Q-omics provides the consensus-scored TIGD1 profile across patient tissues and cancer cell-line models. TIGD1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TIGD1 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, TIGD1 RNA expression shows 20,363 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, COAD, and UVM as cancer lineages where TIGD1 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 TIGD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TIGD1 survival associations across molecular data types. TIGD1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TIGD1 RNA expression–survival associations across cancer types. High TIGD1 expression shows unfavorable associations in KIRC, ACC, COAD and LIHC, but favorable associations in UCS and OV. The KIRC 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 KIRC as the clearest survival context for TIGD1 RNA expression.
This table summarizes TIGD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for TIGD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TIGD1 shows lower tumor expression in KICH and higher tumor expression in COAD, HNSC, LIHC, LUAD and STAD. The COAD box plot shows higher TIGD1 RNA expression in tumor versus normal tissue (log2 FC = +1.184, t-test p < 0.001).
This table shows molecular features associated with TIGD1 in patient tissues and cancer cell lines. In patient samples, TIGD1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, TIGD1 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 BREAST and BLOOD_Leukemia.
