Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy.

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential-often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel-a commonly used chemotherapeutic -displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations.

Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis.

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.

Elucidation and Pharmacologic Targeting of Master Regulator Dependencies in Coexisting Diffuse Midline Glioma Subpopulations.

Diffuse Midline Gliomas (DMGs) are universally fatal, primarily pediatric malignancies affecting the midline structures of the central nervous system. Despite decades of clinical trials, treatment remains limited to palliative radiation therapy. A major challenge is the coexistence of molecularly distinct malignant cell states with potentially orthogonal drug sensitivities. To address this challenge, we leveraged established network-based methodologies to elucidate Master Regulator (MR) proteins representing mechanistic, non-oncogene dependencies of seven coexisting subpopulations identified by single-cell analysis-whose enrichment in essential genes was validated by pooled CRISPR/Cas9 screens. Perturbational profiles of 372 clinically relevant drugs helped identify those able to invert the activity of subpopulation-specific MRs for follow-up in vivo validation. While individual drugs predicted to target individual subpopulations-including avapritinib, larotrectinib, and ruxolitinib-produced only modest tumor growth reduction in orthotopic models, systemic co-administration induced significant survival extension, making this approach a valuable contribution to the rational design of combination therapy.

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer.

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up To Cancer-Mark Foundation cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including (1) favorable (for example, ATM altered) and unfavorable (for example, TERT amplified) genomic subgroups, (2) a prominent association between expression of inducible components of the immunoproteasome and response and (3) a dedifferentiated tumor-intrinsic subtype with enhanced response to checkpoint blockade. Taken together, results from this cohort demonstrate the complexity of biological determinants underlying immunotherapy outcomes and reinforce the discovery potential of integrative analysis within large, well-curated, cancer-specific cohorts.

NaRnEA: An Information Theoretic Framework for Gene Set Analysis.

Gene sets are being increasingly leveraged to make high-level biological inferences from transcriptomic data; however, existing gene set analysis methods rely on overly conservative, heuristic approaches for quantifying the statistical significance of gene set enrichment. We created Nonparametric analytical-Rank-based Enrichment Analysis (NaRnEA) to facilitate accurate and robust gene set analysis with an optimal null model derived using the information theoretic Principle of Maximum Entropy. By measuring the differential activity of ~2500 transcriptional regulatory proteins based on the differential expression of each protein's transcriptional targets between primary tumors and normal tissue samples in three cohorts from The Cancer Genome Atlas (TCGA), we demonstrate that NaRnEA critically improves in two widely used gene set analysis methods: Gene Set Enrichment Analysis (GSEA) and analytical-Rank-based Enrichment Analysis (aREA). We show that the NaRnEA-inferred differential protein activity is significantly correlated with differential protein abundance inferred from independent, phenotype-matched mass spectrometry data in the Clinical Proteomic Tumor Analysis Consortium (CPTAC), confirming the statistical and biological accuracy of our approach. Additionally, our analysis crucially demonstrates that the sample-shuffling empirical null models leveraged by GSEA and aREA for gene set analysis are overly conservative, a shortcoming that is avoided by the newly developed Maximum Entropy analytical null model employed by NaRnEA.

Network-based elucidation of colon cancer drug resistance by phosphoproteomic time-series analysis.

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. By leveraging progress in proteomic technologies and network-based methodologies, over the past decade, we developed VESPA-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and used it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogation of tumor-specific enzyme/substrate interactions accurately inferred kinase and phosphatase activity, based on their inferred substrate phosphorylation state, effectively accounting for signal cross-talk and sparse phosphoproteome coverage. The analysis elucidated time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring that was experimentally confirmed by CRISPRko assays, suggesting broad applicability to cancer and other diseases.

A genome-wide copper-sensitized screen identifies novel regulators of mitochondrial cytochrome c oxidase activity.

Copper is essential for the activity and stability of cytochrome c oxidase (CcO), the terminal enzyme of the mitochondrial respiratory chain. Loss-of-function mutations in genes required for copper transport to CcO result in fatal human disorders. Despite the fundamental importance of copper in mitochondrial and organismal physiology, systematic identification of genes that regulate mitochondrial copper homeostasis is lacking. To discover these genes, we performed a genome-wide screen using a library of DNA-barcoded yeast deletion mutants grown in copper-supplemented media. Our screen recovered a number of genes known to be involved in cellular copper homeostasis as well as genes previously not linked to mitochondrial copper biology. These newly identified genes include the subunits of the adaptor protein 3 complex (AP-3) and components of the cellular pH-sensing pathway Rim20 and Rim21, both of which are known to affect vacuolar function. We find that AP-3 and Rim mutants exhibit decreased vacuolar acidity, which in turn perturbs mitochondrial copper homeostasis and CcO function. CcO activity of these mutants could be rescued by either restoring vacuolar pH or supplementing growth media with additional copper. Consistent with these genetic data, pharmacological inhibition of the vacuolar proton pump leads to decreased mitochondrial copper content and a concomitant decrease in CcO abundance and activity. Taken together, our study uncovered novel genetic regulators of mitochondrial copper homeostasis and provided a mechanism by which vacuolar pH impacts mitochondrial respiration through copper homeostasis.

