Outcomes of a Formal Hematopoietic Cell Transplantation Survivorship Program on Screening for Late Effects.

Allogeneic hematopoietic cell transplantation (HCT) survivors may benefit from routine screening for post-transplant complications. However, the impact of formal survivorship efforts to promote screening adherence is uncertain. The effect of a formal HCT survivorship program to promote screening adherence was evaluated. We conducted a retrospective analysis of an academic formal HCT survivorship program with primary and specialty consult components. We included patients who underwent allogeneic HCT and were alive and relapse-free 1-year post-HCT. We excluded patients who died <2-year post-HCT or transferred care. We measured screening adherence to cardiovascular, pulmonary, ocular, secondary cancer, and endocrine evaluations. The primary outcome was proportion of patients completing ≥1 evaluation per screening domain prior to 2-year post-HCT. We examined screening adherence during 3 time periods: presurvivorship (2012 to 2014) and 2 postsurvivorship (2016 to 2018 and 2019 to 2021) using multivariate logistic and Cox proportional hazards regression. Four hundred ten patients (2012 to 2014: n = 136, 2016 to 2018: n = 153, 2019 to 2021: n = 121) were included. Compared to the presurvivorship period (16.9%), patients in 2016 to 2018 (47.7%, odds ratio [OR] = 4.9, P < .0001) and 2019 to 2021 (34.7%, OR = 2.7, P = .001) were more likely to complete ≥1 evaluation per screening domain. Except for pulmonary function tests in 2019 to 2021, median time to completion of survivorship evaluations was shorter in the survivorship periods compared to presurvivorship. Patients who completed a formal HCT survivorship consult in 2016 to 2018 and 2019 to 2021 were more likely to complete ≥1 evaluation per screening domain (OR = 5.1, P = .0004). Survivorship consult had similar effect on the primary screening outcome in 2016 to 2018 and 2019 to 2021 (consult × time interaction OR: 2.5, P = .2). However, patients who received a consult in 2019 to 2021 were more likely to complete all screenings (consult × time interaction: OR = 5.7, P = .03). Our HCT survivorship program with primary and specialty components improved screening adherence. Additional studies are needed to evaluate efficacy, dissemination, and implementation of formal HCT survivorship programs.

Selective Inference for Hierarchical Clustering.

Classical tests for a difference in means control the type I error rate when the groups are defined a priori. However, when the groups are instead defined via clustering, then applying a classical test yields an extremely inflated type I error rate. Notably, this problem persists even if two separate and independent data sets are used to define the groups and to test for a difference in their means. To address this problem, in this paper, we propose a selective inference approach to test for a difference in means between two clusters. Our procedure controls the selective type I error rate by accounting for the fact that the choice of null hypothesis was made based on the data. We describe how to efficiently compute exact p-values for clusters obtained using agglomerative hierarchical clustering with many commonly-used linkages. We apply our method to simulated data and to single-cell RNA-sequencing data.

Searching for the "Holy Grail" of breast cancer recurrence risk: a narrative review of the hunt for a better biomarker and the promise of circulating tumor DNA (ctDNA).

BACKGROUND: This paper is a narrative review of a major clinical challenge at the heart of breast cancer care: determining which patients are at risk of recurrence, which require systemic therapy, and which remain at risk in the survivorship phase of care despite initial therapy. METHODS: We review the literature on prognostic and predictive biomarkers in breast cancer with a focus on detection of minimal residual disease. RESULTS: While we have many tools to estimate and refine risk that are used to individualize local and systemic therapy, we know that we continue to over treat many patients and undertreat others. Many patients also experience what is, at least in hindsight, needless fear of recurrence. In this review, we frame this dilemma for the practicing breast oncologist and discuss the search for what we term the "holy grail" of breast cancer evaluation: the ideal biomarker of residual distant disease. We review the history of attempts to address this problem and the up-to-date science on biomarkers, circulating tumor cells and circulating tumor DNA (ctDNA). CONCLUSION: This review suggests that the emerging promise of ctDNA may help resolve a crticical dilemma at the heart of breast cancer care, and improve prognostication, treatment selection, and outcomes for patients with breast cancer.

