The objective of this work was to overcome some of the long-standing limitations of ratiometric fluorescent protein (FP)-based Ca2+ biosensors, which typically rely on Förster resonance energy transfer (FRET) between two FPs and generally exhibit only relatively modest Ca2+-dependent changes in emission ratio. To develop biosensors with substantially greater ratiometric changes, we explored an alternative biosensor design strategy in which two independently optimized intensiometric single FP-based Ca2+ biosensors were hybridized into a single protein construct such that they employed a shared calmodulin (CaM) and CaM-binding peptide (CBP). By hybridizing a direct-response red FP-based biosensor with an inverse-response green FP-based biosensor, we created SuiCa, a single-polypeptide Ca2+ biosensor that exhibits exceptionally large red-to-green ratiometric fluorescence changes as purified protein (∼60-fold) and when expressed in immortalized cell cultures (∼80-fold) and primary neurons (∼37-fold). Relative to co-expression of two spectrally distinct FP-based Ca2+ biosensors, SuiCa provides the advantages of a smaller gene size, a fixed fluorophore stoichiometry, and a ratiometric response that depends on Ca2+ binding to a single, shared, CaM plus CBP domain. With these advantages, along with its bright fluorescence and large ratiometric change, SuiCa represents a new addition to the Ca2+ imaging toolbox.

Monitoring H2O2 dynamics in conjunction with key biological interactants is critical for elucidating the physiological outcome of cellular redox regulation. Optogenetic hydrogen peroxide sensor with HaloTag with JF635 (oROS-HT635) allows fast and sensitive chemigenetic far-red H2O2 imaging while overcoming drawbacks of existing red fluorescent H2O2 indicators, including oxygen dependency, high pH sensitivity, photoartifacts and intracellular aggregation. The compatibility of oROS-HT635 with blue-green-shifted optical tools allows versatile optogenetic dissection of redox biology. In addition, targeted expression of oROS-HT635 and multiplexed H2O2 imaging enables spatially resolved imaging of H2O2 targeting the plasma membrane and neighboring cells. Here we present multiplexed use cases of oROS-HT635 with other green fluorescence reporters by capturing acute and real-time changes in H2O2 with intracellular redox potential and Ca2+ levels in response to auranofin, an inhibitor of antioxidative enzymes, via dual-color imaging. oROS-HT635 enables detailed insights into intricate intracellular and intercellular H2O2 dynamics, along with their interactants, through spatially resolved, far-red H2O2 imaging in real time.

H2O2 is a key oxidant in mammalian biology and a pleiotropic signaling molecule at the physiological level, and its excessive accumulation in conjunction with decreased cellular reduction capacity is often found to be a common pathological marker. Here, we present a red fluorescent Genetically Encoded H2O2 Indicator (GEHI) allowing versatile optogenetic dissection of redox biology. Our new GEHI, oROS-HT, is a chemigenetic sensor utilizing a HaloTag and Janelia Fluor (JF) rhodamine dye as fluorescent reporters. We developed oROS-HT through a structure-guided approach aided by classic protein structures and recent protein structure prediction tools. Optimized with JF635, oROS-HT is a sensor with 635 nm excitation and 650 nm emission peaks, allowing it to retain its brightness while monitoring intracellular H2O2 dynamics. Furthermore, it enables multi-color imaging in combination with blue-green fluorescent sensors for orthogonal analytes and low auto-fluorescence interference in biological tissues. Other advantages of oROS-HT over alternative GEHIs are its fast kinetics, oxygen-independent maturation, low pH sensitivity, lack of photo-artifact, and lack of intracellular aggregation. Here, we demonstrated efficient subcellular targeting and how oROS-HT can map inter and intracellular H2O2 diffusion at subcellular resolution. Lastly, we used oROS-HT with the green fluorescent calcium indicator Fluo-4 to investigate the transient effect of the anti-inflammatory agent auranofin on cellular redox physiology and calcium levels via multi-parametric, dual-color imaging.

Here we used machine learning to engineer genetically encoded fluorescent indicators, protein-based sensors critical for real-time monitoring of biological activity. We used machine learning to predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. The trained ensemble performed an in silico functional screen on 1,423 novel, uncharacterized GCaMP variants. As a result, we identified the ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP+, which achieve both faster kinetics and larger ∆F/F0 responses upon stimulation than previously published fast variants. Furthermore, we identified a combinatorial mutation with extraordinary dynamic range, eGCaMP2+, which outperforms the tested sixth-, seventh- and eighth-generation GCaMPs. These findings demonstrate the value of machine learning as a tool to facilitate the efficient engineering of proteins for desired biophysical characteristics.

