<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/GSE292nnn/GSE292421/</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Transcriptomics</omics_type><species>Homo sapiens</species><gds_type>Expression profiling by high throughput sequencing</gds_type><full_dataset_link>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE292421</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>A pan-cancer immune and genomic feature-based classification of tumor microenvironment and resistance to immunotherapy</name><description>The tumor microenvironment (TME) profoundly influences responses to immune checkpoint blockade (ICB) therapies, however characterizing its complexity has been challenging. While the immune-inflamed, immune-excluded, and immune-desert T cell immunophenotypes are commonly used to classify the TME, their association with clinical outcomes to ICBs remains inconsistent. Here we demonstrated that integrating T cell immunophenotypes and tumor mutational burden (TMB) enables a more precise stratification of tumors into five distinct subtypes: immune-inflamed phenotype with high TMB (TMB-H), immune-inflamed phenotype with low TMB (TMB-L), TMB-H excluded phenotype, TMB-L excluded phenotype, and desert phenotype. Subsequently, we revealed the underlying mechanisms of tumor resistance to ICBs of each phenotype within the novel classification and elucidate several combination treatment approaches aiming at overcoming these inherent resistance mechanisms. Our study suggested that tailored combination therapy regimens addressing distinct patterns of immune resistance in different TME subtypes hold promise for enhancing immunotherapy efficacy</description><dates><publication>2026/05/22</publication></dates><accession>GSE292421</accession><cross_references><GSM>GSM8858688</GSM><GSM>GSM8858689</GSM><GSM>GSM8858686</GSM><GSM>GSM8858687</GSM><GSM>GSM9639169</GSM><GSM>GSM9639164</GSM><GSM>GSM8858680</GSM><GSM>GSM9639163</GSM><GSM>GSM8858681</GSM><GSM>GSM9639162</GSM><GSM>GSM9639161</GSM><GSM>GSM9639168</GSM><GSM>GSM8858684</GSM><GSM>GSM8858685</GSM><GSM>GSM9639167</GSM><GSM>GSM8858682</GSM><GSM>GSM9639166</GSM><GSM>GSM9639165</GSM><GSM>GSM8858683</GSM><GSM>GSM9639160</GSM><GSM>GSM8858677</GSM><GSM>GSM8858678</GSM><GSM>GSM8858675</GSM><GSM>GSM8858676</GSM><GSM>GSM8858679</GSM><GSM>GSM9639175</GSM><GSM>GSM9639174</GSM><GSM>GSM9639173</GSM><GSM>GSM9639172</GSM><GSM>GSM9639179</GSM><GSM>GSM8858673</GSM><GSM>GSM8858674</GSM><GSM>GSM9639178</GSM><GSM>GSM8858671</GSM><GSM>GSM9639177</GSM><GSM>GSM9639176</GSM><GSM>GSM8858672</GSM><GSM>GSM9639171</GSM><GSM>GSM9639170</GSM><GSM>GSM9639180</GSM><GSM>GSM9639159</GSM><GSM>GSM9639158</GSM><GSM>GSM8858691</GSM><GSM>GSM9639153</GSM><GSM>GSM9639152</GSM><GSM>GSM9639151</GSM><GSM>GSM8858690</GSM><GSM>GSM9639157</GSM><GSM>GSM9639156</GSM><GSM>GSM9639155</GSM><GSM>GSM9639154</GSM><GPL>34281</GPL><GSE>292421</GSE><taxon>Homo sapiens</taxon></cross_references></HashMap>