Kinetics of Trisulfide-to-Disulfide Conversion of Therapeutic IgG1 Monoclonal Antibodies Under Physiological Conditions: A Case Study of Casirivimab And Imdevimab.

The percentage of trisulfide variants is a product quality metric that is monitored during the manufacture of monoclonal antibody (mAb)-based therapeutics. Results from earlier preclinical studies revealed that trisulfide linkages in mAbs are rapidly converted to disulfides in circulation. In this study, casirivimab and imdevimab, which are both IgG1 subclass mAbs that target the non-overlapping epitopes in SARS-CoV2 Spike protein, are used as models to study the kinetics of trisulfide-to-disulfide conversion in vivo in human circulation. To determine the percentage of trisulfide variants in systemic circulation immediately after intravenous injection, both mAbs were immunoprecipitated from serum samples collected from COVID-19 patients that received this cocktail antibody treatment as part of a first-in-human study. The immunoprecipitated mAbs were then digested under non-reducing conditions and evaluated by liquid-chromatography-mass spectrometry (LC-MS). Significant reductions in the percentages of trisulfide variants were observed in serum samples as early as 1 hr after completion of the intravenous infusion. A flow-through dialysis model designed to mimic the redox potential of blood revealed a plausible chemical mechanism for the rapid trisulfide-to-disulfide conversion of IgG1 subclass mAbs under physiological conditions.

Prevalence of targetable genomic alterations in young women with advanced breast cancer: a cross-sectional study.

PURPOSE: Approximately 5% of breast cancers each year are diagnosed in young women < 40 years who tend to have worse clinical outcomes. We compared genomic alterations using comprehensive genomic profiling (CGP) of tumor tissue among very young women (< 30 years) and young women (30-39 years) compared to women ≥ 40 years at diagnosis. METHODS: 2049 advanced breast cancer cases were submitted to Foundation Medicine within a 22-month window for CGP. Hybrid-capture based CGP was performed to evaluate all classes of genomic alterations. Tumor mutational burden was determined on at least 0.8 Mbp of sequenced DNA and microsatellite instability was determined on at least 95 loci. Immunocyte PD-L1 expression was determined by immunohistochemistry. RESULTS: Of the total cases, 28 (1.37%) were < 30 years, 159 (7.76%) were 30-39 years, and 1862 (90.87%) were ≥ 40 at time of diagnosis. Breast tumors were less likely to be estrogen receptor positive in younger women (54% of < 30 years, p > 0.05; 60% of 30-39 years, p < 0.001; 69.4% of ≥ 40 years) and more likely to be triple negative (43%, p = 0.05; 33%, p = 0.05; 26.1% respectively). Young women had higher rates of BRCA1 mutations (17.9% <30 years, p < 0.001; 10.1% 30-39 years, p < 0.001; 2.6% ≥40 years), but lower rates of CDH1 (7.1% <30 years, p > 0.05; 5.0% 30-39 years, p < 0.001; 15.4% ≥40 years) and PIK3CA mutations (17.9% <30 years, p = 0.02; 17.6% 30-39 years, p < 0.001; 40.0% ≥40 years). CONCLUSION: Our findings contribute to the growing literature demonstrating unique genetic profiles among young women diagnosed with breast cancer, compared to older women.

Testing for a difference in means of a single feature after clustering.

For many applications, it is critical to interpret and validate groups of observations obtained via clustering. A common validation approach involves testing differences in feature means between observations in two estimated clusters. In this setting, classical hypothesis tests lead to an inflated Type I error rate. To overcome this problem, we propose a new test for the difference in means in a single feature between a pair of clusters obtained using hierarchical or k-means clustering. The test based on the proposed p-value controls the selective Type I error rate in finite samples and can be efficiently computed. We further illustrate the validity and power of our proposal in simulation and demonstrate its use on single-cell RNA-sequencing data.

Intravascular Lymphoma as a Cause of Recurrent Strokes - Case Report and Review of the Literature.

