Faculty Bibliography

MYC paralogs are frequently activated in small cell lung cancer (SCLC) but represent poor drug targets. Thus, a detailed mapping of MYC-paralog-specific vulnerabilities may help to develop effective therapies for SCLC patients. Using a unique cellular CRISPR activation model, we uncover that, in contrast to MYCN and MYCL, MYC represses BCL2 transcription via interaction with MIZ1 and DNMT3a. The resulting lack of BCL2 expression promotes sensitivity to cell cycle control inhibition and dependency on MCL1. Furthermore, MYC activation leads to heightened apoptotic priming, intrinsic genotoxic stress and susceptibility to DNA damage checkpoint inhibitors. Finally, combined AURK and CHK1 inhibition substantially prolongs the survival of mice bearing MYC-driven SCLC beyond that of combination chemotherapy. These analyses uncover MYC-paralog-specific regulation of the apoptotic machinery with implications for genotype-based selection of targeted therapeutics in SCLC patients.

Small cell lung cancer (SCLC) is an exceptionally lethal malignancy for which more effective therapies are urgently needed. Several lines of evidence, from SCLC primary human tumours, patient-derived xenografts, cancer cell lines and genetically engineered mouse models, appear to be converging on a new model of SCLC subtypes defined by differential expression of four key transcription regulators: achaete-scute homologue 1 (ASCL1; also known as ASH1), neurogenic differentiation factor 1 (NeuroD1), yes-associated protein 1 (YAP1) and POU class 2 homeobox 3 (POU2F3). In this Perspectives article, we review and synthesize these recent lines of evidence and propose a working nomenclature for SCLC subtypes defined by relative expression of these four factors. Defining the unique therapeutic vulnerabilities of these subtypes of SCLC should help to focus and accelerate therapeutic research, leading to rationally targeted approaches that may ultimately improve clinical outcomes for patients with this disease.

INTRODUCTION/BACKGROUND:Multiple genetic mechanisms have been identified in EGFR-mutant lung cancers as mediators of acquired resistance (AR) to EGFR tyrosine kinase inhibitors (TKIs), but many cases still lack a known mechanism. METHODS:To identify novel mechanisms of AR, we performed targeted large panel sequencing of samples from 374 consecutive patients with metastatic EGFR-mutant lung cancer, including 174 post-TKI samples, of which 38 also had a matched pre-TKI sample. Alterations hypothesized to confer AR were introduced into drug-sensitive EGFR-mutant lung cancer cell lines (H1975, HCC827, and PC9) by using clustered regularly interspaced short palindromic repeats/Cas9 genome editing. MSK-LX138cl, a cell line with EGFR exon 19 deletion (ex19del) and praja ring finger ubiquitin ligase 2 gene (PJA2)/BRAF fusion, was generated from an EGFR TKI-resistant patient sample. RESULTS:We identified four patients (2.3%) with a BRAF fusion (three with acylglycerol kinase gene (AGK)/BRAF and one with PJA2/BRAF) in samples obtained at AR to EGFR TKI therapy (two posterlotinib samples and two posterlotinib and postosimertinib samples). Pre-TKI samples were available for two of four patients and both were negative for BRAF fusion. Induction of AGK/BRAF fusion in H1975 (L858R + T790M), PC9 (ex19del) and HCC827 (ex19del) cells increased phosphorylation of BRAF, MEK1/2, ERK1/2, and signal transducer and activator of transcription 3 and conferred resistance to growth inhibition by osimertinib. MEK inhibition with trametinib synergized with osimertinib to block growth. Alternately, a pan-RAF inhibitor as a single agent blocked growth of all cell lines with mutant EGFR and BRAF fusion. CONCLUSION/CONCLUSIONS:BRAF fusion is a mechanism of AR to EGFR TKI therapy in approximately 2% of patients. Combined inhibition of EGFR and MEK (with osimertinib and trametinib) or BRAF (with a pan-RAF inhibitor) are potential therapeutic strategies that should be explored.