Supplementary Table from Inhibition of Karyopherin β1-Mediated Nuclear Import Disrupts Oncogenic Lineage-Defining Transcription Factor Activity in Small Cell Lung Cancer

Genetically encoded fluorescent indicators (GEFIs) are protein-based optogenetic tools that change their fluorescence intensity when binding specific ligands in cells and tissues. GEFI encoding DNA can be expressed in cell subtypes while monitoring cellular physiological responses. However, engineering GEFIs with physiological sensitivity and pharmacological specificity often requires iterative optimization through trial-and-error mutagenesis while assessing their biophysical function in vitro one by one. Here, the vast mutational landscape of proteins constitutes a significant obstacle that slows GEFI development, particularly for sensors that rely on mammalian host systems for testing. To overcome these obstacles, we developed a multiplexed high-throughput engineering platform called the optogenetic microwell array screening system (Opto-MASS) that functionally tests thousands of GEFI variants in parallel in mammalian cells. Opto-MASS represents the next step for engineering optogenetic tools as it can screen large variant libraries orders of magnitude faster than current methods. We showcase this system by testing over 13,000 dopamine and 21,000 opioid sensor variants. We generated a new dopamine sensor, dMASS1, with a >6-fold signal increase to 100 nM dopamine exposure compared to its parent construct. Our new opioid sensor, μMASS1, has a ∼4.6-fold signal increase over its parent scaffold's response to 500 nM DAMGO. Thus, Opto-MASS can rapidly engineer new sensors while significantly shortening the optimization time for new sensors with distinct biophysical properties.

Optimizing genetically encoded fluorescent indicators (GEFIs) is intellectually and experimentally taxing. We developed a machine learning (ML) platform to discover new variants of the calcium indicator GCaMP and illustrate ML’s ability to accelerate GEFI engineering.

Supplemental Figures 1-6 and Supplemental Methods

Abstract Genomic studies support the classification of small cell lung cancer (SCLC) into subtypes based on the expression of lineage-defining transcription factors ASCL1 and NEUROD1, which together are expressed in ∼86% of SCLC. ASCL1 and NEUROD1 activate SCLC oncogene expression, drive distinct transcriptional programs, and maintain the in vitro growth and oncogenic properties of ASCL1 or NEUROD1-expressing SCLC. ASCL1 is also required for tumor formation in SCLC mouse models. A strategy to inhibit the activity of these oncogenic drivers may therefore provide both a targeted therapy for the predominant SCLC subtypes and a tool to investigate the underlying lineage plasticity of established SCLC tumors. However, there are no known agents that inhibit ASCL1 or NEUROD1 function. In this study, we identify a novel strategy to pharmacologically target ASCL1 and NEUROD1 activity in SCLC by exploiting the nuclear localization required for the function of these transcription factors. Karyopherin β1 (KPNB1) was identified as a nuclear import receptor for both ASCL1 and NEUROD1 in SCLC, and inhibition of KPNB1 led to impaired ASCL1 and NEUROD1 nuclear accumulation and transcriptional activity. Pharmacologic targeting of KPNB1 preferentially disrupted the growth of ASCL1+ and NEUROD1+ SCLC cells in vitro and suppressed ASCL1+ tumor growth in vivo, an effect mediated by a combination of impaired ASCL1 downstream target expression, cell-cycle activity, and proteostasis. These findings broaden the support for targeting nuclear transport as an anticancer therapeutic strategy and have implications for targeting lineage-transcription factors in tumors beyond SCLC. Significance: The identification of KPNB1 as a nuclear import receptor for lineage-defining transcription factors in SCLC reveals a viable therapeutic strategy for cancer treatment.

Fluorescent sensor proteins are instrumental for detecting biological signals in vivo with high temporal accuracy and cell-type specificity. However, engineering sensors with physiological ligand sensitivity and selectivity is difficult because they need to be optimized through individual mutagenesis in vitro to assess their performance. The vast mutational landscape proteins constitute an obstacle that slows down sensor development. This is particularly true for sensors that require mammalian host systems to be screened. Here, we developed a novel high-throughput engineering platform that functionally tests thousands of variants simultaneously in mammalian cells and thus allows the screening of large variant numbers. We showcase the capabilities of our platform, called Optogenetic Microwell Array Screening System (Opto-MASS), by engineering novel monoamine and neuropeptide in vivo capable sensors with distinct physiological roles at high-throughput.

