Biology subjects

Sheltzer, J. M.

Publications and source records attributed to Sheltzer, J. M..

18 recordsLinked to original sources

bioRxiv2026

Systematic analysis of genetic vulnerabilities caused by chromosome loss events in cancer

Chromosome loss events are common across tumor types but rarely occur in normal tissue, raising the possibility that these alterations could be exploited as cancer-specific therapeutic vulnerabilities. Here, we integrate genome-scale CRISPR screening data with chromosome-level copy number profiles from 1,150 cancer cell lines and identify 389 dependencies that are selectively associated with individual chromosome loss events. The most significant vulnerabilities uncovered by our analysis are paralogous gene pairs, in which the loss of a paralog on an aneuploid chromosome establishes a unique dependency on its redundant paralog encoded elsewhere in the genome. We experimentally validate two paralog dependencies: loss of chromosome 8p, which encodes the phosphatase PPP2CB, creates a specific dependency on its paralog PPP2CA, while loss of the Y chromosome, which encodes the helicase DDX3Y, creates a specific dependency on its paralog DDX3X. Systematic benchmarking of CRISPR screening data indicates that the selective dependency on DDX3X in loss-of-Y cells exceeds other published aneuploidy-associated vulnerabilities and matches or exceeds most clinically-validated biomarker-target relationships. Furthermore, we found that the acute degradation of DDX3X was sufficient to trigger apoptosis in vitro and tumor regressions in mice. Collectively, these findings establish chromosome loss as a recurrent source of biomarker-defined therapeutic targets, identify paralog insufficiency as a general vulnerability in aneuploid cells, and provide in vivo proof-of-concept for targeting DDX3X in cancers with Y chromosome loss.

cancer biology↗

bioRxiv2026

Paired CRISPR screens identify mitochondrial metabolism and UBE2H as aneuploid-specific dependencies in human cancer cell lines

Aneuploidy is a hallmark of cancer and imposes widespread cellular stress, including proteotoxicity, transcriptional dysregulation, and increased metabolic demand. Although these stresses are predicted to create therapeutic vulnerabilities, the genetic dependencies of aneuploid cells remain incompletely characterized. Here, we performed paired CRISPR loss-of-function screens in isogenic aneuploid and near-euploid cancer cell line models to systematically identify aneuploidy-specific dependencies. Seven genome-wide paired screens identified ribosomes, rRNA processing, spliceosome-mediated RNA processing, proteasome subunits, and mitochondrial metabolism as top aneuploid-specific dependency gene groups. To identify therapeutically targetable aneuploid dependencies, we performed 18 additional paired CRISPR screens using a focused druggable genome library. This analysis identified the ubiquitin-conjugating enzyme UBE2H as a top aneuploid-selective dependency. Functional validation confirmed aneuploid cell dependency on UBE2H, and mechanistic analyses linked UBE2H to mitochondrial protein abundance, suggesting a role in maintaining mitochondrial proteostasis under aneuploid stress. Together, these findings define core cellular systems that support the viability of aneuploid cells and identify UBE2H as a potential therapeutic vulnerability connecting ubiquitin signaling to mitochondrial homeostasis.

cancer biology↗

bioRxiv2025

A clinical-stage oncology compound selectively targets drug-resistant cancers

Re-evaluating existing clinical compounds can uncover previously unrecognized mechanisms that reshape a drugs therapeutic potential. The small molecule Procaspase-Activating Compound 1 (PAC-1) entered oncology testing as a proposed activator of caspase-driven apoptosis. Here, we show that PAC-1-driven cytotoxicity occurs in the absence of executioner caspase expression, demonstrating that its anti-cancer activity occurs via an alternative mechanism. We provide genetic, biochemical, and biophysical evidence demonstrating that PAC-1 functions as a highly selective iron chelator that eliminates cancer cells by disrupting iron homeostasis. Unexpectedly, we discovered that expression of the key chemotherapy-resistance pump MDR1 confers marked hypersensitivity to PAC-1 treatment. While PAC-1 is only weakly effluxed by MDR1 under basal conditions, this process is potentiated when PAC-1 is bound to iron. Consequently, PAC-1 induces progressive iron depletion and selective cytotoxicity in otherwise drug-resistant MDR1-expressing cancer cells. Together, these findings redefine PAC-1s mechanism-of-action and establish a framework for exploiting multidrug resistance as a therapeutic vulnerability through targeted iron starvation.

cancer biology↗

bioRxiv2025

On-target toxicity limits the efficacy of CDK11 inhibition against cancers with 1p36 deletions

The cyclin-dependent kinase CDK11 is an understudied kinase that has been the subject of conflicting reports regarding its function in cancer. Here, we combine genetic and pharmacological approaches to demonstrate that CDK11 is a critical regulator of cancer cell survival that is required for RNA splicing and the expression of homologous recombination genes. Inhibition of CDK11 disrupts genome stability, promotes the retention of intronic sequences in mature mRNAs, and induces synthetic lethality with PARP inhibitors. Through integrative analysis of functional genomics datasets, we identify heterozygous deletions of chromosome 1p36 - which encompasses CDK11 and its activating cyclin CCNL2 - as a recurrent and predictive biomarker of sensitivity to CDK11 inhibition. To assess the therapeutic potential of CDK11, we develop MEL-495R, a selective and orally bioavailable CDK11 inhibitor. Additionally, we establish a genetically-engineered mouse model that allows us to differentiate between the on-target and off-target effects of CDK11 inhibitors in vivo. Using this platform, we demonstrate that MEL-495R induces widespread on-target toxicity, revealing a narrow therapeutic index. Together, these findings define CDK11 as a core cancer dependency, uncover a chromosomal deletion that sensitizes tumors to CDK11 inhibition, and provide a generalizable strategy for deconvolving drug efficacy and toxicity in vivo for novel oncology targets.

cancer biology↗

bioRxiv2024

Chromosome engineering to restore euploidy in cells harboring a complex rearrangement of chromosome 8

Chromosomal rearrangements on the short arm of Chromosome 8 cause 8p syndrome, a rare developmental disorder characterized by neurodevelopmental delays, epilepsy, and cardiac abnormalities. While significant progress has been made in managing the symptoms of 8p syndrome and other conditions caused by large-scale chromosomal aneuploidies, no therapeutic approach has yet been demonstrated to target the underlying disease-causing chromosome. Here, we establish a two-step approach to eliminate the abnormal copy of Chromosome 8 and restore euploidy in cells derived from an individual with a complex rearrangement of Chromosome 8p. Transcriptomic analysis revealed 361 differentially expressed genes between the proband and the euploid revertant, highlighting genes both within and outside the 8p region that may contribute to 8p syndrome pathology. Furthermore, we demonstrate that the proband exhibits a significant defect in neural differentiation that could be partially rescued by treatment with small-molecule inhibitors of cell death. Our work demonstrates the feasibility of using chromosome engineering to correct complex aneuploidies in vitro and establishes a platform to further dissect the pathophysiology of 8p syndrome and other conditions caused by chromosomal rearrangements.

developmental biology↗

bioRxiv2023

Oncogene-like addiction to aneuploidy in human cancers

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses TP53 signaling, and we show that TP53 mutations are mutually-exclusive with 1q aneuploidy in human cancers. Thus, specific aneuploidies play essential roles in tumorigenesis, raising the possibility that targeting these "aneuploidy addictions" could represent a novel approach for cancer treatment.

cancer biology↗

bioRxiv2022

A drug's most potent target is not necessarily the source of its anti-cancer activity

The small-molecule drug ralimetinib was developed as an inhibitor of the kinase p38, and it has advanced to phase 2 clinical trials in oncology. Here, we apply a multi-modal approach to demonstrate that ralimetinibs anti-cancer activity occurs due to its ability to inhibit EGFR, rather than p38. We find that cancer cell lines driven by EGFR mutations exhibit the greatest sensitivity to ralimetinib treatment, and ralimetinib phenocopies established EGFR inhibitors in pharmacogenomic profiling experiments. We further demonstrate that ralimetinib inhibits EGFR kinase activity in vitro and in cellulo, albeit at >30-fold higher concentrations than it inhibits p38. Finally, while deletion of the gene encoding p38 has no effect on ralimetinib sensitivity, expression of the EGFR-T790M gatekeeper mutation confers resistance to ralimetinib treatment. These findings suggest that future clinical trials involving ralimetinib could incorporate EGFR mutation status as a biomarker to identify sensitive patients. Moreover, our results demonstrate that a compounds anti-cancer effects should not necessarily be attributed to the protein that it inhibits most strongly, and instead, comprehensive cellular and genetic profiling is required to understand a drugs mechanism-of-action.

cancer biology↗

bioRxiv2022

Evolving copy number gains promote tumor expansion and bolster mutational diversification