INTRODUCTION/BACKGROUND:Determination of the target-binding fraction (TBF) of radiopharmaceuticals using cell-based assays is prone to inconsistencies arising from several intrinsic and extrinsic factors. Here, we report a cell-free quantitative method of analysis to determine the TBF of radioligands. METHODS:Magnetic beads functionalized with Ni-NTA or streptavidin were incubated with 1 μg of histidine-tagged or biotinylated antigen of choice for 15 min, followed by incubating 1 ng of the radioligand for 30 min. The beads, supernatant and wash fractions were measured for radioactivity on a gamma counter. The TBF was determined by quantifying the percentage of activity associated with the magnetic beads. RESULTS:The described method works robustly with a variety of radioisotopes and class of molecules used as radioligands. The entire assay can be completed within 2 h. CONCLUSION/CONCLUSIONS:The described method yields results in a rapid and reliable manner whilst improving and extending the scope of previously described bead-based radioimmunoassays. ADVANCES IN KNOWLEDGE/UNASSIGNED:Using a bead-based radioligand binding assay overcomes the limitations of traditional cell-based assays. The described method is applicable to antibody as well as non-antibody based radioligands and is independent of the effect of target antigen density on cells, the choice of radioisotope used for synthesis of the radioligand and the temperature at which the assay is performed. IMPLICATIONS FOR PATIENT CARE/UNASSIGNED:The bead-based radioligand binding assay is significantly easier to perform and is ideally suited for adoption by the radiopharmacy as a quality control method of analysis to fulfill the criteria for release of radiopharmaceuticals in the clinic. The use of this assay is likely to ensure a more reliable validation of radiopharmaceutical quality and result in fewer failed doses, which could ultimately translate to an efficient release of radiopharmaceuticals for administration to patients in the clinic.

Small cell lung cancer (SCLC) is a recalcitrant, aggressive neuroendocrine-type cancer for which little change to first-line standard-of-care treatment has occurred within the last few decades. Unlike nonsmall cell lung cancer (NSCLC), SCLC harbors few actionable mutations for therapeutic intervention. Lysine-specific histone demethylase 1A (LSD1 also known as KDM1A) inhibitors were previously shown to have selective activity in SCLC models, but the underlying mechanism was elusive. Here, we found that exposure to the selective LSD1 inhibitor ORY-1001 activated the NOTCH pathway, resulting in the suppression of the transcription factor ASCL1 and the repression of SCLC tumorigenesis. Our analyses revealed that LSD1 bound to the NOTCH1 locus, thereby suppressing NOTCH1 expression and downstream signaling. Reactivation of NOTCH signaling with the LSD1 inhibitor reduced the expression of ASCL1 and neuroendocrine cell lineage genes. Knockdown studies confirmed the pharmacological inhibitor-based results. In vivo, sensitivity to LSD1 inhibition in SCLC patient-derived xenograft (PDX) models correlated with the extent of consequential NOTCH pathway activation and repression of a neuroendocrine phenotype. Complete and durable tumor regression occurred with ORY-1001-induced NOTCH activation in a chemoresistant PDX model. Our findings reveal how LSD1 inhibitors function in this tumor and support their potential as a new and targeted therapy for SCLC.

Immune checkpoint therapies have shown tremendous promise in cancer therapy. However, tools to assess their target engagement, and hence the ability to predict their efficacy, have been lacking. Here, we show that target engagement and tumor-residence kinetics of antibody therapeutics targeting programmed death ligand-1 (PD-L1) can be quantified noninvasively. In computational docking studies, we observed that PD-L1-targeted monoclonal antibodies (atezolizumab, avelumab, and durvalumab) and a high-affinity PD-L1-binding peptide, WL12, have common interaction sites on PD-L1. Using the peptide radiotracer [64Cu]WL12 in vivo, we employed positron emission tomography (PET) imaging and biodistribution studies in multiple xenograft models and demonstrated that variable PD-L1 expression and its saturation by atezolizumab, avelumab, and durvalumab can be quantified independently of biophysical properties and pharmacokinetics of antibodies. Next, we used [64Cu]WL12 to evaluate the impact of time and dose on the unoccupied fraction of tumor PD-L1 during treatment. These quantitative measures enabled, by mathematical modeling, prediction of antibody doses needed to achieve therapeutically effective occupancy (defined as >90%). Thus, we show that peptide-based PET is a promising tool for optimizing dose and therapeutic regimens employing PD-L1 checkpoint antibodies, and can be used for improving therapeutic efficacy.

