Dataset Information

A head and neck cancer protein interaction map reveals PIK3CA mutant drug sensitivity

ABSTRACT: Despite extensive DNA sequencing of patient tumors, it remains challenging to translate the immense landscape of heterogeneous genetic alterations into function and clinical outcomes due to a limited understanding of cancer specific molecular network architectures. To bridge this gap, we have used affinity purification-mass spectrometry to generate protein interaction networks for 31 proteins with significant alterations in head and neck squamous cell carcinoma. This network includes 771 interactions covering both cancer and non-tumorigenic cell states, as well as wild-type and mutant proteins. Differential analysis across these dimensions reveals a strong interaction between PIK3CA and ERBB3 (HER3), dependent upon mutations in PIK3CA. We show that this interaction correlates with ERBB3 activity in vitro and can be targeted in vivo using a clinical ERBB3 inhibitor, CDX3379, to prohibit growth of tumors with common PIK3CA mutations. This study provides a roadmap for elucidating genetic complexity through multidimensional maps of cancer cell biology.

INSTRUMENT(S): Q Exactive Plus, LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

DISEASE(S): Head And Neck Squamous Cell Carcinoma

SUBMITTER: Danielle Swaney

LAB HEAD: Danielle Swaney / Nevan Krogan

PROVIDER: PXD019469 | Pride | 2021-10-07

REPOSITORIES: Pride

ACCESS DATA

Similar Datasets

Project description:Uveal melanoma (UM) is the most prevalent cancer of the eye in adults, with a highly aggressive form of metastasis that is refractory to current therapies. UM is driven by aberrant activation of the Gαq pathway by hotspot activating mutation of GNAQ/GNA11, with few additional genetic aberrations. Despite this, there are limited effective targeted therapies currently available against the treatment of UM and mUM. Here, we performed a high-throughput chemogenetic drug screen in GNAQ-mutant UM contrasted with that of BRAF-mutant skin cutaneous melanoma, as a network chemical biology-based approach to identify therapeutic agents that target the mechanistic underpinnings driving UM. We observed strong genotype-driven drug sensitivities, and identified several drug classes with preferential activity against UM using a method termed Drug Set Enrichment Analysis (DSEA). Among them, we found an enrichment for PKC inhibitors, and identified one compound LXS-196, with the highest preferential activity against UM. Our investigation into the mechanism of action of LXS-196 revealed that in addition to inhibiting the Gq-ERK pathway, unlike other PKC inhibitors, this drug also reduced FAK activity, a recently identified mediator of non-canonical Gαq-driven oncogenic signaling. Kinome profiling revealed that LXS-196 acts as a multi-targeted kinase inhibitor, with high preference for PKC as well as PKN/PRK, the latter a poorly investigated AGC kinase that is activated directly by RhoA. This primes LXS-196 to target cell-essential pathways that drive tumor growth in UM by targeting both PKC, in addition to FAK. Moreover, we find that PKN is activated by GNAQ downstream from RhoA, thereby contributing to FAK stimulation. These findings expose a signaling vulnerability that can be targeted pharmacologically. Ultimately, dual PKC and PKN inhibition by LXS-196 acts synergistically with FAK inhibitors (FAKi) to halt UM growth and promote cytotoxic cell death in vitro and in preclinical metastatic mouse models, thus providing a highly translatable therapeutic multimodal precision strategy against mUM.

Dataset Information

A head and neck cancer protein interaction map reveals PIK3CA mutant drug sensitivity

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure