Faculty Bibliography

BACKGROUND:Prostate cancer is the most common form of male cancer and can initially be treated as a localized disease. Although the 5-year survival rate at diagnosis approaches 100 percent, a subset of patients will subsequently develop resistance to treatment. This may ultimately lead to metastatic castration resistant prostate cancer (mCRPC), for which the prognosis is much less favorable. The importance of the Wnt/β-catenin pathway in treatment-resistant prostate cancer has inspired efforts to exploit the interaction of β-catenin with its transcription binding partners as a therapeutic strategy for prostate cancer. METHODS:Peptoid-peptide macrocycles are attractive design scaffolds for disrupting protein-protein interactions. In this study, we evaluate a library of these macrocycles and demonstrate their selectivity for the β-catenin/TCF (T Cell Factor) interaction. RESULTS:Importantly, we show that the macrocycles do not significantly alter the binding of β-catenin to cell surface protein, E-cadherin. Our lead sequence, Macrocycle 13, (MC13) was also tolerant of modifications aimed to improve aqueous solubility while retaining activity. Herein, we demonstrate in vivo proof of principle for using peptidomimetic macrocycles to target the β-catenin/TCF interaction. Treated prostate cancer mouse xenografts show markedly diminished tumor growth and decreased levels of myc protein. MC13 also inhibits growth in an organoid model with genetic alterations frequently found in prostate cancer. Transcriptome analysis of prostate cancer cells treated with MC13 reveals downregulation of key pathways, including Wnt/β-catenin and c-myc. Furthermore, chromatin immunoprecipitation (ChIP) analysis shows reduced β-catenin at its target genes, axin2 and c-myc. CONCLUSION/CONCLUSIONS:Our findings underscore the therapeutic potential of peptoid-peptide macrocycle inhibition of β-catenin in prostate cancer.

Approved inhibitors of KRASG12C prevent oncogenic activation by sequestering the inactive, GDP-bound (OFF) form rather than directly binding and inhibiting the active, GTP-bound (ON) form. This approach provides no direct target coverage of the active protein. Expectedly, adaptive resistance to KRASG12C (OFF)-only inhibitors is observed in association with increased expression and activity of KRASG12C(ON). To provide optimal KRASG12C target coverage, we have developed BBO-8520, a first-in-class, direct dual inhibitor of KRASG12C(ON) and (OFF) forms. BBO-8520 binds in the Switch-II/Helix3 pocket, covalently modifies the target cysteine, and disables effector binding to KRASG12C(ON). BBO-8520 exhibits potent signaling inhibition in growth factor-activated states, in which current (OFF)-only inhibitors demonstrate little measurable activity. In vivo, BBO-8520 demonstrates rapid target engagement and inhibition of signaling, resulting in durable tumor regression in multiple models, including those resistant to KRASG12C(OFF)-only inhibitors. BBO-8520 is in phase 1 clinical trials in patients with KRASG12C non-small cell lung cancer. Significance: BBO-8520 is a first-in-class direct, small molecule covalent dual inhibitor that engages KRASG12C in the active (ON) and inactive (OFF) conformations. BBO-8520 represents a novel mechanism of action that allows for optimal target coverage and delays the emergence of adaptive resistance seen with (OFF)-only inhibitors in the clinic. See related commentary by Zhou and Westover, p. 455.

High-dimensional multiplexed imaging can reveal the spatial organization of tumour tissues at the molecular level. However, owing to the scale and information complexity of the imaging data, it is challenging to discover and thoroughly characterize the heterogeneity of tumour microenvironments. Here we show that self-supervised representation learning on data from imaging mass cytometry can be leveraged to distinguish morphological differences in tumour microenvironments and to precisely characterize distinct microenvironment signatures. We used self-supervised masked image modelling to train a vision transformer that directly takes high-dimensional multiplexed mass-cytometry images. In contrast with traditional spatial analyses relying on cellular segmentation, the vision transformer is segmentation-free, uses pixel-level information, and retains information on the local morphology and biomarker distribution. By applying the vision transformer to a lung-tumour dataset, we identified and validated a monocytic signature that is associated with poor prognosis.

KRAS is the most frequently mutated oncogene in lung adenocarcinoma, with G12C and G12V being the most predominant forms. Recent breakthroughs in KRASG12C inhibitors have transformed the clinical management of patients with G12C mutation and advanced our understanding of its function. However, little is known about the targeted disruption of KRASG12V, partly due to a lack of specific inhibitors. Here, we leverage the degradation tag (dTAG) system to develop a KRASG12V transgenic mouse model. We explore the therapeutic potential of KRASG12V degradation and characterize its impact on the tumor microenvironment (TME). Our study reveals that degrading KRASG12V abolishes lung and pancreatic tumors in mice and causes a robust inhibition of KRAS-regulated cancer intrinsic signaling. Importantly, targeted degradation of KRASG12V reprograms the TME towards a stimulatory milieu and drives antitumor immunity, elicited mainly by effector and cytotoxic CD8+ T cells. Our work provides important insights into the impact of degrading KRASG12V on both tumor progression and immune response, highlighting degraders as a powerful strategy for targeting KRAS mutant cancers.

