Göksu Avar

Precision oncology relies on molecular biomarkers to stratify patients into responders and non-responders to a given treatment. Although gene expression profiles have historically been explored for biomarker discovery, fewer studies investigated single-gene expression biomarkers. Additionally, many approaches are limited to cancer type-specific associations, which constrain statistical power. To address these limitations, we developed a regression-based framework that corrects for tissue-specific biases and enhances detection of pan-cancer single-gene expression biomarkers of drug sensitivity in cancer cell line high-throughput drug screens. Our method maintains predictive performance post-correction, and successfully recovers established biomarkers, such as SLFN11 expression for DNA damaging agents. Notably, we identified SPRY4 and NES expression as biomarkers of sensitivity for compounds targeting ERK/MAPK signaling (adjusted p-value = 4.016 × 10 ⁻ ⁵ and 7.221 × 10 ⁻ ⁶, respectively). This approach offers a scalable strategy for biomarker discovery and holds potential for translation to more complex biological models and patient-derived datasets. Ultimately, pan-cancer single-gene expression biomarkers may inform patient stratification and warrant clinical validation in precision oncology.

The CARD11-BCL10-MALT1 (CBM) complex drives NF-κB signaling and MALT1 protease activation after T cell receptor (TCR) stimulation, forming a central signaling hub in adaptive immunity. Both linear ubiquitin chain assembly complex (LUBAC), consisting of HOIP, HOIL-1 and SHARPIN, and TRAF6 interact with the CBM complex. Still, the coordinated activity of these E3 ligases in controlling CBM activity remains elusive. Here we demonstrate that LUBAC, unlike TRAF6, is largely dispensable for TCR-induced NF-κB activation in human CD4 ⁺ T cells. However, HOIP contributes to NF-κB target gene expression and, with TRAF6, modulates MALT1 substrate recognition, influencing T cell responses. Further, LUBAC-mediated conjugation of Met1-linked ubiquitin chains to BCL10 strictly depends on TRAF6, but putative Met1-ubiquitin acceptor lysines in BCL10 serve essential structural roles that limit accessibility within BCL10-MALT1 filaments. Thus, LUBAC acts downstream of TRAF6 to modulate MALT1 substrate recognition and to catalyze BCL10 ubiquitination, which is incompatible with BCL10-MALT1 filament formation.

The epithelial-mesenchymal transition (EMT) is characterised by the loss of cell-cell adhesion and cell polarity, which is often exploited by cancer cells to adopt a motile, invasive and metastatic phenotype. Whilst EMT is often linked with cancer progression and therapy resistance, strategies for its selective targeting remain limited. In order to address this, we infer EMT states of cancer cell lines from their molecular signatures and use predictive and causal modelling to estimate the effect of EMT on drug susceptibility in high-throughput drug screens. For example, we show that EMT signatures in melanoma cells can predict favourable responses to the HSP90 inhibitor luminespib and demonstrate that epithelial-like melanoma cells can be sensitised to luminespib upon stimulation of EMT by TGF-β. Thus, we provide an analysis that systematically yields a set of potent drugs by exploiting vulnerabilities of cancer cells undergoing EMT, which may pave the way for therapies to target these cells.

Constitutive mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) activity drives survival of malignant lymphomas addicted to chronic B-cell receptor signaling, oncogenic CARD11, or the API2-MALT1 (also BIRC3::MALT1) fusion oncoprotein. Although MALT1 scaffolding induces NF-κB–dependent survival signaling, MALT1 protease function is thought to augment NF-κB activation by cleaving signaling mediators and transcriptional regulators in B-cell lymphomas. However, the pathological role of MALT1 protease function in lymphomagenesis is not well understood. Here, we show that TRAF6 controls MALT1-dependent activation of NF-κB transcriptional responses but is dispensable for MALT1 protease activation driven by oncogenic CARD11. To uncouple enzymatic and nonenzymatic functions of MALT1, we analyzed TRAF6-dependent and -independent as well as MALT1 protease–dependent gene expression profiles downstream of oncogenic CARD11 and API2-MALT1. The data suggest that by cleaving and inactivating the RNA binding proteins Regnase-1 and Roquin-1/2, MALT1 protease induces posttranscriptional upregulation of many genes including NFKBIZ/IκBζ, NFKBID/IκBNS, and ZC3H12A/Regnase-1 in activated B-cell–like diffuse large B-cell lymphoma (ABC DLBCL). We demonstrate that oncogene-driven MALT1 activity in ABC DLBCL cells regulates NFKBIZ and NFKBID induction on an mRNA level via releasing a brake imposed by Regnase-1 and Roquin-1/2. Furthermore, MALT1 protease drives posttranscriptional gene induction in the context of the API2-MALT1 fusion created by the recurrent t(11;18)(q21;q21) translocation in MALT lymphoma. Thus, MALT1 paracaspase acts as a bifurcation point for enhancing transcriptional and posttranscriptional gene expression in malignant lymphomas. Moreover, the identification of MALT1 protease–selective target genes provides specific biomarkers for the clinical evaluation of MALT1 inhibitors.

Aberrant DNA methylation accompanies genetic alterations during oncogenesis and tumour homeostasis and contributes to the transcriptional deregulation of key signalling pathways in cancer. Despite increasing efforts in DNA methylation profiling of cancer patients, there is still a lack of epigenetic biomarkers to predict treatment efficacy. To address this, we analyse 721 cancer cell lines across 22 cancer types treated with 453 anti-cancer compounds. We systematically detect the predictive component of DNA methylation in the context of transcriptional and mutational patterns, i.e., in total 19 DNA methylation biomarkers across 17 drugs and five cancer types. DNA methylation constitutes drug sensitivity biomarkers by mediating the expression of proximal genes, thereby enhancing biological signals across multi-omics data modalities. Our method reproduces anticipated associations, and in addition, we find that the NEK9 promoter hypermethylation may confer sensitivity to the NEDD8-activating enzyme (NAE) inhibitor pevonedistat in melanoma through downregulation of NEK9. In summary, we envision that epigenomics will refine existing patient stratification, thus empowering the next generation of precision oncology.