Q-omics provides the consensus-scored ERC2-IT1 profile across patient tissues and cancer cell-line models. ERC2-IT1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ERC2-IT1 is differentially expressed in 2, with the highest sampling consensus in LUAD. Additionally, ERC2-IT1 RNA expression shows 13,366 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LUAD, and GBM as cancer lineages where ERC2-IT1 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 ERC2-IT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERC2-IT1 survival associations across molecular data types. ERC2-IT1 RNA expression shows survival associations in the most cancer types (19). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ERC2-IT1 RNA expression–survival associations across cancer types. High ERC2-IT1 expression shows unfavorable associations in UVM, READ and COAD, but favorable associations in CESC, THCA and BRCA. The UVM 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 UVM as the clearest survival context for ERC2-IT1 RNA expression.
This table summarizes ERC2-IT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for ERC2-IT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERC2-IT1 shows lower tumor expression in THCA and higher tumor expression in LUAD. The LUAD box plot shows higher ERC2-IT1 RNA expression in tumor versus normal tissue (log2 FC = +0.033, t-test p = .029).
This table shows molecular features associated with ERC2-IT1 in patient tissues and cancer cell lines. In patient samples, ERC2-IT1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ERC2-IT1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in NCI60_ALL.
