Patient-derived response estimates from zero-passage organoids of luminal breast cancer.

Background: Primary luminal breast cancer cells lose their identity rapidly in standard tissue culture, which is problematic for testing hormone interventions and molecular pathways specific to the luminal subtype. Breast cancer organoids are thought to retain tumor characteristics better, but long-term viability of luminal-subtype cases is a persistent challenge. Our goal was to adapt short-term organoids of luminal breast cancer for parallel testing of genetic and pharmacologic perturbations. Methods: We freshly isolated patient-derived cells from luminal tumor scrapes, miniaturized the organoid format into 5 µl replicates for increased throughput, and set an endpoint of 14 days to minimize drift. Therapeutic hormone targeting was mimicked in these "zero-passage" organoids by withdrawing ß-estradiol and adding 4-hydroxytamoxifen. We also examined sulforaphane as an electrophilic stress and commercial neutraceutical with reported anti-cancer properties. Downstream mechanisms were tested genetically by lentiviral transduction of two complementary sgRNAs and Cas9 stabilization for the first week of organoid culture. Transcriptional changes were measured by RT-qPCR or RNA sequencing, and organoid phenotypes were quantified by serial brightfield imaging, digital image segmentation, and regression modeling of cellular doubling times. Results: We achieved >50% success in initiating luminal breast cancer organoids from tumor scrapes and maintaining them to the 14-day zero-passage endpoint. Success was mostly independent of clinical parameters, supporting general applicability of the approach. Abundance of ESR1 and PGR in zero-passage organoids consistently remained within the range of patient variability at the endpoint. However, responsiveness to hormone withdrawal and blockade was highly variable among luminal breast cancer cases tested. Combining sulforaphane with knockout of NQO1 (a phase II antioxidant response gene and downstream effector of sulforaphane) also yielded a breadth of organoid growth phenotypes, including growth inhibition with sulforaphane, growth promotion with NQO1 knockout, and growth antagonism when combined. Conclusions: Zero-passage organoids are a rapid and scalable way to interrogate properties of luminal breast cancer cells from patient-derived material. This includes testing drug mechanisms of action in different clinical cohorts. A future goal is to relate inter-patient variability of zero-passage organoids to long-term outcomes.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer.

Basal-like breast cancer (BLBC) is highly aggressive, and often characterized by BRCA1 and p53 deficiency. Although conventional mouse models enabled the investigation of BLBC at malignant stages, its initiation and pre-malignant progression remain understudied. Here, we leveraged a mouse genetic system known as mosaic analysis with double markers (MADM) to study BLBC initiation by generating rare GFP+Brca1, p53-deficient mammary cells alongside RFP+ wild-type sibling cells. After confirming the close resemblance of mammary tumors arising in this model to human BLBC at both transcriptomic and genomic levels, we focused our studies on the pre-malignant progression of BLBC. Initiated GFP+ mutant cells showed a stepwise pre-malignant progression trajectory from focal expansion to hyper-alveolarization and then to micro-invasion. Furthermore, despite morphological similarities to alveoli, hyper-alveolarized structures actually originate from ductal cells based on twin-spot analysis of GFP-RFP sibling cells. Finally, luminal-to-basal transition occurred exclusively in cells that have progressed to micro-invasive lesions. Our MADM model provides excellent spatiotemporal resolution to illuminate the pre-malignant progression of BLBC, and should enable future studies on early detection and prevention for this cancer.

Proteome-wide copy-number estimation from transcriptomics.

Protein copy numbers constrain systems-level properties of regulatory networks, but absolute proteomic data remain scarce compared to transcriptomics obtained by RNA sequencing. We addressed this persistent gap by relating mRNA to protein statistically using best-available data from quantitative proteomics-transcriptomics for 4366 genes in 369 cell lines. The approach starts with a central estimate of protein copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model that links mRNAs to protein. For dozens of independent cell lines and primary prostate samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, and empirical protein-to-mRNA ratios. The optimal mRNA-to-protein relationships capture biological processes along with hundreds of known protein-protein interaction complexes, suggesting mechanistic relationships are embedded. We use the method to estimate viral-receptor abundances of CD55-CXADR from human heart transcriptomes and build 1489 systems-biology models of coxsackievirus B3 infection susceptibility. When applied to 796 RNA sequencing profiles of breast cancer from The Cancer Genome Atlas, inferred copy-number estimates collectively reclassify 26% of Luminal A and 29% of Luminal B tumors. Protein-based reassignments strongly involve a pharmacologic target for luminal breast cancer (CDK4) and an α-catenin that is often undetectable at the mRNA level (CTTNA2). Thus, by adopting a gene-centered perspective of mRNA-protein covariation across different biological contexts, we achieve accuracies comparable to the technical reproducibility limits of contemporary proteomics. The collection of gene-specific models is assembled as a web tool for users seeking mRNA-guided predictions of absolute protein abundance (http://janeslab.shinyapps.io/Pinferna).

