Understanding cancer drug resistance with Sleeping Beauty functional genomic screens: Application to MAPK inhibition in cutaneous melanoma

Combined BRAF and MEK inhibition is an effective treatment for BRAF-mutant cutaneous melanoma. However, most patients progress on this treatment due to drug resistance. Here, we applied the Sleeping Beauty transposon system to understand how melanoma evades MAPK inhibition. We found that the specific drug resistance mechanisms differed across melanomas in our genetic screens of five cutaneous melanoma cell lines. While drivers that reactivated MAPK were highly conserved, many others were cell-line specific. One such driver, VAV1, activated a de-differentiated transcriptional program like that of hyperactive RAC1, RAC1P29S. To target this mechanism, we showed that an inhibitor of SRC, saracatinib, blunts the VAV1-induced transcriptional reprogramming. Overall, we highlighted the importance of accounting for melanoma heterogeneity in treating cutaneous melanoma with MAPK inhibitors. Moreover, we demonstrated the utility of the Sleeping Beauty transposon system in understanding cancer drug resistance.

SRC-RAC1 signaling drives drug resistance to BRAF inhibition in de-differentiated cutaneous melanomas

Rare gain-of-function mutations in RAC1 drive drug resistance to targeted BRAF inhibition in cutaneous melanoma. Here, we show that wildtype RAC1 is a critical driver of growth and drug resistance, but only in a subset of melanomas with elevated markers of de-differentiation. Similarly, SRC inhibition also selectively sensitized de-differentiated melanomas to BRAF inhibition. One possible mechanism may be the suppression of the de-differentiated state, as SRC and RAC1 maintained markers of de-differentiation in human melanoma cells. The functional differences between melanoma subtypes suggest that the clinical management of cutaneous melanoma can be enhanced by the knowledge of differentiation status. To simplify the task of classification, we developed a binary classification strategy based on a small set of ten genes. Using this gene set, we reliably determined the differentiation status previously defined by hundreds of genes. Overall, our study informs strategies that enhance the precision of BRAFi by discovering unique vulnerabilities of the de-differentiated cutaneous melanoma subtype and creating a practical method to resolve differentiation status.

Machine learning approach informs biology of cancer drug response

Background

The mechanism of action for most cancer drugs is not clear. Large-scale pharmacogenomic cancer cell line datasets offer a rich resource to obtain this knowledge. Here, we present an analysis strategy for revealing biological pathways that contribute to drug response using publicly available pharmacogenomic cancer cell line datasets.

Methods

We present a custom machine-learning based approach for identifying biological pathways involved in cancer drug response. We test the utility of our approach with a pan-cancer analysis of ML210, an inhibitor of GPX4, and a melanoma-focused analysis of inhibitors of BRAF^V600. We apply our approach to reveal determinants of drug resistance to microtubule inhibitors.

Results

Our method implicated lipid metabolism and Rac1/cytoskeleton signaling in the context of ML210 and BRAF inhibitor response, respectively. These findings are consistent with current knowledge of how these drugs work. For microtubule inhibitors, our approach implicated Notch and Akt signaling as pathways that associated with response.

Conclusions

Our results demonstrate the utility of combining informed feature selection and machine learning algorithms in understanding cancer drug response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04720-z.

Abstract B08: Identification and characterization of Rho family GTPases as drivers of drug resistance in BRAFV600 mutant melanoma

The serine/threonine protein kinase BRAF is mutated in approximately 50% of cutaneous melanomas, leading to hyperactivation of the MAPK/ERK pathway. The most common mutations, BRAFV600, can be targeted by selective kinase inhibitors, such as vemurafenib. Although initial clinical response to BRAF inhibition (BRAFi) is encouraging, 90% of patients develop drug resistance within a few months. Drug resistance can be delayed, but not prevented, by combining BRAFi with an MEK inhibitor (MEKi), such as cobimetinib. While some resistance mechanisms are known, disease progression on drug cannot be explained in all patients. We performed a gain-of-function mutagenesis screen utilizing the Sleeping Beauty transposon system to identify novel drivers of resistance in BRAFV600E mutant melanoma cells sensitive to current therapies. We chose four of the top candidates from our screen and validated the ability to drive resistance to both vemurafenib and vemurafenib-cobimetinib combination treatment in multiple melanoma cell lines. In an effort to determine the broader role of candidate vemurafenib-resistance drivers, we conducted an additional in vivo mutagenesis screen, of which genetic analysis is ongoing. Our initial cell-based screen identified two members of the Dbl family of guanine nucleotide exchange factors (GEFs), VAV1 and MCF2, as candidate drivers of vemurafenib resistance. A375 melanoma cells overexpressing VAV1 or MCF2 maintain significant growth under vemurafenib treatment, while control cells do not. Functional tests of VAV1 and MCF2 identified that the active form of two Rho family members, RAC1 and CDC42, increases following treatment with vemurafenib, suggesting a PAK-mediated pathway of resistance. In addition, all candidates that were tested elevated ERK signaling in the presence of vemurafenib. Many of the extracellular signaling pathways known to drive increased vemurafenib resistance activate Rho signaling. Our results suggest that Dbl family members may play an important role in this process. Understanding how Rho activation occurs and its consequences for drug resistance in melanoma will provide critical insights into the design and validation of future targeted therapies.