ASCL1 is a neuroendocrine lineage-specific oncogenic driver of small cell lung cancer (SCLC), highly expressed in a significant fraction of tumors. However, ∼25% of human SCLC are ASCL1-low and associated with low neuroendocrine fate and high MYC expression. Using genetically engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc in the mouse lung induce an ASCL1+ state of SCLC in multiple cells of origin. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation and progression to the NEUROD1+ subtype of SCLC. Surprisingly, ASCL1 loss promotes a SOX9+ mesenchymal/neural crest stem-like state and the emergence of osteosarcoma and chondroid tumors, whose propensity is impacted by cell of origin. ASCL1 is critical for expression of key lineage-related transcription factors NKX2-1, FOXA2, and INSM1 and represses genes involved in the Hippo/Wnt/Notch developmental pathways in vivo. Importantly, ASCL1 represses a SOX9/RUNX1/RUNX2 program in vivo and SOX9 expression in human SCLC cells, suggesting a conserved function for ASCL1. Together, in a MYC-driven SCLC model, ASCL1 promotes neuroendocrine fate and represses the emergence of a SOX9+ nonendodermal stem-like fate that resembles neural crest.

Small cell lung cancer (SCLC) is a neuroendocrine tumor treated clinically as a single disease with poor outcomes. Distinct SCLC molecular subtypes have been defined based on expression of ASCL1, NEUROD1, POU2F3, or YAP1. Here, we use mouse and human models with a time-series single-cell transcriptome analysis to reveal that MYC drives dynamic evolution of SCLC subtypes. In neuroendocrine cells, MYC activates Notch to dedifferentiate tumor cells, promoting a temporal shift in SCLC from ASCL1(+) to NEUROD1(+) to YAP1(+) states. MYC alternatively promotes POU2F3(+) tumors from a distinct cell type. Human SCLC exhibits intratumoral subtype heterogeneity, suggesting that this dynamic evolution occurs in patient tumors. These findings suggest that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype.

Small-cell neuroendocrine (SCN) cancers are an aggressive cancer subtype. Transdifferentiation toward an SCN phenotype has been reported as a resistance route in response to targeted therapies. This has important consequences in that SCN cancers, once considered rare in many tissue types, may become increasingly common with the emergence of resistance cases. Here, we identified a molecular convergence to an SCN state that is more widespread across various epithelial cancers than previously realized, with these additional cases associated with poor prognosis. More broadly, non-SCN metastases have higher expression of SCN-associated transcription factors than non-SCN primary tumors. Drug sensitivity and gene dependency screens demonstrate that these convergent SCN cancers have shared vulnerabilities. These common vulnerabilities are found across unannotated SCN-like epithelial cases, pediatric small round blue cell tumors, and unexpectedly in hematologic malignancies. The SCN convergent phenotype and common sensitivity profiles with hematologic cancers can guide treatment options beyond the limitations of tissue-specific targeted therapies.

Small-cell lung cancer (SCLC) is a highly aggressive neuroendocrine lung tumor that has been treated clinically as a homogeneous disease. Recent discoveries suggest that SCLC is heterogeneous with distinct molecular subtypes. Whether metabolic differences exist among SCLC subtypes is largely unexplored. We have aimed to determine whether metabolic vulnerabilities exist between SCLC subtypes that can be therapeutically exploited. Toward this end, we performed steady-state metabolomics on tumors isolated from distinct genetically engineered mouse models (GEMMs) representing the MYC and MYCL-driven subtypes of SCLC. We discovered that SCLC subtypes driven by different MYC family members have distinct metabolic profiles. Purine nucleotide biosynthesis and arginine/urea cycle pathways were enriched specifically in MYC-driven SCLC (Huang et al., Cell Metab 2108; Chalishazar et al., Clin Can Res 2019). MYC-driven SCLC preferentially depends on arginine-regulated pathways for polyamine biosynthesis and mTOR pathway activation. Chemoresistant SCLC cells exhibited increased MYC expression and similar metabolic liabilities as chemo-naive MYC-driven cells. Arginine depletion with pegylated arginine deiminase (ADI-PEG20) dramatically suppressed tumor growth and promoted survival of mice specifically with MYC-driven tumors, including in GEMMs, human cell line xenografts, and in new patient-derived xenograft (PDX) models. ADI-PEG20 was significantly more effective than the standard-of-care chemotherapy in GEMMs; however, tumors eventually relapse and acquire resistance to ADI-PEG20. Our current efforts are focused on identifying mechanisms of ADI-PEG20 resistance. We find that expression of the arginine biosynthetic enzyme ASS1 is frequently induced in ADI-PEG20 relapsed tumors in mouse and PDX models. Metabolite profiling of ADI-PEG20-resistant tumors suggests that ASS1 induction is associated with metabolic rewiring, which we predict will be associated with new metabolic vulnerabilities. Pathway analyses of metabolite data are consistent with the notion that ASS1 induction causes increased consumption of aspartate to generate arginine, and thereby ameliorate the demand for exogenous arginine. We predict that the diversion of aspartate away from nucleotide biosynthesis will lead to increased demand on other metabolic pathways for nucleotide biosynthesis. Preliminary data have identified pathways whose inhibition may cooperate with ADI-PEG20 to further extend the survival of mice with MYC-driven SCLC.

