【佳學基因檢測】m1A/m5C/m6A 相關 lncRNA 特征在骨肉瘤中的預后價值和免疫景觀

靶向藥一旦停藥會怎樣省錢要點

查重分析《腫瘤治療效果與基因檢測結果的相關性》《Eur Rev Med Pharmacol Sci》在.?2022 Aug;26(16):5868-5883.發(fā)表了一篇題目為《m1A/m5C/m6A 相關 lncRNA 特征在骨肉瘤中的預后價值和免疫景觀》腫瘤靶向藥物治療基因檢測臨床研究文章。該研究由Z-Y Wu,?Z-Y Shi等完成。促進了腫瘤的正確治療與個性化用藥的發(fā)展，進一步強調(diào)了基因信息檢測與分析的重要性。

腫瘤靶向藥物及正確治療臨床研究內(nèi)容關鍵詞：

腫瘤靶向治療基因檢測臨床應用結果

目的：RNA甲基化修飾主要包括N1-甲基腺苷（m1A）、5-甲基胞嘧啶（m5C）和N6-甲基腺苷（m6A），廣泛存在于骨肉瘤中并參與癌癥的生物學過程。然而，目前還沒有關于骨肉瘤與 m1A/m5C/m6A 相關長非編碼 RNA (lncRNAs) 之間關系的研究?；颊吆头椒ǎ哼@里，來自 Therapeutical Applicable Research to Generate Effective Treatments (TARGET) 的骨肉瘤表達數(shù)據(jù)) 數(shù)據(jù)庫被檢索以識別與骨肉瘤患者的總生存期 (總生存期) 相關的 ER 相關 lncRNA。然后，應用 Lasso 懲罰 Cox 回歸分析來構建 lncRNAs 風險特征。同時，根據(jù)已識別的 m1A/m5C/m6A 相關 lncRNA，將患者分為兩個集群。進一步評估了已識別特征和簇的預后價值和免疫景觀。結果：兩個 m1A/m5C/m6A 相關的 lncRNA 被納入我們的風險特征。功能分析表明，預后模型與患者生存、癌癥轉(zhuǎn)移和生長相關。同時，特征模型與免疫細胞、免疫微環(huán)境以及幾個免疫檢查點基因的浸潤顯著相關。對于 lncRNAs 簇也檢測到了類似的結果，它們與免疫浸潤、癌癥微環(huán)境和免疫相關基因顯著相關，有助于預測患者的預后。此外，我們的風險特征和集群可能有助于指導免疫治療藥物在骨肉瘤患者中的應用。最后，建立了基于風險評分的列線圖。結論：總體而言，生成了基于兩個 m1A/m5C/m6A 相關 lncRNA 的風險特征，并為骨肉瘤患者的預后和免疫狀況提供了預測價值。該特征可進一步用于開發(fā)新的骨肉瘤治療策略。

腫瘤發(fā)生與反復轉(zhuǎn)移國際數(shù)據(jù)庫描述：

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.

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