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We sought to systematically characterize the pan\u2010cancer landscape and molecular hallmarks of T\u2010cell dysfunction for the purpose of precision immunotherapy. Here, we defined a transcriptional signature for T\u2010cell exhaustion through analyzing differential gene expression between PD\u20101\u2010high and PD\u20101\u2010negative CD8<jats:sup>+<\/jats:sup> T lymphocytes from primary non\u2010small cell lung cancer (NSCLC), followed by positive correlation tests with <jats:italic>PDCD1<\/jats:italic> in TCGA lung carcinomas. A 78\u2010gene signature for exhausted CD8<jats:sup>+<\/jats:sup> T cells (GET) was identified and validated to reflect dysfunctional immune state spanning different species and disease models. We discovered that GET estimation significantly correlated with intratumoral immune cytolytic activity (CYT) and T\u2010cell\u2010inflamed gene expression profile (GEP) across 30 solid tumor types. Miscellaneous tumor\u2010intrinsic and \u2010extrinsic properties, in particular leukocyte proportions, genomic abnormalities, specific mutational signatures, and signaling pathways, were notably associated with GET levels. Furthermore, higher GET expression predicted an increased likelihood of clinical response to immune checkpoint inhibitors. These findings highlight the interrelation between T\u2010cell exhaustion and immune cytolytic activity at the pan\u2010cancer scale. The resulting inflamed tumor microenvironment may further crosstalk with other molecular and clinicopathological factors, which should be properly considered during immunotherapy biomarker development. \u00a9 2020 Pathological Society of Great Britain and Ireland. 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