Faculty Bibliography

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

Proteogenomics is an increasingly common method for species identification as it allows for rapid and inexpensive interrogation of an unknown organism's proteome-even when the proteome is partially degraded. The proteomic method typically uses tandem mass spectrometry to survey all peptides detectable in a sample that frequently contains hundreds or thousands of proteins. Species identification is based on detection of a small numbers of species-specific peptides. Genetic analysis of proteins by mass spectrometry, however, is a developing field, and the bone proteome, typically consisting of only two proteins, pushes the limits of this technology. Nearly 20% of highly confident spectra from modern human bone samples identify non-human species when searched against a vertebrate database-as would be necessary with a fragment of unknown bone. These non-human peptides are often the result of current limitations in mass spectrometry or algorithm interpretation errors. Consequently, it is difficult to know if a "species-specific" peptide used to identify a sample is actually present in that sample. Here we evaluate the causes of peptide sequence errors and propose an unbiased, probabilistic approach to determine the likelihood that a species is correctly identified from bone without relying on species-specific peptides.

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment.

Despite the great promise of vaccines, the COVID-19 pandemic is ongoing and future serious outbreaks are highly likely, so that multi-pronged containment strategies will be required for many years. Nanobodies are the smallest naturally occurring single domain antigen binding proteins identified to date, possessing numerous properties advantageous to their production and use. We present a large repertoire of high affinity nanobodies against SARS-CoV-2 Spike protein with excellent kinetic and viral neutralization properties, which can be strongly enhanced with oligomerization. This repertoire samples the epitope landscape of the Spike ectodomain inside and outside the receptor binding domain, recognizing a multitude of distinct epitopes and revealing multiple neutralization targets of pseudoviruses and authentic SARS-CoV-2, including in primary human airway epithelial cells. Combinatorial nanobody mixtures show highly synergistic activities, and are resistant to mutational escape and emerging viral variants of concern. These nanobodies establish an exceptional resource for superior COVID-19 prophylactics and therapeutics.

Recent studies have revealed diverse amino acid, post-translational, and noncanonical modifications of proteins in diverse organisms and tissues. However, their unbiased detection and analysis remain hindered by technical limitations. Here, we present a spectral alignment method for the identification of protein modifications using high-resolution mass spectrometry proteomics. Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. Using synthetic standards and controlled chemical labeling experiments, we demonstrate its high specificity and sensitivity for the discovery of substoichiometric protein modifications in complex cellular extracts. SAMPEI mapping of mouse macrophage differentiation revealed diverse post-translational protein modifications, including distinct forms of cysteine itaconatylation. SAMPEI's robust parametrization and versatility are expected to facilitate the discovery of biological modifications of diverse macromolecules. SAMPEI is implemented as a Python package and is available open-source from BioConda and GitHub (https://github.com/FenyoLab/SAMPEI).

D-type cyclins are central regulators of the cell division cycle and are among the most frequently deregulated therapeutic targets in human cancer¹, but the mechanisms that regulate their turnover are still being debated^2,3. Here, by combining biochemical and genetics studies in somatic cells, we identify CRL4^AMBRA1 (also known as CRL4^DCAF3) as the ubiquitin ligase that targets all three D-type cyclins for degradation. During development, loss of Ambra1 induces the accumulation of D-type cyclins and retinoblastoma (RB) hyperphosphorylation and hyperproliferation, and results in defects of the nervous system that are reduced by treating pregnant mice with the FDA-approved CDK4 and CDK6 (CDK4/6) inhibitor abemaciclib. Moreover, AMBRA1 acts as a tumour suppressor in mouse models and low AMBRA1 mRNA levels are predictive of poor survival in cancer patients. Cancer hotspot mutations in D-type cyclins abrogate their binding to AMBRA1 and induce their stabilization. Finally, a whole-genome, CRISPR-Cas9 screen identified AMBRA1 as a regulator of the response to CDK4/6 inhibition. Loss of AMBRA1 reduces sensitivity to CDK4/6 inhibitors by promoting the formation of complexes of D-type cyclins with CDK2. Collectively, our results reveal the molecular mechanism that controls the stability of D-type cyclins during cell-cycle progression, in development and in human cancer, and implicate AMBRA1 as a critical regulator of the RB pathway.

