■急性髓系白血病(AML)表现出广泛的表型表现,进展模式,和对免疫疗法的异质反应,提示涉及复杂的免疫生物学机制。这项研究旨在通过整合癌症驱动基因来开发AML的综合预后模型。随着疾病的临床和表型特征,并评估其对免疫治疗反应的影响。
■通过使用癌症基因组图谱(TCGA)的数据筛选初级效应子和相应的基因对,鉴定了与存活相关的关键致癌驱动基因。通过单变量Cox比例风险回归分析。这使用数据集GSE37642独立地验证。使用LASSO回归进一步精制初级效应基因。转录组分析使用多变量Cox回归进行量化,得出的预后评分随后得到验证.最后,建立了多元Cox回归模型,结合转录组评分和临床参数,如年龄,性别,和法国-美国-英国(FAB)分类亚型。开发并随后验证了“AML总体生存评分的准确预测模型”(APMAO)。对功能途径富集进行了研究,基因突变景观的改变,以及与不同APMAO评分相关的免疫细胞浸润程度。为了进一步研究APMAO评分作为癌症免疫治疗反应性的预测生物标志物的潜力,我们进行了一系列的分析。这些包括检查与免疫检查点相关的基因的表达谱,干扰素-γ信号通路,和M6A法规。此外,我们探讨了这些基因表达模式与肿瘤免疫功能障碍和排斥(TIDE)功能障碍评分之间的关系.
■通过筛选95个与存活相关的癌症基因和313个相互作用的基因对,七个基因(ACSL6,MAP3K1,CHIC2,HIP1,PTPN6,TFEB,和DAXX)被确定,导致转录分数的推导。年龄和转录分数是Cox回归分析中的重要预测因子,并且是最终APMAO模型发展的组成部分,表现出大于0.75的AUC,并成功验证。在转录评分的分布中观察到显著的差异,年龄,细胞遗传学风险类别,和法国-美国-英国(FAB)分类之间的高和低APMAO组。具有高APMAO评分的样品在NFKB中表现出显著更高的突变率和途径富集,TNF,JAK-STAT,和NOTCH信令。此外,免疫细胞浸润和免疫检查点表达的变化,干扰素-γ途径的激活,并注意到m6A调节剂的表达,包括CD160,m6A表达之间的负相关,和APMAO分数。
整合转录和临床参数的联合APMAO评分在预测AML生存结果方面显示出稳健的预后性能。它与独特的表型特征有关,独特的免疫和突变谱,以及与免疫治疗敏感性相关的标志物的表达模式。这些观察结果表明,促进精准免疫疗法的潜力,并倡导在即将进行的临床试验中进行探索。
UNASSIGNED: Acute Myeloid Leukemia (AML) exhibits a wide array of phenotypic manifestations, progression patterns, and heterogeneous responses to immunotherapies, suggesting involvement of complex immunobiological mechanisms. This investigation aimed to develop an integrated prognostic model for AML by incorporating cancer driver genes, along with clinical and phenotypic characteristics of the disease, and to assess its implications for immunotherapy responsiveness.
UNASSIGNED: Critical oncogenic driver genes linked to survival were identified by screening primary effector and corresponding gene pairs using data from The Cancer Genome Atlas (TCGA), through univariate Cox proportional hazard regression analysis. This was independently verified using dataset GSE37642. Primary effector genes were further refined using LASSO regression. Transcriptomic profiling was quantified using multivariate Cox regression, and the derived prognostic score was subsequently validated. Finally, a multivariate Cox regression model was developed, incorporating the transcriptomic score along with clinical parameters such as age, gender, and French-American-British (FAB) classification subtype. The \'Accurate Prediction Model of AML Overall Survival Score\' (APMAO) was developed and subsequently validated. Investigations were conducted into functional pathway enrichment, alterations in the gene mutational landscape, and the extent of immune cell infiltration associated with varying APMAO scores. To further investigate the potential of APMAO scores as a predictive biomarker for responsiveness to cancer immunotherapy, we conducted a series of analyses. These included examining the expression profiles of genes related to immune checkpoints, the interferon-gamma signaling pathway, and m6A regulation. Additionally, we explored the relationship between these gene expression patterns and the Tumor Immune Dysfunction and Exclusion (TIDE) dysfunction scores.
UNASSIGNED: Through the screening of 95 cancer genes associated with survival and 313 interacting gene pairs, seven genes (ACSL6, MAP3K1, CHIC2, HIP1, PTPN6, TFEB, and DAXX) were identified, leading to the derivation of a transcriptional score. Age and the transcriptional score were significant predictors in Cox regression analysis and were integral to the development of the final APMAO model, which exhibited an AUC greater than 0.75 and was successfully validated. Notable differences were observed in the distribution of the transcriptional score, age, cytogenetic risk categories, and French-American-British (FAB) classification between high and low APMAO groups. Samples with high APMAO scores demonstrated significantly higher mutation rates and pathway enrichments in NFKB, TNF, JAK-STAT, and NOTCH signaling. Additionally, variations in immune cell infiltration and immune checkpoint expression, activation of the interferon-γ pathway, and expression of m6A regulators were noted, including a negative correlation between CD160, m6A expression, and APMAO scores.
UNASSIGNED: The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes. It was linked to unique phenotypic characteristics, distinctive immune and mutational profiles, and patterns of expression for markers related to immunotherapy sensitivity. These observations suggest the potential for facilitating precision immunotherapy and advocate for its exploration in upcoming clinical trials.