Charting the evolutionary history of rampant somatic copy number alterations (SCNA) is an indispensable step toward a deeper understanding of their roles in tumor development. However, the existing SCNA timing analysis is limited to low copy number states and initiating gains, which are not necessarily close to the onset of the malignant proliferation. Moreover, it remains a critical question if the timing of an SCNA reveals the corresponding variants fitness effect. Here we propose a framework to estimate the arrival time of a clonal SCNA, i.e., the time delay from its last alteration to the start of population expansion, in addition to its initiation time when the first alteration occurs. Our method leverages the bias that a genomic segment, when resting on a copy number (CN) state, accumulates somatic single nucleotide variants (SSNV) at a rate proportional to its CN. From the whole genome sequencing data of 184 samples from 75 patients across five tumor types, we commonly observed late clonal CN gains following early initiating events, which appear right before the expansion leading to the observed tumor sample(s). Genome doubling (GD) can be late, but post-GD CN evolution is prevalent in the genealogy of the most recent common ancestor of patient tumors. Notably, mathematical modeling suggests that late evolving events could contain rate-limiting drivers. The advantage of evolving gains could arise from the dosage increase of cancer genes in proliferative signaling and amplification of early functional variants. In addition, evolving SCNAs bolster the diversification of SSNVs between sub-populations, exacerbating the vicious circle between malignant growth and accumulation of genomic heterogeneity. Our findings have broad implications for resolving the trajectory of SCNAs, discerning the CN markers of malignant growth in vivo, and properly quantifying tumor heterogeneity in aneuploid tumors.

genomics↗

bioRxiv2021

Extensive protein dosage compensation in aneuploid human cancers

Aneuploidy is a hallmark of human cancers, but the effects of aneuploidy on protein expression remain poorly understood. To uncover how chromosome copy number changes influence the cancer proteome, we have conducted an analysis of hundreds of human cancer cell lines with matched copy number, RNA expression, and protein expression data. We found that a majority of proteins exhibit dosage compensation and fail to change by the degree expected based on chromosome copy number alone. We uncovered a variety of gene groups that were recurrently buffered upon both chromosome gain and loss, including protein complex subunits and cell cycle genes. Several genetic and biophysical factors were predictive of protein buffering, highlighting complex post-translational regulatory mechanisms that maintain appropriate gene product dosage. Finally, we established that chromosomal aneuploidy has an unexpectedly moderate effect on the expression of oncogenes and tumor suppressors, demonstrating that these key cancer drivers can be subject to dosage compensation as well. In total, our comprehensive analysis of aneuploidy and dosage compensation across cancers will help identify the key driver genes encoded on altered chromosomes and will shed light on the overall consequences of aneuploidy during tumor development.

genomics↗

bioRxiv2021

Combustible and electronic cigarette exposures increase ACE2 activity and SARS-CoV-2 Spike binding

The outbreak of coronavirus disease 2019 (COVID-19) has extensively impacted global health. The causative pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), binds to the angiotensin-converting enzyme 2 (ACE2) receptor, a transmembrane metallo-carboxypeptidase that is expressed in both membrane-anchored (mACE2) and soluble (sACE2) forms in the lung. Tobacco use has been speculated as a vulnerability factor for contracting SARS-CoV-2 infection and subsequent disease severity, whilst electronic cigarettes (e-cigarettes) have been shown to induce harmful proteomic and immune changes in the lungs of vapers. We therefore tested the hypothesis that combustible tobacco (e.g. cigarettes) and non-combustible e-cigarettes could affect ACE2 activity and subsequent SARS-CoV-2 infection. We observed that sACE2 activity was significantly higher in bronchoalveolar lavage fluid from both smokers and vapers compared to age-matched non-smokers. Exposure to cigarette smoke increased ACE2 levels, mACE2 activity, and sACE2 in primary bronchial epithelial cultures. Finally, treatment with either cigarette smoke condensate or JUUL e-liquid increased infections with a spike-coated SARS-CoV-2 pseudovirus. Overall, these observations suggest that tobacco product use elevates ACE2 activity and increases the potential for SARS-CoV-2 infection through enhanced spike protein binding.

physiology↗

bioRxiv2021

Genome-wide identification and analysis of prognostic features in human cancers

Clinical decisions in cancer rely on precisely assessing patient risk. To improve our ability to accurately identify the most aggressive malignancies, we constructed genome-wide survival models using gene expression, copy number, methylation, and mutation data from 10,884 patients with known clinical outcomes. We identified more than 100,000 significant prognostic biomarkers and demonstrate that these genomic features can predict patient outcomes in clinically-ambiguous situations. While adverse biomarkers are commonly believed to represent cancer driver genes and promising therapeutic targets, we show that cancer features associated with shorter survival times are not enriched for either oncogenes or for successful drug targets. Instead, the strongest adverse biomarkers represent widely-expressed housekeeping genes with roles in cell cycle progression, and, correspondingly, nearly all therapies directed against these features have failed in clinical trials. In total, our analysis establishes a rich resource for prognostic biomarker analysis and clarifies the use of patient survival data in preclinical cancer research and therapeutic development.