Objective/UNASSIGNED:Retrospective study of COVID-19 positive patients treated at NYU Langone Health (NYULH) to identify clinical markers predictive of disease severity to assist in clinical decision triage and provide additional biological insights into disease progression. Materials and Methods/UNASSIGNED:Clinical activity of 3740 de-identified patients at NYULH between January and August 2020. Models were trained on clinical data during different parts of their hospital stay to predict three clinical outcomes: deceased, ventilated, or admitted to ICU. Results/UNASSIGNED:XGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC=0.92, specificity=86% and sensitivity=85%). Respiration rate was the most important feature, followed by SpO2 and age 75+. Performance of this model to predict the deceased outcome extended 5 days prior with AUC=0.81, specificity=70%, sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU admitted, respectively. Although respiration rate and SpO2 levels offered the highest feature importance, other canonical markers including diabetic history, age and temperature offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen (BUN) and lactate dehydrogenase (LDH). Features predictive of morbidity included LDH, calcium, glucose, and C-reactive protein (CRP). Conclusion/UNASSIGNED:Together this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.

BACKGROUND:Long INterspersed Element-1 (LINE-1) is an autonomous retroelement able to "copy-and-paste" itself into new loci of the host genome through a process called retrotransposition. The LINE-1 bicistronic mRNA codes for two proteins, ORF1p, a nucleic acid chaperone, and ORF2p, a protein with endonuclease and reverse transcriptase activity. Both proteins bind LINE-1 mRNA in cis and are necessary for retrotransposition. While LINE-1 transcription is usually repressed in most healthy somatic cells through a plethora of mechanisms, ORF1p expression has been observed in nearly 50% of tumors, and new LINE-1 insertions have been documented in a similar fraction of tumors, including prostate cancer. RESULTS:Here, we utilized RNA ImmunoPrecipitation (RIP) and the L1EM analysis software to identify ORF1p bound RNA in prostate cancer cells. We identified LINE-1 loci that were expressed in parental androgen sensitive and androgen independent clonal derivatives. In all androgen independent cells, we found higher levels of LINE-1 RNA, as well as unique expression patterns of LINE-1 loci. Interestingly, we observed that ORF1p bound many non-LINE-1 mRNA in all prostate cancer cell lines evaluated, and polyA RNA, and RNA localized in p-bodies were especially enriched. Furthermore, the expression levels of RNAs identified in our ORF1p RIP correlated with RNAs expressed in LINE-1 positive tumors from The Cancer Genome Atlas (TCGA). CONCLUSION/CONCLUSIONS:Our results show a significant remodeling of LINE-1 loci expression in androgen independent cell lines when compared to parental androgen dependent cells. Additionally, we found that ORF1p bound a significant amount of non-LINE-1 mRNA, and that the enriched ORF1p bound mRNAs are also amplified in LINE-1 expressing TCGA prostate tumors, indicating the biological relevance of our findings to prostate cancer.

Rationale: The cardiac sodium channel NaV1.5 has a fundamental role in excitability and conduction. Previous studies have shown that sodium channels cluster together in specific cellular subdomains. Their association with intracellular organelles in defined regions of the myocytes, and the functional consequences of that association, remain to be defined. Objective: To characterize a subcellular domain formed by sodium channel clusters in the crest region of the myocytes, and the subjacent subsarcolemmal mitochondria (SSM).Methods and Results: Through a combination of imaging approaches including super-resolution microscopy and electron microscopy we identified, in adult cardiac myocytes, a NaV1.5 subpopulation in close proximity to SSM; we further found that SSM preferentially host the mitochondrial Na+/Ca2+ exchanger (NCLX). This anatomical proximity led us to investigate functional changes in mitochondria resulting from sodium channel activity. Upon TTX exposure, mitochondria near NaV1.5 channels accumulated more Ca2+ and showed increased ROS production when compared to interfibrillar mitochondria. Finally, crosstalk between NaV1.5 channels and mitochondria was analyzed at a transcriptional level. We found that SCN5A and SLC8B1 (which encode NaV1.5 and NCLX, respectively) are negatively correlated both in a human transcriptome dataset (GTEx) and in human-induced pluripotent stem cell-derived cardiac myocytes deficient in SCN5A. Conclusions: We describe an anatomical hub (a couplon) formed by sodium channel clusters and SSM. Preferential localization of NCLX to this domain allows for functional coupling where the extrusion of Ca2+ from the mitochondria is powered, at least in part, by the entry of sodium through NaV1.5 channels. These results provide a novel entry-point into a mechanistic understanding of the intersection between electrical and structural functions of the heart.