Abstract Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor that is treated clinically as a single disease with poor outcomes. However, SCLC is recently recognized to comprise multiple molecular subsets with unique therapeutic vulnerabilities. Four distinct subtypes of SCLC have been defined based on expression of lineage-related transcription factors: ASCL1, NEUROD1, POU2F3 or YAP1. The origins of these subtypes remain unknown. We use mouse and human SCLC models with a time-series analysis of single-cell transcriptome profiling to reveal that the oncogene MYC drives the dynamic evolution of SCLC subtypes by activation of Notch signaling. MYC cooperates with Notch signaling to promote a temporal shift from an ASCL1-to-NEUROD1-to-YAP1-positive state from a neuroendocrine cell of origin, whereas MYC promotes POU2F3+ tumors from a distinct cell type. SCLC molecular subtypes are therefore not distinct, but rather represent dynamic stages of MYC-driven tumor evolution. Treatment-naive human SCLC exhibits intratumoral heterogeneity in SCLC subtypes, suggesting this dynamic evolution occurs in patient tumors. These findings demonstrate that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype. Given the reported unique therapeutic vulnerabilities of each subtype, we postulate that SCLC tumors represent a “moving therapeutic target” that may require more general, combinatorial, or plasticity-directed therapeutic approaches to combat this transcriptional flexibility. We anticipate that molecular subsets of other cancer types may also represent dynamic stages of tumor evolution. Citation Format: Abbie S. Ireland, Alexi M. Micinski, David W. Kastner, Bingqian Guo, Sarah J. Wait, Kyle B. Spainhower, Christopher C. Conley, Opal S. Chen, Matthew R. Guthrie, Danny Soltero, Yi Qiao, Xiaomeng Huang, Szabolcs Tarapcsak, Siddhartha Devarakonda, Milind D. Chalishazar, Jason Gertz, Justin C. Moser, Gabor Marth, Sonam Puri, Benjamin L. Witt, Benjamin T. Spike, Trudy G. Oliver. MYC drives temporal evolution of small cell lung cancer subtypes by reprogramming neuroendocrine fate [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-120.

Small-cell lung cancer (SCLC) has been treated in the clinic as a single disease, but our previous work demonstrated that MYC drives a unique molecular and therapeutically relevant subset of SCLC (Mollaoglu et al., Cancer Cell 2017; Chalishazar et al., Clin Can Res 2019). Four major molecular subsets of SCLC have now been identified, and they are associated with high expression of four key developmental transcription factors: ASCL1, NEUROD1, POU2F3, and YAP1 (Rudin et al., Nat Rev Can 2019). ASCL1 is a lineage-specific oncogenic driver of SCLC, highly expressed in a significant fraction of tumors, that is required for the development of SCLC in specific mouse models. However, ∼20% of human SCLC are ASCL1-low and associated with a non-neuroendocrine fate and high MYC expression. The role of ASCL1 in the MYC-driven subset of SCLC is unknown. Using genetically engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc can drive SCLC in multiple cell types of origin and that these tumors initially express ASCL1. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation but, surprisingly, converts tumors to an RUNX2+ osteogenic cell fate. Thus, ASCL1 normally represses the osteogenic fate in MYC-driven SCLC arising from multiple cells of origin. MYC-driven SCLC harbors gene signatures that resemble neural crest and mesenchymal stem cells, which have the cell fate options of becoming neuroendocrine or bone. These data suggest that ASCL1 is critical for neuroendocrine tumor cell fate even when initiated in non-neuroendocrine cells. Together, specific genetic alterations can promote remarkable plasticity or deprogramming of adult lung cells, with ASCL1 repressing the emergence of nonendodermal tumor fates.

