Q-omics provides the consensus-scored PTTG1IP profile across patient tissues and cancer cell-line models. PTTG1IP expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PTTG1IP is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, PTTG1IP RNA expression shows 18,973 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where PTTG1IP 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 PTTG1IP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PTTG1IP survival associations across molecular data types. PTTG1IP RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PTTG1IP RNA expression–survival associations across cancer types. High PTTG1IP expression shows unfavorable associations in HNSC, BRCA, ACC, CESC and LIHC, but favorable associations in KIRC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for PTTG1IP RNA expression.
This table summarizes PTTG1IP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PTTG1IP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTTG1IP shows lower tumor expression in KICH and COAD and higher tumor expression in HNSC, KIRC, LIHC and BRCA. The HNSC box plot shows higher PTTG1IP RNA expression in tumor versus normal tissue (log2 FC = +0.820, t-test p < 0.001).
This table shows molecular features associated with PTTG1IP in patient tissues and cancer cell lines. In patient samples, PTTG1IP shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PTTG1IP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
