Q-omics provides the consensus-scored EIF2S1 profile across patient tissues and cancer cell-line models. EIF2S1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EIF2S1 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, EIF2S1 protein abundance shows 29,952 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight ACC, HNSC, and LUAD as cancer lineages where EIF2S1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for EIF2S1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF2S1 survival associations across molecular data types. EIF2S1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (1) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF2S1 RNA expression–survival associations across cancer types. High EIF2S1 expression shows unfavorable associations in ACC, HNSC, UVM, BLCA and KICH, but favorable associations in KIRC. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for EIF2S1 RNA expression.
This table summarizes EIF2S1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for EIF2S1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF2S1 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, COAD, STAD and BRCA. The HNSC box plot shows higher EIF2S1 RNA expression in tumor versus normal tissue (log2 FC = +1.105, t-test p < 0.001).
This table shows molecular features associated with EIF2S1 in patient tissues and cancer cell lines. In patient samples, EIF2S1 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, EIF2S1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
