance. Hyperactivation or deficiency of key effectors in Wnt cascade is a common event in many osteosarcoma patients. Recently, increasing evidences have suggested that lncRNAs could interplay with component of Wnt pathway, and thereby contribute to osteosarcoma onset, progression and dissemination. In this review, we briefly summarize Wnt signaling-related lncRNAs in osteosarcoma progression, aiming to gain insights into their underlying crosstalk as well as clinical application in osteosarcoma therapeutic modalities.

Prognostic factors of chondroblastic osteosarcoma and nomogram development for prediction: A population-based, STROBE-compliant study

The present study aimed to develop nomograms to predict survival in patients with chondroblastic osteosarcoma (COS).An analysis was conducted of 320 cases of COS collected from the surveillance, epidemiology, and end results (SEER) database between 2004 and 2015. Independent prognostic factors were screened using univariate and multivariate Cox analyses. Subsequently, nomograms were established to predict the patients' cancer-specific survival (CSS) and overall survival (OS) rates. The prediction accuracy and discriminative ability of the nomograms were examined using calibration curves and the concordance index (C-index).As revealed in the univariate and multivariate Cox regression analysis, age, tumor size, the primary site, the presence of metastasis, a history of having undergone surgery, and a history of having received radiotherapy were found to be independent prognostic factors associated with survival in patients with COS (all P < .05). Furthermore, age >39 years, the presence of distant metastasis, no history of having undergone any surgery, and tumor size >103 mm were found to be associated with poor prognosis in patients, while the primary site of the mandible and no history of having undergone radiotherapy showed associations with a more favorable prognosis in patients. Next, nomograms were constructed to predict the OS and CSS in patients with COS.We constructed nomograms that can provide accurate survival predictions in patients with chondroblastic osteosarcoma. These nomograms can help surgeons customize the treatment strategies for patients with chondroblastic osteosarcoma.

LncRNA prostate androgen-regulated transcript 1 (PART 1) functions as an oncogene in osteosarcoma via sponging miR-20b-5p to upregulate BAMBI

Background

Osteosarcoma (OS) is an aggressive bone cancer that most commonly affects adolescents and children. Emerging studies have shown that long noncoding RNA (lncRNA) performs essential roles in the occurrence and development of many tumors. Prostate androgen-regulated transcript 1 (PART 1) has been reported as a tumor oncogene; despite this, the mechanisms underlying its involvement in OS are unclear.

Methods

OS and paired normal tissue samples were obtained, and gene expressions were detected by real time-quantitative polymerase chain reaction (RT-qPCR). The functions of PART 1 in OS cell proliferation, invasion, and migration were determined by Cell Counting Kit-8 (CCK-8) and Transwell assays. Furthermore, the binding sites of PART 1 and miR-20b-5p as well as those between miR-20b-5p and bone morphogenic protein and activin membrane-bound inhibitor homolog (BAMBI) were verified by bioinformatics analysis and dual-luciferase reporter assay.

Results

Our study found obvious overexpression of PART 1 in OS tissues and cells. Furthermore, PART 1 overexpression facilitated OS cell proliferation, invasion, and migration. Further mechanistic investigations revealed that PART 1 could sponge to miR-20b-5p, which was expressed at a low level in OS tissues and cells. Importantly, miR-20b-5p overexpression inhibited OS cell proliferation, invasion, and migration. Additionally, BAMBI was confirmed as a downstream gene of miR-20b-5p, and its expression was reversely modulated by miR-20b-5p and positively modulated by PART 1. Rescue experiments suggested that BAMBI was involved in PART 1-mediated promotion of OS progression.

Conclusions

PART 1 serves as a competing endogenous RNA to promote OS tumorigenesis via its regulation of the miR-20b-5p/BAMBI axis, which may provide a promising therapeutic biomarkers for OS patients.