Biphasic JNK-Erk signaling separates the induction and maintenance of cell senescence after DNA damage induced by topoisomerase II inhibition.

Genotoxic stress in mammalian cells, including those caused by anti-cancer chemotherapy, can induce temporary cell-cycle arrest, DNA damage-induced senescence (DDIS), or apoptotic cell death. Despite obvious clinical importance, it is unclear how the signals emerging from DNA damage are integrated together with other cellular signaling pathways monitoring the cell's environment and/or internal state to control different cell fates. Using single-cell-based signaling measurements combined with tensor partial least square regression (t-PLSR)/principal component analysis (PCA) analysis, we show that JNK and Erk MAPK signaling regulates the initiation of cell senescence through the transcription factor AP-1 at early times after doxorubicin-induced DNA damage and the senescence-associated secretory phenotype (SASP) at late times after damage. These results identify temporally distinct roles for signaling pathways beyond the classic DNA damage response (DDR) that control the cell senescence decision and modulate the tumor microenvironment and reveal fundamental similarities between signaling pathways responsible for oncogene-induced senescence (OIS) and senescence caused by topoisomerase II inhibition. A record of this paper's transparent peer review process is included in the supplemental information.

Acute myeloid leukemia stratifies as two clinically relevant sphingolipidomic subtypes.

Acute myeloid leukemia (AML) is an aggressive disease with complex and heterogeneous biology. Although several genomic classifications have been proposed, there is a growing interest in going beyond genomics to stratify AML. In this study, we profile the sphingolipid family of bioactive molecules in 213 primary AML samples and 30 common human AML cell lines. Using an integrative approach, we identify two distinct sphingolipid subtypes in AML characterized by a reciprocal abundance of hexosylceramide (Hex) and sphingomyelin (SM) species. The two Hex-SM clusters organize diverse samples more robustly than known AML driver mutations and are coupled to latent transcriptional states. Using transcriptomic data, we develop a machine-learning classifier to infer the Hex-SM status of AML cases in TCGA and BeatAML clinical repositories. The analyses show that the sphingolipid subtype with deficient Hex and abundant SM is enriched for leukemic stemness transcriptional programs and comprises an unappreciated high-risk subgroup with poor clinical outcomes. Our sphingolipid-focused examination of AML identifies patients least likely to benefit from standard of care and raises the possibility that sphingolipidomic interventions could switch the subtype of AML patients who otherwise lack targetable alternatives.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer.

Basal-like breast cancer is an aggressive breast cancer subtype, often characterized by a deficiency in BRCA1 function and concomitant loss of p53 . While conventional mouse models enable the investigation of its malignant stages, one that reveals its initiation and pre-malignant progression is lacking. Here, we leveraged a mouse genetic system known as M osaic A nalysis with D ouble M arkers (MADM) to generate rare GFP-labeled Brca1 , p53 -deficient cells alongside RFP+ wildtype sibling cells in the mammary gland. The mosaicism resembles the sporadic initiation of human cancer and enables spatially resolved analysis of mutant cells in comparison to paired wildtype sibling cells. Mammary tumors arising in the model show transcriptomic and genomic characteristics similar to human basal-like breast cancer. Analysis of GFP+ mutant cells at interval time points before malignancy revealed a stepwise progression of lesions from focal expansion to hyper-alveolarization and then to micro-invasion. These stereotyped morphologies indicate the pre-malignant stage irrespective of the time point at which it is observed. Paired analysis of GFP-RFP siblings during focal expansion suggested that hyper-alveolarized structures originate from ductal rather than alveolar cells, despite their morphological similarities to alveoli. Evidence for luminal-to-basal transition at the pre-malignant stages was restricted to cells that had escaped hyper-alveoli and progressed to micro-invasive lesions. Our MADM-based mouse model presents a useful tool for studying the pre-malignancy of basal-like breast cancer. Summary statement: A mouse model recapitulates the process of human basal-like breast tumorigenesis initiated from sporadic Brca1, p53 -deficient cells, empowering spatially-resolved analysis of mutant cells during pre-malignant progression.

Dichotomous ovarian cancer-initiating potential of Pax8+ cells revealed by a mouse genetic mosaic model.

Different cellular compartments within a tissue present distinct cancer-initiating capacities. Current approaches to dissect such heterogeneity require cell-type-specific genetic tools based on a well-understood lineage hierarchy, which are lacking for many tissues. Here, we circumvented this hurdle and revealed the dichotomous capacity of fallopian tube Pax8+ cells in initiating ovarian cancer, utilizing a mouse genetic system that stochastically generates rare GFP-labeled mutant cells. Through clonal analysis and spatial profiling, we determined that only clones founded by rare, stem/progenitor-like Pax8+ cells can expand on acquiring oncogenic mutations whereas vast majority of clones stall immediately. Furthermore, expanded mutant clones undergo further attrition: many turn quiescent shortly after the initial expansion, whereas others sustain proliferation and manifest a bias toward Pax8+ fate, underlying early pathogenesis. Our study showcases the power of genetic mosaic system-based clonal analysis for revealing cellular heterogeneity of cancer-initiating capacity in tissues with limited prior knowledge of lineage hierarchy.

Nucleocytoplasmic transport of active HER2 causes fractional escape from the DCIS-like state.

Activation of HER2/ErbB2 coincides with escape from ductal carcinoma in situ (DCIS) premalignancy and disrupts 3D organization of cultured breast-epithelial spheroids. The 3D phenotype is infrequent, however, and mechanisms for its incomplete penetrance have been elusive. Using inducible HER2/ErbB2-EGFR/ErbB1 heterodimers, we match phenotype penetrance to the frequency of co-occurring transcriptomic changes and uncover a reconfiguration in the karyopherin network regulating ErbB nucleocytoplasmic transport. Induction of the exportin CSE1L inhibits nuclear accumulation of ErbBs, whereas nuclear ErbBs silence the importin KPNA1 by inducing miR-205. When these negative feedbacks are incorporated into a validated systems model of nucleocytoplasmic transport, steady-state localization of ErbB cargo becomes ultrasensitive to initial CSE1L abundance. Erbb2-driven carcinomas with Cse1l deficiency outgrow less irregularly from mammary ducts, and NLS-attenuating mutants or variants of HER2 favor escape in 3D culture. We conclude here that adaptive nucleocytoplasmic relocalization of HER2 creates a systems-level molecular switch at the premalignant-to-malignant transition.

Pan-Cancer Drivers Are Recurrent Transcriptional Regulatory Heterogeneities in Early-Stage Luminal Breast Cancer.

The heterogeneous composition of solid tumors is known to impact disease progression and response to therapy. Malignant cells coexist in different regulatory states that can be accessed transcriptomically by single-cell RNA sequencing, but these methods have many caveats related to sensitivity, noise, and sample handling. We revised a statistical fluctuation analysis called stochastic profiling to combine with 10-cell RNA sequencing, which was designed for laser-capture microdissection (LCM) and extended here for immuno-LCM. When applied to a cohort of late-onset, early-stage luminal breast cancers, the integrated approach identified thousands of candidate regulatory heterogeneities. Intersecting the candidates from different tumors yielded a relatively stable set of 710 recurrent heterogeneously expressed genes (RHEG), which were significantly variable in >50% of patients. RHEGs were not strongly confounded by dissociation artifacts, cell-cycle oscillations, or driving mutations for breast cancer. Rather, RHEGs were enriched for epithelial-to-mesenchymal transition genes and, unexpectedly, the latest pan-cancer assembly of driver genes across cancer types other than breast. These findings indicate that heterogeneous transcriptional regulation conceivably provides a faster, reversible mechanism for malignant cells to evaluate the effects of potential oncogenes or tumor suppressors on cancer hallmarks. SIGNIFICANCE: Profiling intratumor heterogeneity of luminal breast carcinoma cells identifies a recurrent set of genes, suggesting sporadic activation of pathways known to drive other types of cancer.See related articles by Schaff and colleagues, p. 1853 and Sutcliffe and colleagues, p. 1868.