Although adeno-to-squamous transition (AST) has been observed in association with resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) in clinic, its causality, molecular mechanism and overcoming strategies remain largely unclear. We here demonstrate that squamous transition occurs concomitantly with TKI resistance in PC9-derived xenograft tumors. Perturbation of squamous transition via DNp63 overexpression or knockdown leads to significant changes in TKI responses, indicative of a direct causal link between squamous transition and TKI resistance. Integrative RNA-seq, ATAC-seq analyses and functional studies reveal that FOXA1 plays an important role in maintaining adenomatous lineage and contributes to TKI sensitivity. FOXM1 overexpression together with FOXA1 knockout fully recapitulates squamous transition and TKI resistance in both PC9 xenografts and patient-derived xenograft (PDX) models. Importantly, pharmacological inhibition of RAPGEF3 combined with EGFR TKI efficiently overcomes TKI resistance, especially in RAPGEF3^high PDXs. Our findings provide novel mechanistic insights into squamous transition and therapeutic strategy to overcome EGFR TKI resistance in lung cancer.

Lung cancer screening via annual low-dose computed tomography (LDCT) has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by an LDCT. Changes in genome-wide cell-free DNA (cfDNA) fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples, and then validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer, and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a five-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.

Tumor-educated platelets (TEPs) are a potential method of liquid biopsy for the diagnosis and monitoring of cancer. However, the mechanism underlying tumor education of platelets is not known, and transcripts associated with TEPs are often not tumor-associated transcripts. We demonstrated that direct tumor transfer of transcripts to circulating platelets is an unlikely source of the TEP signal. We used CDSeq, a latent Dirichlet allocation algorithm, to deconvolute the TEP signal in blood samples from patients with glioblastoma. We demonstrated that a substantial proportion of transcripts in the platelet transcriptome are derived from nonplatelet cells, and the use of this algorithm allows the removal of contaminant transcripts. Furthermore, we used the results of this algorithm to demonstrate that TEPs represent a subset of more activated platelets, which also contain transcripts normally associated with nonplatelet inflammatory cells, suggesting that these inflammatory cells, possibly in the tumor microenvironment, transfer transcripts to platelets that are then found in circulation. Our analysis suggests a useful and efficient method of processing TEP transcriptomic data to enable the isolation of a unique TEP signal associated with specific tumors.

Small cell lung cancer (SCLC) presents as a highly chemosensitive malignancy but acquires cross-resistance after relapse. This transformation is nearly inevitable in patients but has been difficult to capture in laboratory models. Here, we present a pre-clinical system that recapitulates acquired cross-resistance, developed from 51 patient-derived xenograft (PDX) models. Each model was tested in vivo against three clinical regimens: cisplatin plus etoposide, olaparib plus temozolomide, and topotecan. These drug-response profiles captured hallmark clinical features of SCLC, such as the emergence of treatment-refractory disease after early relapse. For one patient, serial PDX models revealed that cross-resistance was acquired through MYC amplification on extrachromosomal DNA (ecDNA). Genomic and transcriptional profiles of the full PDX panel revealed that MYC paralog amplifications on ecDNAs were recurrent in relapsed cross-resistant SCLC, and this was corroborated in tumor biopsies from relapsed patients. We conclude that ecDNAs with MYC paralogs are recurrent drivers of cross-resistance in SCLC.

Loss-of-function mutations in KEAP1 frequently occur in lung cancer and are associated with poor prognosis and resistance to standard of care treatment, highlighting the need for the development of targeted therapies. We previously showed that KEAP1 mutant tumors consume glutamine to support the metabolic rewiring associated with NRF2-dependent antioxidant production. Here, using preclinical patient-derived xenograft models and antigenic orthotopic lung cancer models, we show that the glutamine antagonist prodrug DRP-104 impairs the growth of KEAP1 mutant tumors. We find that DRP-104 suppresses KEAP1 mutant tumors by inhibiting glutamine-dependent nucleotide synthesis and promoting antitumor T cell responses. Using multimodal single-cell sequencing and ex vivo functional assays, we demonstrate that DRP-104 reverses T cell exhaustion, decreases T_regs, and enhances the function of CD4 and CD8 T cells, culminating in an improved response to anti-PD1 therapy. Our preclinical findings provide compelling evidence that DRP-104, currently in clinical trials, offers a promising therapeutic approach for treating patients with KEAP1 mutant lung cancer.