Q-omics provides the consensus-scored TMEM165 profile across patient tissues and cancer cell-line models. TMEM165 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, TMEM165 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, TMEM165 RNA expression shows 19,485 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight UVM, BLCA, and KIRP as cancer lineages where TMEM165 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 TMEM165 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TMEM165 survival associations across molecular data types. TMEM165 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) 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 TMEM165 RNA expression–survival associations across cancer types. High TMEM165 expression shows unfavorable associations in UVM, LIHC, CESC, KIRC, KIRP and KICH. 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 TMEM165 RNA expression.
This table summarizes TMEM165 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TMEM165. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TMEM165 shows higher tumor expression in BLCA, HNSC, LIHC, COAD, STAD and LUAD. The BLCA box plot shows higher TMEM165 RNA expression in tumor versus normal tissue (log2 FC = +0.840, t-test p < 0.001).
This table shows molecular features associated with TMEM165 in patient tissues and cancer cell lines. In patient samples, TMEM165 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, TMEM165 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