Premalignant Oligodendrocyte Precursor Cells Stall in a Heterogeneous State of Replication Stress Prior to Gliomagenesis.

Cancer evolves from premalignant clones that adopt unusual cell states to achieve transformation. We previously pinpointed the oligodendrocyte precursor cell (OPC) as a cell of origin for glioma, but the early changes of mutant OPCs during premalignancy remained unknown. Using mice engineered for inducible Nf1-Trp53 loss in OPCs, we acutely isolated labeled mutant OPCs by laser-capture microdissection, determined global gene-expression changes by bulk RNA sequencing, and compared with cell-state fluctuations at the single-cell level by stochastic profiling, which uses RNA-sequencing measurements from random pools of 10 mutant cells. At 12 days after Nf1-Trp53 deletion, bulk differences were mostly limited to mitotic hallmarks and genes for ribosome biosynthesis, and stochastic profiling revealed a spectrum of stem-progenitor (Axl, Aldh1a1), proneural, and mesenchymal states as potential starting points for gliomagenesis. At 90 days, bulk sequencing detected few differentially expressed transcripts, whereas stochastic profiling revealed cell states for neurons and mural cells that do not give rise to glial tumors, suggesting cellular dead-ends for gliomagenesis. Importantly, mutant OPCs that strongly expressed key effectors of nonsense-mediated decay (Upf3b) and homology-dependent DNA repair (Rad51c, Slx1b, Ercc4) were identified along with DNA-damage markers, suggesting transcription-associated replication stress. Analysis of 10-cell transcriptomes at 90 days identified a locus of elevated gene expression containing an additional repair endonuclease (Mus81) and Rin1, a Ras-Raf antagonist and possible counterbalance to Nf1 loss, which was microdeleted or downregulated in gliomas at 150 days. These hidden cell-state variations uncover replication stress as a potential bottleneck that must be resolved for glioma initiation. SIGNIFICANCE: Profiling premalignant cell states in a mouse model of glioma uncovers regulatory heterogeneity in glioma cells-of-origin and defines a state of replication stress that precedes tumor initiation.See related articles by Singh and colleagues, p. 1840 and Schaff and colleagues, p. 1853.

Fragmentation of Small-Cell Lung Cancer Regulatory States in Heterotypic Microenvironments.

Small-cell lung cancers derive from pulmonary neuroendocrine cells, which have stem-like properties to reprogram into other cell types upon lung injury. It is difficult to uncouple transcriptional plasticity of these transformed cells from genetic changes that evolve in primary tumors or secondary metastases. Profiling of single cells is also problematic if the required sample dissociation activates injury-like signaling and reprogramming. Here we defined cell-state heterogeneities in situ through laser capture microdissection-based 10-cell transcriptomics coupled with stochastic-profiling fluctuation analysis. In labeled cells from a small-cell lung cancer mouse model initiated by neuroendocrine deletion of Rb1-Trp53, variations in transcript abundance revealed cell-to-cell differences in regulatory state in vitro and in vivo. Fluctuating transcripts in spheroid culture were partly shared among Rb1-Trp53-null models, and heterogeneities increased considerably when cells were delivered intravenously to colonize the liver. Colonization of immunocompromised animals drove a fractional appearance of alveolar type II-like markers and poised cells for paracrine stimulation from immune cells and hepatocytes. Immunocompetency further exaggerated the fragmentation of tumor states in the liver, yielding mixed stromal signatures evident in bulk sequencing from autochthonous tumors and metastases. Dozens of transcript heterogeneities recurred irrespective of biological context; their mapped orthologs brought together observations of murine and human small-cell lung cancer. Candidate heterogeneities recurrent in the liver also stratified primary human tumors into discrete groups not readily explained by molecular subtype but with prognostic relevance. These data suggest that heterotypic interactions in the liver and lung are an accelerant for intratumor heterogeneity in small-cell lung cancer. SIGNIFICANCE: These findings demonstrate that the single-cell regulatory heterogeneity of small-cell lung cancer becomes increasingly elaborate in the liver, a common metastatic site for the disease.See related articles by Singh and colleagues, p. 1840 and Sutcliffe and colleagues, p. 1868.

