Q-omics provides the consensus-scored KRT17P2 profile across patient tissues and cancer cell-line models. KRT17P2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, KRT17P2 is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, KRT17P2 RNA expression shows 9,964 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where KRT17P2 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 KRT17P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KRT17P2 survival associations across molecular data types. KRT17P2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KRT17P2 RNA expression–survival associations across cancer types. High KRT17P2 expression shows unfavorable associations in KIRC, UCEC, PAAD, COAD and LIHC, but favorable associations in UCS. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for KRT17P2 RNA expression.
This table summarizes KRT17P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for KRT17P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KRT17P2 shows lower tumor expression in BRCA, PRAD and COAD and higher tumor expression in HNSC, LUSC and LUAD. The HNSC box plot shows higher KRT17P2 RNA expression in tumor versus normal tissue (log2 FC = +0.847, t-test p < 0.001).
This table shows molecular features associated with KRT17P2 in patient tissues and cancer cell lines. In patient samples, KRT17P2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, KRT17P2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE.