cancer biology↗

bioRxiv2020

Non-parametric Bayesian density estimation for biological sequence space with applications to pre-mRNA splicing and the karyotypic diversity of human cancer

Density estimation in sequence space is a fundamental problem in machine learning that is of great importance in computational biology. Due to the discrete nature and large dimensionality of sequence space, how best to estimate such probability distributions from a sample of observed sequences remains unclear. One common strategy for addressing this problem is to estimate the probability distribution using maximum entropy, i.e. calculating point estimates for some set of correlations based on the observed sequences and predicting the probability distribution that is as uniform as possible while still matching these point estimates. Building on recent advances in Bayesian field-theoretic density estimation, we present a generalization of this maximum entropy approach that provides greater expressivity in regions of sequence space where data is plentiful while still maintaining a conservative maximum entropy char-acter in regions of sequence space where data is sparse or absent. In particular, we define a family of priors for probability distributions over sequence space with a single hyper-parameter that controls the expected magnitude of higher-order correlations. This family of priors then results in a corresponding one-dimensional family of maximum a posteriori estimates that interpolate smoothly between the maximum entropy estimate and the observed sample frequencies. To demonstrate the power of this method, we use it to explore the high-dimensional geometry of the distribution of 5' splice sites found in the human genome and to understand the accumulation of chromosomal abnormalities during cancer progression.

bioinformatics↗

bioRxiv2020

Chromosomal instability accelerates the evolution of resistance to anti-cancer therapies

Aneuploidy is a ubiquitous feature of human tumors, but the acquisition of aneuploidy is typically detrimental to cellular fitness. To investigate how aneuploidy could contribute to tumor growth, we triggered periods of chromosomal instability (CIN) in human cells and then exposed them to a variety of different culture environments. While chromosomal instability was universally detrimental under normal growth conditions, we discovered that transient CIN reproducibly accelerated the ability of cells to adapt and thrive in the presence of anti-cancer therapeutic agents. Single-cell sequencing revealed that these drug-resistant populations recurrently developed specific whole-chromosome gains and losses. We independently derived one aneuploidy that was frequently recovered in cells exposed to paclitaxel, and we found that this chromosome loss event was sufficient to decrease paclitaxel sensitivity. Finally, we demonstrated that intrinsic levels of CIN correlate with poor responses to a variety of systemic therapies in a collection of patient-derived xenografts. In total, our results show that while chromosomal instability generally antagonizes cell fitness, it also provides phenotypic plasticity to cancer cells that can allow them to adapt to diverse stressful environments. Moreover, our findings suggest that aneuploidy may function as an under-explored cause of therapy failure in human tumors.

cancer biology↗

bioRxiv2020

Camostat mesylate inhibits SARS-CoV-2 activation by TMPRSS2-related proteases and its metabolite GBPA exerts antiviral activity

Antiviral therapy is urgently needed to combat the coronavirus disease 2019 (COVID-19) pandemic, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The protease inhibitor camostat mesylate inhibits SARS-CoV-2 infection of lung cells by blocking the virus-activating host cell protease TMPRSS2. Camostat mesylate has been approved for treatment of pancreatitis in Japan and is currently being repurposed for COVID-19 treatment. However, potential mechanisms of viral resistance as well as camostat mesylate metabolization and antiviral activity of metabolites are unclear. Here, we show that SARS-CoV-2 can employ TMPRSS2-related host cell proteases for activation and that several of them are expressed in viral target cells. However, entry mediated by these proteases was blocked by camostat mesylate. The camostat metabolite GBPA inhibited the activity of recombinant TMPRSS2 with reduced efficiency as compared to camostat mesylate and was rapidly generated in the presence of serum. Importantly, the infection experiments in which camostat mesylate was identified as a SARS-CoV-2 inhibitor involved preincubation of target cells with camostat mesylate in the presence of serum for 2 h and thus allowed conversion of camostat mesylate into GBPA. Indeed, when the antiviral activities of GBPA and camostat mesylate were compared in this setting, no major differences were identified. Our results indicate that use of TMPRSS2-related proteases for entry into target cells will not render SARS-CoV-2 camostat mesylate resistant. Moreover, the present and previous findings suggest that the peak concentrations of GBPA established after the clinically approved camostat mesylate dose (600 mg/day) will result in antiviral activity.