Sporadic activation of an oxidative stress-dependent NRF2-p53 signaling network in breast epithelial spheroids and premalignancies.

Breast and mammary epithelial cells experience different local environments during tissue development and tumorigenesis. Microenvironmental heterogeneity gives rise to distinct cell regulatory states whose identity and importance are just beginning to be appreciated. Cellular states diversify when clonal three-dimensional (3D) spheroids are cultured in basement membrane, and one such state is associated with stress tolerance and poor response to anticancer therapeutics. Here, we found that this state was jointly coordinated by the NRF2 and p53 pathways, which were costabilized by spontaneous oxidative stress within 3D cultures. Inhibition of NRF2 or p53 individually disrupted some of the transcripts defining the regulatory state but did not yield a notable phenotype in nontransformed breast epithelial cells. In contrast, combined perturbation prevented 3D growth in an oxidative stress-dependent manner. By integrating systems models of NRF2 and p53 signaling in a single oxidative stress network, we recapitulated these observations and made predictions about oxidative stress profiles during 3D growth. NRF2 and p53 signaling were similarly coordinated in normal breast epithelial tissue and hormone-negative ductal carcinoma in situ lesions but were uncoupled in triple-negative breast cancer (TNBC), a subtype in which p53 is usually mutated. Using the integrated model, we correlated the extent of this uncoupling in TNBC cell lines with the importance of NRF2 in the 3D growth of these cell lines and their predicted handling of oxidative stress. Our results point to an oxidative stress tolerance network that is important for single cells during glandular development and the early stages of breast cancer.

Astrocytic trans-Differentiation Completes a Multicellular Paracrine Feedback Loop Required for Medulloblastoma Tumor Growth.

The tumor microenvironment (TME) is critical for tumor progression. However, the establishment and function of the TME remain obscure because of its complex cellular composition. Using a mouse genetic system called mosaic analysis with double markers (MADMs), we delineated TME evolution at single-cell resolution in sonic hedgehog (SHH)-activated medulloblastomas that originate from unipotent granule neuron progenitors in the brain. First, we found that astrocytes within the TME (TuAstrocytes) were trans-differentiated from tumor granule neuron precursors (GNPs), which normally never differentiate into astrocytes. Second, we identified that TME-derived IGF1 promotes tumor progression. Third, we uncovered that insulin-like growth factor 1 (IGF1) is produced by tumor-associated microglia in response to interleukin-4 (IL-4) stimulation. Finally, we found that IL-4 is secreted by TuAstrocytes. Collectively, our studies reveal an evolutionary process that produces a multi-lateral network within the TME of medulloblastoma: a fraction of tumor cells trans-differentiate into TuAstrocytes, which, in turn, produce IL-4 that stimulates microglia to produce IGF1 to promote tumor progression.

An ultrasensitive fiveplex activity assay for cellular kinases.

Protein kinases are enzymes whose abundance, protein-protein interactions, and posttranslational modifications together determine net signaling activity in cells. Large-scale data on cellular kinase activity are limited, because existing assays are cumbersome, poorly sensitive, low throughput, and restricted to measuring one kinase at a time. Here, we surmount the conventional hurdles of activity measurement with a multiplexing approach that leverages the selectivity of individual kinase-substrate pairs. We demonstrate proof of concept by designing an assay that jointly measures activity of five pleiotropic signaling kinases: Akt, IκB kinase (IKK), c-jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK)-extracellular regulated kinase kinase (MEK), and MAPK-activated protein kinase-2 (MK2). The assay operates in a 96-well format and specifically measures endogenous kinase activation with coefficients of variation less than 20%. Multiplex tracking of kinase-substrate pairs reduces input requirements by 25-fold, with ~75 µg of cellular extract sufficient for fiveplex activity profiling. We applied the assay to monitor kinase signaling during coxsackievirus B3 infection of two different host-cell types and identified multiple differences in pathway dynamics and coordination that warrant future study. Because the Akt-IKK-JNK-MEK-MK2 pathways regulate many important cellular functions, the fiveplex assay should find applications in inflammation, environmental-stress, and cancer research.