Citation Format: Jacob L. Schillo, Charlotte R. Feddersen, Afshin Varzavand, Hayley R. Vaughn, Lexy S. Wadsworth, Andrew P. Voigt, Eliot Y. Zhu, Jesse D. Riordan, Christopher S. Stipp, Adam J. Dupuy. Identification and characterization of Rho family GTPases as drivers of drug resistance in BRAFV600 mutant melanoma [abstract]. In: Proceedings of the AACR Special Conference on Melanoma: From Biology to Target; 2019 Jan 15-18; Houston, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(19 Suppl):Abstract nr B08.

Src-Dependent DBL Family Members Drive Resistance to Vemurafenib in Human Melanoma

The use of selective BRAF inhibitors (BRAFi) has produced remarkable outcomes for patients with advanced cutaneous melanoma harboring a BRAFV600E mutation. Unfortunately, the majority of patients eventually develop drug-resistant disease. We employed a genetic screening approach to identify gain-of-function mechanisms of BRAFi resistance in two independent melanoma cell lines. Our screens identified both known and unappreciated drivers of BRAFi resistance, including multiple members of the DBL family. Mechanistic studies identified a DBL/RAC1/PAK signaling axis capable of driving resistance to both current and next-generation BRAFis. However, we show that the SRC inhibitor, saracatinib, can block the DBL-driven resistance. Our work highlights the utility of our straightforward genetic screening method in identifying new drug combinations to combat acquired BRAFi resistance. SIGNIFICANCE: A simple, rapid, and flexible genetic screening approach identifies genes that drive resistance to MAPK inhibitors when overexpressed in human melanoma cells.

A simplified transposon mutagenesis method to perform phenotypic forward genetic screens in cultured cells

BACKGROUND

The introduction of genome-wide shRNA and CRISPR libraries has facilitated cell-based screens to identify loss-of-function mutations associated with a phenotype of interest. Approaches to perform analogous gain-of-function screens are less common, although some reports have utilized arrayed viral expression libraries or the CRISPR activation system. However, a variety of technical and logistical challenges make these approaches difficult for many labs to execute. In addition, genome-wide shRNA or CRISPR libraries typically contain of hundreds of thousands of individual engineered elements, and the associated complexity creates issues with replication and reproducibility for these methods.

RESULTS

Here we describe a simple, reproducible approach using the SB transposon system to perform phenotypic cell-based genetic screens. This approach employs only three plasmids to perform unbiased, whole-genome transposon mutagenesis. We also describe a ligation-mediated PCR method that can be used in conjunction with the included software tools to map raw sequence data, identify candidate genes associated with phenotypes of interest, and predict the impact of recurrent transposon insertions on candidate gene function. Finally, we demonstrate the high reproducibility of our approach by having three individuals perform independent replicates of a mutagenesis screen to identify drivers of vemurafenib resistance in cultured melanoma cells.

CONCLUSIONS

Collectively, our work establishes a facile, adaptable method that can be performed by labs of any size to perform robust, genome-wide screens to identify genes that influence phenotypes of interest.

Abstract LB-096: A gain-of-function screen identifies drivers of drug resistance in BRAFV600E melanoma cell lines

Melanoma is the deadliest form of skin cancer, and until recently patients had few treatment options upon diagnosis. Fortunately, this lack of treatment options changed with the discovery of vemurafenib, a highly selective kinase inhibitor that specifically targets the BRAFV600E mutant protein, found in ~50% of all melanoma cases. Initially, the kinase inhibitor provided complete or partial response to over 50% of patients and prolonged progression-free survival. However, the majority of patients relapse once tumors acquire resistance to vemurafenib. Some of the genetic resistance mechanisms are known, including BRAF amplification, expression of truncated BRAF, and RAS mutation. However, a significant portion of vemurafenib resistance cases is unexplained. While drug resistance can be delayed by combining vemurafenib with cobimetinib, a MEK inhibitor, mechanisms of resistance to this drug combination are not well characterized.

We performed a gain-of-function screen to identify drivers of drug resistance to vemurafenib or vemurafenib combined with cobimetinib. Briefly, A375 melanoma cells were engineered to express the hyperactive transposase SB100. These cells were then subsequently transfected with the mutagenic T2Onc3 transposon to produce a population of mutagenized A375 cells. Three weeks of vemurafenib treatment selected for cells with the acquired ability to grow in the presence of drug. Candidate driver mutations were then identified by profiling the sites of transposon insertion in drug-resistant cells to find genes that were recurrently over-expressed by transposon insertions. This led to the discovery of five genes that act as drivers of vemurafenib resistance when overexpressed in the human melanoma cell line A375. Candidate genes were then validated in multiple melanoma cell lines by assessing cell growth and viability in varying concentrations of vemurafenib.

An analogous screen was performed in A375 to identify drivers of resistance to the combination of vemurafenib and cobimetinib. In addition, we are assessing the diversity of drug resistance mechanisms by performing mutagenesis in three additional human melanoma cell lines.

The characterization of the novel drug resistance pathways identified here will improve treatment outcomes for patients with BRAFV600E mutant melanoma.

Citation Format: Charlotte R. Feddersen, Jacob L. Schillo, Hayley R. Vaughn, Andrew P. Voigt, Eliot Y. Zhu, Lexy S. Wadsworth, Christopher S. Stipp, Adam J. Dupuy. A gain-of-function screen identifies drivers of drug resistance in BRAFV600E melanoma cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-096.

Poled-fiber source of broadband polarization-entangled photon pairs

We demonstrate broadband polarization-entangled photon pair generation in a poled fiber phase matched for Type II downconversion in the 1.5 μm telecom band. Even with signal-idler separation greater than 100 nm, we observe fringe visibilities greater than 97% and tangle greater than 0.8. A Hong-Ou-Mandel interference experiment is also used to experimentally confirm the broadband nature of the entanglement.