Neuroendocrine prostate cancer (NEPC), a lethal form of the disease, is characterized by loss of androgen receptor (AR) signaling during neuroendocrine transdifferentiation, which results in resistance to AR-targeted therapy. Clinically, genomically and epigenetically, NEPC resembles other types of poorly differentiated neuroendocrine tumors (NETs). Through pan-NET analyses, we identified ONECUT2 as a candidate master transcriptional regulator of poorly differentiated NETs. ONECUT2 ectopic expression in prostate adenocarcinoma synergizes with hypoxia to suppress androgen signaling and induce neuroendocrine plasticity. ONEUCT2 drives tumor aggressiveness in NEPC, partially through regulating hypoxia signaling and tumor hypoxia. Specifically, ONECUT2 activates SMAD3, which regulates hypoxia signaling through modulating HIF1α chromatin-binding, leading NEPC to exhibit higher degrees of hypoxia compared to prostate adenocarcinomas. Treatment with hypoxia-activated prodrug TH-302 potently reduces NEPC tumor growth. Collectively, these results highlight the synergy between ONECUT2 and hypoxia in driving NEPC, and emphasize the potential of hypoxia-directed therapy for NEPC patients.

Recent advancements in oncolytic virotherapy commend a special attention to developing new strategies for targeting cancer cells with oncolytic viruses (OVs). Modifications of the viral envelope or coat proteins serve as a logical mean of repurposing viruses for cancer treatment. In this review, we discuss how detailed structural knowledge of the interactions between OVs and their natural receptors provide valuable insights into tumor specificity of some viruses and re-targeting of alternate receptors for broad tumor tropism or improved tumor selectivity.

Molecularly targeted therapies aim to obstruct cell autonomous programs required for tumor growth. We show that mitogen-activated protein kinase (MAPK) and cyclin-dependent kinase 4/6 inhibitors act in combination to suppress the proliferation of KRAS-mutant lung cancer cells while simultaneously provoking a natural killer (NK) cell surveillance program leading to tumor cell death. The drug combination, but neither agent alone, promotes retinoblastoma (RB) protein-mediated cellular senescence and activation of the immunomodulatory senescence-associated secretory phenotype (SASP). SASP components tumor necrosis factor-α and intercellular adhesion molecule-1 are required for NK cell surveillance of drug-treated tumor cells, which contributes to tumor regressions and prolonged survival in a KRAS-mutant lung cancer mouse model. Therefore, molecularly targeted agents capable of inducing senescence can produce tumor control through non-cell autonomous mechanisms involving NK cell surveillance.

Modern mass spectrometry now permits genome-scale and quantitative measurements of biological proteomes. However, analysis of specific specimens is currently hindered by the incomplete representation of biological variability of protein sequences in canonical reference proteomes and the technical demands for their construction. Here, we report ProteomeGenerator, a framework for de novo and reference-assisted proteogenomic database construction and analysis based on sample-specific transcriptome sequencing and high-accuracy mass spectrometry proteomics. This enables the assembly of proteomes encoded by actively transcribed genes, including sample-specific protein isoforms resulting from non-canonical mRNA transcription, splicing, or editing. To improve the accuracy of protein isoform identification in non-canonical proteomes, ProteomeGenerator relies on statistical target-decoy database matching calibrated using sample-specific controls. Its current implementation includes automatic integration with MaxQuant mass spectrometry proteomics algorithms. We applied this method for the proteogenomic analysis of splicing factor SRSF2 mutant leukemia cells, demonstrating high-confidence identification of non-canonical protein isoforms arising from alternative transcriptional start sites, intron retention, and cryptic exon splicing as well as improved accuracy of genome-scale proteome discovery. Additionally, we report proteogenomic performance metrics for current state-of-the-art implementations of SEQUEST HT, MaxQuant, Byonic, and PEAKS mass spectral analysis algorithms. Finally, ProteomeGenerator is implemented as a Snakemake workflow within a Singularity container for one-step installation in diverse computing environments, thereby enabling open, scalable, and facile discovery of sample-specific, non-canonical, and neomorphic biological proteomes.