In situ 10-cell RNA sequencing in tissue and tumor biopsy samples.

Single-cell transcriptomic methods classify new and existing cell types very effectively, but alternative approaches are needed to quantify the individual regulatory states of cells in their native tissue context. We combined the tissue preservation and single-cell resolution of laser capture with an improved preamplification procedure enabling RNA sequencing of 10 microdissected cells. This in situ 10-cell RNA sequencing (10cRNA-seq) can exploit fluorescent reporters of cell type in genetically engineered mice and is compatible with freshly cryoembedded clinical biopsies from patients. Through recombinant RNA spike-ins, we estimate dropout-free technical reliability as low as ~250 copies and a 50% detection sensitivity of ~45 copies per 10-cell reaction. By using small pools of microdissected cells, 10cRNA-seq improves technical per-cell reliability and sensitivity beyond existing approaches for single-cell RNA sequencing (scRNA-seq). Detection of low-abundance transcripts by 10cRNA-seq is comparable to random 10-cell groups of scRNA-seq data, suggesting no loss of gene recovery when cells are isolated in situ. Combined with existing approaches to deconvolve small pools of cells, 10cRNA-seq offers a reliable, unbiased, and sensitive way to measure cell-state heterogeneity in tissues and tumors.

Automated brightfield morphometry of 3D organoid populations by OrganoSeg.

Spheroid and organoid cultures are powerful in vitro models for biology, but size and shape diversity within the culture is largely ignored. To streamline morphometric profiling, we developed OrganoSeg, an open-source software that integrates segmentation, filtering, and analysis for archived brightfield images of 3D culture. OrganoSeg is more accurate and flexible than existing platforms, and we illustrate its potential by stratifying 5167 breast-cancer spheroid and 5743 colon and colorectal-cancer organoid morphologies. Organoid transcripts grouped by morphometric signature heterogeneity were enriched for biological processes not prominent in the original RNA sequencing data. OrganoSeg enables complete, objective quantification of brightfield phenotypes, which may give insight into the molecular and multicellular mechanisms of organoid regulation.

Tumor-Suppressor Inactivation of GDF11 Occurs by Precursor Sequestration in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous carcinoma in which various tumor-suppressor genes are lost by mutation, deletion, or silencing. Here we report a tumor-suppressive mode of action for growth-differentiation factor 11 (GDF11) and an unusual mechanism of its inactivation in TNBC. GDF11 promotes an epithelial, anti-invasive phenotype in 3D triple-negative cultures and intraductal xenografts by sustaining expression of E-cadherin and inhibitor of differentiation 2 (ID2). Surprisingly, clinical TNBCs retain the GDF11 locus and expression of the protein itself. GDF11 bioactivity is instead lost because of deficiencies in its convertase, proprotein convertase subtilisin/kexin type 5 (PCSK5), causing inactive GDF11 precursor to accumulate intracellularly. PCSK5 reconstitution mobilizes the latent TNBC reservoir of GDF11 in vitro and suppresses triple-negative mammary cancer metastasis to the lung of syngeneic hosts. Intracellular GDF11 retention adds to the concept of tumor-suppressor inactivation and reveals a cell-biological vulnerability for TNBCs lacking therapeutically actionable mutations.

Computational Models of Reactive Oxygen Species as Metabolic Byproducts and Signal-Transduction Modulators.

Reactive oxygen species (ROS) are widely involved in intracellular signaling and human pathologies, but their precise roles have been difficult to enumerate and integrate holistically. The context- and dose-dependent intracellular effects of ROS can lead to contradictory experimental results and confounded interpretations. For example, lower levels of ROS promote cell signaling and proliferation, whereas abundant ROS cause overwhelming damage to biomolecules and cellular apoptosis or senescence. These complexities raise the question of whether the many facets of ROS biology can be joined under a common mechanistic framework using computational modeling. Here, we take inventory of some current models for ROS production or ROS regulation of signaling pathways. Several models captured non-intuitive observations or made predictions that were later verified by experiment. There remains a need for systems-level analyses that jointly incorporate ROS production, handling, and modulation of multiple signal-transduction cascades.