ASCL1 is a neuroendocrine-lineage-specific oncogenic driver of small cell lung cancer (SCLC), highly expressed in a significant fraction of tumors. However, ~25% of human SCLC are ASCL1-low and associated with low-neuroendocrine fate and high MYC expression. Using genetically-engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc in the mouse lung induce an ASCL1 + state of SCLC in multiple cells of origin. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation and progression to the NEUROD1 + subtype of SCLC. Surprisingly, ASCL1 loss converts tumors to a SOX9 + mesenchymal/neural-crest-stem-like state that can differentiate into RUNX2 + bone tumors. ASCL1 represses SOX9 expression, as well as WNT and NOTCH developmental pathways, consistent with human gene expression data. Together, SCLC demonstrates remarkable cell fate plasticity with ASCL1 repressing the emergence of non-endodermal stem-like fates that have the capacity for bone differentiation.

The major types of non-small cell lung cancer, squamous cell carcinoma and adenocarcinoma, have distinct tumor immune microenvironments. Understanding the mechanisms underlying these differences is of particular importance given the success and current limitations of immunotherapy. We developed multiple mouse models of lung cancer to demonstrate that NKX2-1 potently suppresses SOX2-driven squamous tumorigenesis by repressing adeno-to-squamous transdifferentiation. Furthermore, SOX2 recruits, whereas NKX2-1 suppresses, tumor-associated neutrophils (TANs) at least partly through inverse regulation of the chemoattractant CXCL5/6. Single-cell RNA sequencing revealed that TANs exhibit tumor-promoting features and distinct gene expression profiles compared to blood neutrophils. Finally, TANs cooperate with squamous-associated genetic alterations to promote squamous tumors. These data reveal how transcription factors with key functions in normal development dictate not only cancer cell identity but also distinct tumor immune microenvironments. Citation Format: Gurkan Mollaoglu, Alex Jones, Sarah Wait, Anandaroop Mukhopadhyay, Sangmin Jeong, Rahul Arya, Soledad Camolotto, Timothy Mosbruger, Chris Stubben, Christopher Conley, Arjun Bhutkar, Jeffery Vahrenkamp, Kristofer Berrett, Melissa Cessna, Thomas Lane, Benjamin Witt, Mohamed Salama, Jason Gertz, Kevin Jones, Eric Snyder, Trudy Oliver. Lineage specifiers SOX2 and NKX2-1 inversely regulate tumor cell fate and neutrophil recruitment in lung cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B72.

The outcomes of patients with SCLC have not yet been substantially impacted by the revolution in precision oncology, primarily owing to a paucity of genetic alterations in actionable driver oncogenes. Nevertheless, systemic therapies that include immunotherapy are beginning to show promise in the clinic. Although, these results are encouraging, many patients do not respond to, or rapidly recur after, current regimens, necessitating alternative or complementary therapeutic strategies. In this review, we discuss ongoing investigations into the pathobiology of this recalcitrant cancer and the therapeutic vulnerabilities that are exposed by the disease state. Included within this discussion, is a snapshot of the current biomarker and clinical trial landscapes for SCLC. Finally, we identify key knowledge gaps that should be addressed to advance the field in pursuit of reduced SCLC mortality. This review largely summarizes work presented at the Third Biennial International Association for the Study of Lung Cancer SCLC Meeting.

AbstractPurpose:Small-cell lung cancer (SCLC) has been treated clinically as a homogeneous disease, but recent discoveries suggest that SCLC is heterogeneous. Whether metabolic differences exist among SCLC subtypes is largely unexplored. In this study, we aimed to determine whether metabolic vulnerabilities exist between SCLC subtypes that can be therapeutically exploited.Experimental Design:We performed steady state metabolomics on tumors isolated from distinct genetically engineered mouse models (GEMM) representing the MYC- and MYCL-driven subtypes of SCLC. Using genetic and pharmacologic approaches, we validated our findings in chemo-naïve and -resistant human SCLC cell lines, multiple GEMMs, four human cell line xenografts, and four newly derived PDX models.Results:We discover that SCLC subtypes driven by different MYC family members have distinct metabolic profiles. MYC-driven SCLC preferentially depends on arginine-regulated pathways including polyamine biosynthesis and mTOR pathway activation. Chemo-resistant SCLC cells exhibit increased MYC expression and similar metabolic liabilities as chemo-naïve MYC-driven cells. Arginine depletion with pegylated arginine deiminase (ADI-PEG 20) dramatically suppresses tumor growth and promotes survival of mice specifically with MYC-driven tumors, including in GEMMs, human cell line xenografts, and a patient-derived xenograft from a relapsed patient. Finally, ADI-PEG 20 is significantly more effective than the standard-of-care chemotherapy.Conclusions:These data identify metabolic heterogeneity within SCLC and suggest arginine deprivation as a subtype-specific therapeutic vulnerability for MYC-driven SCLC.