Oncoprotein-specific molecular interaction maps (SigMaps) for cancer network analyses.

Tumor-specific elucidation of physical and functional oncoprotein interactions could improve tumorigenic mechanism characterization and therapeutic response prediction. Current interaction models and pathways, however, lack context specificity and are not oncoprotein specific. We introduce SigMaps as context-specific networks, comprising modulators, effectors and cognate binding-partners of a specific oncoprotein. SigMaps are reconstructed de novo by integrating diverse evidence sources-including protein structure, gene expression and mutational profiles-via the OncoSig machine learning framework. We first generated a KRAS-specific SigMap for lung adenocarcinoma, which recapitulated published KRAS biology, identified novel synthetic lethal proteins that were experimentally validated in three-dimensional spheroid models and established uncharacterized crosstalk with RAB/RHO. To show that OncoSig is generalizable, we first inferred SigMaps for the ten most mutated human oncoproteins and then for the full repertoire of 715 proteins in the COSMIC Cancer Gene Census. Taken together, these SigMaps show that the cell's regulatory and signaling architecture is highly tissue specific.

Mitochondrial disease genes COA6, COX6B and SCO2 have overlapping roles in COX2 biogenesis.

Biogenesis of cytochrome c oxidase (CcO), the terminal enzyme of the mitochondrial respiratory chain, is a complex process facilitated by several assembly factors. Pathogenic mutations were recently reported in one such assembly factor, COA6, and our previous work linked Coa6 function to mitochondrial copper metabolism and expression of Cox2, a copper-containing subunit of CcO. However, the precise role of Coa6 in Cox2 biogenesis remained unknown. Here we show that yeast Coa6 is an orthologue of human COA6, and like Cox2, is regulated by copper availability, further implicating it in copper delivery to Cox2. In order to place Coa6 in the Cox2 copper delivery pathway, we performed a comprehensive genetic epistasis analysis in the yeast Saccharomyces cerevisiae and found that simultaneous deletion of Coa6 and Sco2, a mitochondrial copper metallochaperone, or Coa6 and Cox12/COX6B, a structural subunit of CcO, completely abrogates Cox2 biogenesis. Unlike Coa6 deficient cells, copper supplementation fails to rescue Cox2 levels of these double mutants. Overexpression of Cox12 or Sco proteins partially rescues the coa6Δ phenotype, suggesting their overlapping but non-redundant roles in copper delivery to Cox2. These genetic data are strongly corroborated by biochemical studies demonstrating physical interactions between Coa6, Cox2, Cox12 and Sco proteins. Furthermore, we show that patient mutations in Coa6 disrupt Coa6-Cox2 interaction, providing the biochemical basis for disease pathogenesis. Taken together, these results place COA6 in the copper delivery pathway to CcO and, surprisingly, link it to a previously unidentified function of CcO subunit Cox12 in Cox2 biogenesis.

Copper supplementation restores cytochrome c oxidase assembly defect in a mitochondrial disease model of COA6 deficiency.

Mitochondrial respiratory chain biogenesis is orchestrated by hundreds of assembly factors, many of which are yet to be discovered. Using an integrative approach based on clues from evolutionary history, protein localization and human genetics, we have identified a conserved mitochondrial protein, C1orf31/COA6, and shown its requirement for respiratory complex IV biogenesis in yeast, zebrafish and human cells. A recent next-generation sequencing study reported potential pathogenic mutations within the evolutionarily conserved Cx9CxnCx10C motif of COA6, implicating it in mitochondrial disease biology. Using yeast coa6Δ cells, we show that conserved residues in the motif, including the residue mutated in a patient with mitochondrial disease, are essential for COA6 function, thus confirming the pathogenicity of the patient mutation. Furthermore, we show that zebrafish embryos with zfcoa6 knockdown display reduced heart rate and cardiac developmental defects, recapitulating the observed pathology in the human mitochondrial disease patient who died of neonatal hypertrophic cardiomyopathy. The specific requirement of Coa6 for respiratory complex IV biogenesis, its intramitochondrial localization and the presence of the Cx9CxnCx10C motif suggested a role in mitochondrial copper metabolism. In support of this, we show that exogenous copper supplementation completely rescues respiratory and complex IV assembly defects in yeast coa6Δ cells. Taken together, our results establish an evolutionarily conserved role of Coa6 in complex IV assembly and support a causal role of the COA6 mutation in the human mitochondrial disease patient.