Q-omics provides the consensus-scored EIF3H profile across patient tissues and cancer cell-line models. EIF3H expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, EIF3H is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, EIF3H protein abundance shows 27,187 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight CESC, KIRC, and LUAD as cancer lineages where EIF3H 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 EIF3H — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EIF3H survival associations across molecular data types. EIF3H RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EIF3H RNA expression–survival associations across cancer types. High EIF3H expression shows unfavorable associations in CESC, KIRP, LIHC, ACC, UVM and HNSC. The CESC 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 CESC as the clearest survival context for EIF3H RNA expression.
This table summarizes EIF3H tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for EIF3H. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EIF3H shows higher tumor expression in KIRC, HNSC, COAD, LIHC, BRCA and LUAD. The KIRC box plot shows higher EIF3H RNA expression in tumor versus normal tissue (log2 FC = +0.453, t-test p < 0.001).
This table shows molecular features associated with EIF3H in patient tissues and cancer cell lines. In patient samples, EIF3H 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, EIF3H RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and UPPER_AERODIGESTIVE_TRACT.