molecular biology↗

bioRxiv2020

Cigarette smoke triggers the expansion of a subpopulation of respiratory epithelial cells that express the SARS-CoV-2 receptor ACE2

The factors mediating fatal SARS-CoV-2 infections are poorly understood. Here, we show that cigarette smoke causes a dose-dependent upregulation of Angiotensin Converting Enzyme 2 (ACE2), the SARS-CoV-2 receptor, in rodent and human lungs. Using single-cell sequencing data, we demonstrate that ACE2 is expressed in a subset of secretory cells in the respiratory tract. Chronic smoke exposure triggers the expansion of this cell population and a concomitant increase in ACE2 expression. In contrast, quitting smoking decreases the abundance of these secretory cells and reduces ACE2 levels. Finally, we demonstrate that ACE2 expression is responsive to inflammatory signaling and can be upregulated by viral infections or interferon treatment. Taken together, these results may partially explain why smokers are particularly susceptible to severe SARS-CoV-2 infections. Furthermore, our work identifies ACE2 as an interferon-stimulated gene in lung cells, suggesting that SARS-CoV-2 infections could create positive-feedback loops that increase ACE2 levels and facilitate viral dissemination.

cell biology↗

bioRxiv2019

Single chromosome gains can function as metastasis suppressors and metastasis promoters

Most human tumors display chromosome-scale copy number alterations, and high levels of aneuploidy are frequently associated with advanced disease and poor patient prognosis. To examine the relationship between aneuploidy and cancer progression, we generated and analyzed a series of congenic human cell lines that harbor single extra chromosomes. We find that different aneuploidies can have distinct effects on invasive behavior: across 13 different cell lines, 12 trisomies suppressed invasiveness or were largely neutral, while a single trisomy increased metastatic behavior by triggering a partial epithelial-mesenchymal transition. In contrast, chromosomal instability, which can lead to the development of aneuploidy, uniformly suppressed cellular invasion. By analyzing genomic copy number and survival data from 10,133 cancer patients, we demonstrate that specific aneuploidies are associated with distinct clinical outcomes, and the acquisition of certain aneuploidies is in fact linked with a favorable prognosis. Thus, aneuploidy is not a uniform driver of malignancy, and different chromosome copy number changes can uniquely influence tumor progression. At the same time, the gain of a single chromosome is capable of inducing a profound cell state transition, underscoring how genomic plasticity can engender phenotypic plasticity and lead to the acquisition of enhanced metastatic properties.

cancer biology↗

bioRxiv2017

Combining CRISPR/Cas9 mutagenesis and a small-molecule inhibitor to probe the function of MELK in cancer

The Maternal Embryonic Leucine Zipper Kinase (MELK) has been identified as a promising therapeutic target in multiple cancer types. MELK over-expression is associated with aggressive disease, and MELK has been implicated in numerous cancer-related processes, including chemotherapy resistance, stem cell renewal, and tumor growth. On the basis of these findings, a MELK inhibitor is currently being tested in several clinical trials. Here, we report that cancer cell lines harboring CRISPR/Cas9-induced null mutations in MELK exhibit wild-type growth in vitro, under environmental stress, in the presence of multiple chemotherapy agents, and in vivo. By combining our MELK-knockout clones with a recently-described, highly-specific MELK inhibitor, we further demonstrate that the acute inhibition of MELK results in no specific anti-proliferative phenotype. Analysis of gene expression data from cohorts of cancer patients identifies MELK expression as a correlate of tumor mitotic activity, explaining its association with poor clinical prognosis. In total, our results demonstrate the power of CRISPR/Cas9-based genetic approaches to investigate cancer drug targets, and call into question the rationale for treating patients with anti-MELK monotherapies.

cancer biology↗

bioRxiv2017

An integrated analysis of the epigenetic, genetic, and transcriptional patterns associated with outcome across cancer types

Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed genomic profiles from 33,036 solid tumors with known patient outcomes. Contrary to expectations, we find that mutations in cancer driver genes are almost never associated with patient survival time. In contrast, copy number changes in these same genes are broadly prognostic. Analysis of methylation, microRNA, mRNA, and protein expression patterns in primary tumors define several additional prognostic patterns, including signatures of tumor mitotic activity and tissue de-differentiation. Co-expression analysis with a cell cycle meta-gene distinguished proliferation-dependent and -independent prognostic features, allowing us to construct multivariate survival models with improved stratification power. In total, our analysis provides a comprehensive resource for biomarker and therapeutic target identification, and suggests that copy number and methylation profiling should complement tumor sequencing efforts to improve patient risk assessment.

cancer biology↗