【佳學(xué)基因檢測】m1A/m5C/m6A 相關(guān) lncRNA 特征在骨肉瘤中的預(yù)后價(jià)值和免疫景觀

靶向藥一旦停藥會怎樣省錢要點(diǎn)

查重分析《腫瘤治療效果與基因檢測結(jié)果的相關(guān)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(guān) lncRNA 特征在骨肉瘤中的預(yù)后價(jià)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(jìn)了腫瘤的正確治療與個(gè)性化用藥的發(fā)展，進(jìn)一步強(qiáng)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(guān)鍵詞：

腫瘤靶向治療基因檢測臨床應(yīng)用結(jié)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(xué)過程。然而，目前還沒有關(guān)于骨肉瘤與 m1A/m5C/m6A 相關(guān)長非編碼 RNA (lncRNAs) 之間關(guān)系的研究。患者和方法：這里，來自 Therapeutical Applicable Research to Generate Effective Treatments (TARGET) 的骨肉瘤表達(dá)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(guān)的 ER 相關(guān) lncRNA。然后，應(yīng)用 Lasso 懲罰 Cox 回歸分析來構(gòu)建 lncRNAs 風(fēng)險(xiǎn)特征。同時(shí)，根據(jù)已識別的 m1A/m5C/m6A 相關(guān) lncRNA，將患者分為兩個(gè)集群。進(jìn)一步評估了已識別特征和簇的預(yù)后價(jià)值和免疫景觀。結(jié)果：兩個(gè) m1A/m5C/m6A 相關(guān)的 lncRNA 被納入我們的風(fēng)險(xiǎn)特征。功能分析表明，預(yù)后模型與患者生存、癌癥轉(zhuǎn)移和生長相關(guān)。同時(shí)，特征模型與免疫細(xì)胞、免疫微環(huán)境以及幾個(gè)免疫檢查點(diǎn)基因的浸潤顯著相關(guān)。對于 lncRNAs 簇也檢測到了類似的結(jié)果，它們與免疫浸潤、癌癥微環(huán)境和免疫相關(guān)基因顯著相關(guān)，有助于預(yù)測患者的預(yù)后。此外，我們的風(fēng)險(xiǎn)特征和集群可能有助于指導(dǎo)免疫治療藥物在骨肉瘤患者中的應(yīng)用。最后，建立了基于風(fēng)險(xiǎn)評分的列線圖。結(jié)論：總體而言，生成了基于兩個(gè) m1A/m5C/m6A 相關(guān) lncRNA 的風(fēng)險(xiǎn)特征，并為骨肉瘤患者的預(yù)后和免疫狀況提供了預(yù)測價(jià)值。該特征可進(jìn)一步用于開發(fā)新的骨肉瘤治療策略。

腫瘤發(fā)生與反復(fù)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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