<HashMap><database>GEO</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Other>ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE347nnn/GSE347344/</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Methylation profiling</omics_type><species>Homo sapiens</species><gds_type>Methylation profiling by genome tiling array</gds_type><full_dataset_link>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE347344</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>Epigenetic Age Acceleration Enhances Prediction of Overall Survival in Early-Stage Non-Small Cell Lung Cancer</name><description>Epigenetic age, influenced by environmental factors like smoking, predicts mortality in general populations but remains under-explored in early-stage lung cancer. We analyzed blood DNA methylation from 75 Boston Lung Cancer Study participants with early-stage non-small cell lung cancer (NSCLC), of whom 63 died during follow-up. Epigenetic age acceleration (EAA) was estimated using Horvath, Hannum, PhenoAge, and GrimAge2 clocks and assessed using Cox models and random survival forests (RSF). Across clocks, EAA significantly predicted survival in early-stage NSCLC. GrimAge2 EAA achieved the highest predictive accuracy (C-index=0.73±0.04) and emerged as the dominant predictor of survival among RSF models (variable importance=5.7%), surpassing smoking and age. GrimAge2 EAA showed a non-linear association with mortality in which current smokers had >10% higher predicted mortality risk than former or never smokers at equivalent EAA, a pattern confirmed in Kaplan-Meier analyses. GrimAge2 EAA is a promising biomarker for personalizing risk stratification alongside traditional clinical factors.</description><dates><publication>2026/09/19</publication></dates><accession>GSE347344</accession><cross_references><GSM>GSM10051195</GSM><GSM>GSM10051151</GSM><GSM>GSM10051150</GSM><GSM>GSM10051194</GSM><GSM>GSM10051153</GSM><GSM>GSM10051196</GSM><GSM>GSM10051152</GSM><GSM>GSM10051155</GSM><GSM>GSM10051154</GSM><GSM>GSM10051157</GSM><GSM>GSM10051156</GSM><GSM>GSM10051159</GSM><GSM>GSM10051158</GSM><GSM>GSM10051160</GSM><GSM>GSM10051162</GSM><GSM>GSM10051161</GSM><GSM>GSM10051164</GSM><GSM>GSM10051163</GSM><GSM>GSM10051166</GSM><GSM>GSM10051122</GSM><GSM>GSM10051165</GSM><GSM>GSM10051124</GSM><GSM>GSM10051168</GSM><GSM>GSM10051167</GSM><GSM>GSM10051123</GSM><GSM>GSM10051126</GSM><GSM>GSM10051169</GSM><GSM>GSM10051125</GSM><GSM>GSM10051128</GSM><GSM>GSM10051127</GSM><GSM>GSM10051129</GSM><GSM>GSM10051171</GSM><GSM>GSM10051170</GSM><GSM>GSM10051173</GSM><GSM>GSM10051172</GSM><GSM>GSM10051175</GSM><GSM>GSM10051131</GSM><GSM>GSM10051130</GSM><GSM>GSM10051174</GSM><GSM>GSM10051133</GSM><GSM>GSM10051177</GSM><GSM>GSM10051176</GSM><GSM>GSM10051132</GSM><GSM>GSM10051135</GSM><GSM>GSM10051179</GSM><GSM>GSM10051178</GSM><GSM>GSM10051134</GSM><GSM>GSM10051137</GSM><GSM>GSM10051136</GSM><GSM>GSM10051139</GSM><GSM>GSM10051138</GSM><GSM>GSM10051180</GSM><GSM>GSM10051182</GSM><GSM>GSM10051181</GSM><GSM>GSM10051184</GSM><GSM>GSM10051140</GSM><GSM>GSM10051183</GSM><GSM>GSM10051142</GSM><GSM>GSM10051186</GSM><GSM>GSM10051141</GSM><GSM>GSM10051185</GSM><GSM>GSM10051144</GSM><GSM>GSM10051188</GSM><GSM>GSM10051187</GSM><GSM>GSM10051143</GSM><GSM>GSM10051146</GSM><GSM>GSM10051189</GSM><GSM>GSM10051145</GSM><GSM>GSM10051148</GSM><GSM>GSM10051147</GSM><GSM>GSM10051149</GSM><GSM>GSM10051191</GSM><GSM>GSM10051190</GSM><GSM>GSM10051193</GSM><GSM>GSM10051192</GSM><GPL>21145</GPL><GSE>347344</GSE><taxon>Homo sapiens</taxon></cross_references></HashMap>