{'fraction_non_alphanumeric': 0.031018518518518518, 'fraction_numerical': 0.009722222222222222, 'mean_word_length': 5.774294670846395, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The prognostic value and immune landscapes of m1A/m5C/m6A-associated lncRNA signature in osteosarcoma.

OBJECTIVE
RNA methylation modifications, mainly including N1-methyladenosine (m1A), 5-methylcytosine (m5C), and N6-methyladenosine (m6A), are widely existed in osteosarcoma and involved in the biological processes of cancers. However, there is still no study regarding the relationship between osteosarcoma and m1A/m5C/m6A-associated long non-coding RNAs (lncRNAs).


PATIENTS AND METHODS
Here, expression data of osteosarcoma from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database were retrieved to identify ER-related lncRNAs associated with the overall survival (OS) of osteosarcoma patients. Then, Lasso penalized Cox regression analysis was applied to construct a lncRNAs risk signature. Meanwhile, patients were stratified into two clusters based on the identified m1A/m5C/m6A-associated lncRNAs. The prognostic value and immune landscape of the identified signature and clusters were further evaluated.


RESULTS
Two m1A/m5C/m6A-associated lncRNAs were incorporated into our risk signature. The functional analyses indicated that the prognostic model was correlated with patient survival, and cancer metastasis and growth. Meanwhile, the signature model was significantly associated with the infiltration of immune cells, immune microenvironment, as well as several immune checkpoint genes. Similar results were detected for the lncRNAs clusters, which were significantly correlated with immune infiltration, cancer microenvironment, and immune-associated genes, and contributed to predicting the prognosis of patients. Moreover, our risk signature and clusters might help guide the application of immunotherapeutic drugs for osteosarcoma patients. Finally, a nomogram based on the risk score was established.


CONCLUSIONS
Overall, a risk signature based on two m1A/m5C/m6A-associated lncRNAs was generated and presented predictive value for the prognosis and immune landscapes of osteosarcoma patients. This signature can be further used in the development of novel therapeutic strategies for osteosarcoma.