Regulation of protein serine/threonine kinase activity

associated omics data
GO:0071900Ontology (GO BP)GO biological process · ~281 member genes

Q-omics provides the Regulation of protein serine/threonine kinase activity (GO:0071900) pathway profile, scoring each patient from the combined activity of its roughly 281 member genes. Pathway activity is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, the pathway is differentially active in 12, with the highest sampling consensus in HNSC. Additionally, pathway RNA activity shows 37,114 significant cross-omics associations, again with the highest sampling consensus in STAD. Together, these results highlight KIRC, HNSC, and STAD as cancer lineages where the pathway shows reproducible signals across outcome, tissue activity, and molecular association 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. Pathway-against-pathway and pathway-against-mutation comparisons are not available for ontology entities.

Survival associations

This table summarizes Regulation of protein serine/threonine kinase activity survival associations by molecular data type. RNA-level pathway activity shows survival associations in the most cancer types (24). The rightmost column indicates the cancer type with the highest sampling consensus for each layer.
Data typeSurvival analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Kaplan–Meier24KIRC (142)view →
This table ranks reproducible pathway activity–survival associations across cancer types. High Regulation of protein serine/threonine kinase activity activity shows favorable associations in HNSC, but unfavorable associations in KIRC, KIRP, ACC, LIHC and MESO. In the KIRC Kaplan–Meier curve the high-activity group declines faster, consistent with the unfavorable association (log-rank p < 0.001). KIRC ranks highest by sampling consensus for Regulation of protein serine/threonine kinase activity.
LineageMeasureSplitStageAUC1
high
AUC2
low
pSampling consensus
KIRCDFSMedianAll0.5110.722<.001142view →
KIRPOSMedianAll0.3840.823<.001137view →
ACCOSMedianAll0.4450.756<.001129view →
LIHCDFSMedianAll0.4460.629<.00195view →
HNSCOSMedianIV0.5280.317<.00190view →
MESOOSQuartileII,III,IV0.2600.619<.00156view →
Pink = unfavorable, green = favorable. all 24 lineages →

Regulation of protein serine/threonine kinase activity-KIRC (DFS)

Kaplan–Meier survival curve for Regulation of protein serine/threonine kinase activity pathway activity in KIRC: high vs low activity groups.

Explore this curve interactively →

Tumor vs Normal activity

This table summarizes Regulation of protein serine/threonine kinase activity tumor–normal activity differences by data type. RNA-level activity shows significant tumor–normal differences in 12 cancer types. The strongest signals are in HNSC for RNA.
Data typeActivity analysisLineage consensusLineage of highest sampling consensus
GO function (RNA)Box plot12HNSC (11)view →
This table ranks reproducible tumor–normal activity differences for the pathway. A positive fold-change indicates higher activity in tumor tissue. The pathway shows higher tumor activity across HNSC, LIHC and COAD and lower tumor activity in KICH, KIRC and KIRP. In the HNSC box plot, tumor samples show higher pathway activity than matched normal samples (log2 FC = +0.033, t-test p < 0.001).
LineageGenderStageFold-changepSampling consensus
HNSCMaleIII,IV+0.033<.00111view →
KICHFemaleAll−0.042<.00110view →
KIRCFemaleIV−0.026<.00110view →
LIHCFemaleII,III,IV+0.027<.0019view →
COADFemaleAll+0.021<.0019view →
KIRPMaleAll−0.029<.0017view →
Pink = higher activity in tumor. all 12 lineages →

Regulation of protein serine/threonine kinase activity-HNSC

Tumor-vs-normal pathway-activity box plot for Regulation of protein serine/threonine kinase activity in HNSC.

Explore this plot interactively →

Cross-omics associations

This table shows molecular features associated with Regulation of protein serine/threonine kinase activity pathway activity in patient tissues and cancer cell lines. In patient samples, pathway activity is most strongly linked to RNA and protein features, with the largest associated set in STAD. In cancer cell lines, RNA-expression features and functional dependencies dominate, with the largest set in BLOOD_Lymphoma.
Associated data typeStrength (# associated data)Lineage of highest associated data
RNA
RNA37,114STAD (24028)view →
Protein (mass-spec)11,910GBM (2779)view →
Associated data typeStrength (# associated data)Lineage of highest associated data
CRISPR
CRISPR1,902BLOOD_Lymphoma (186)view →
RNA1,424BLOOD_Lymphoma (223)view →
RNA
RNA6,719UPPER_AERODIGESTIVE_TRACT (2808)view →
CRISPR1,676CNS (119)view →
shRNA
RNA2,016SOFT_TISSUE (258)view →
shRNA1,945SOFT_TISSUE (265)view →
Protein (mass-spec)
shRNA864UPPER_AERODIGESTIVE_TRACT (181)view →
RNA780BLOOD_Leukemia (152)view →