Background: Intravascular lymphoma is an uncommon cause of ischemic strokes. Because of its rarity and atypical pattern, most diagnoses are made post-mortem. Case study: We present a case of a 68-year-old male with multiple cardiovascular risk factors and recent SARS-CoV-2 infection who presented with recurrent strokes. Because of his stroke risk factors, he was initially managed with a sequentially escalating antithrombotic regimen. A malignant process was low on the differential at this point given his lack of systemic symptoms. When he continued to have new strokes despite these measures, including a spinal cord infarct, a broad workup was sent including for hypercoagulable states, vasculitis, and intravascular lymphoma. Eventually, a skin biopsy of a cherry angioma returned positive for lymphoma cells. He was treated with methotrexate followed by chemotherapy and rituximab. Unfortunately, he did not improve and was made comfort measures only by his family. Conclusion: This case illustrates the importance of considering intravascular lymphoma as a potential etiology of recurrent strokes, as early diagnosis and treatment are important for preventing irreversible neurological damage.

Therapy of autoimmune inflammation in sporadic amyotrophic lateral sclerosis: Dimethyl fumarate and H-151 downregulate inflammatory cytokines in the cGAS-STING pathway.

In sporadic amyotrophic lateral sclerosis (sALS), IL-17A- and granzyme-positive cytotoxic T lymphocytes (CTL), IL-17A-positive mast cells, and inflammatory macrophages invade the brain and spinal cord. In some patients, the disease starts following a trauma or a severe infection. We examined cytokines and cytokine regulators over the disease course and found that, since the early stages, peripheral blood mononuclear cells (PBMC) exhibit increased expression of inflammatory cytokines IL-12A, IFN-γ, and TNF-α, as well as granzymes and the transcription factors STAT3 and STAT4. In later stages, PBMCs upregulated the autoimmunity-associated cytokines IL-23A and IL-17B, and the chemokines CXCL9 and CXCL10, which attract CTL and monocytes into the central nervous system. The inflammation is fueled by the downregulation of IL-10, TGFß, and the inhibitory T-cell co-receptors CTLA4, LAG3, and PD-1, and, in vitro, by stimulation with the ligand PD-L1. We investigated in two sALS patients the regulation of the macrophage transcriptome by dimethyl fumarate (DMF), a drug approved against multiple sclerosis and psoriasis, and the cyclic GMP-AMP synthase/stimulator of interferon genes (cGAS/STING) pathway inhibitor H-151. Both DMF and H-151 downregulated the expression of granzymes and the pro-inflammatory cytokines IL-1ß, IL-6, IL-15, IL-23A, and IFN-γ, and induced a pro-resolution macrophage phenotype. The eicosanoid epoxyeicosatrienoic acids (EET) from arachidonic acid was anti-inflammatory in synergy with DMF. H-151 and DMF are thus candidate drugs targeting the inflammation and autoimmunity in sALS via modulation of the NFκB and cGAS/STING pathways.

Condition-dependent fitness effects of large synthetic chromosome amplifications.

Whole-chromosome aneuploidy and large segmental amplifications can have devastating effects in multicellular organisms, from developmental disorders and miscarriage to cancer. Aneuploidy in single-celled organisms such as yeast also results in proliferative defects and reduced viability. Yet, paradoxically, CNVs are routinely observed in laboratory evolution experiments with microbes grown in stressful conditions. The defects associated with aneuploidy are often attributed to the imbalance of many differentially expressed genes on the affected chromosomes, with many genes each contributing incremental effects. An alternate hypothesis is that a small number of individual genes are large effect 'drivers' of these fitness changes when present in an altered copy number. To test these two views, we have employed a collection of strains bearing large chromosomal amplifications that we previously assayed in nutrient-limited chemostat competitions. In this study, we focus on conditions known to be poorly tolerated by aneuploid yeast-high temperature, treatment with the Hsp90 inhibitor radicicol, and growth in extended stationary phase. To identify potential genes with a large impact on fitness, we fit a piecewise constant model to fitness data across chromosome arms, filtering breakpoints in this model by magnitude to focus on regions with a large impact on fitness in each condition. While fitness generally decreased as the length of the amplification increased, we were able to identify 91 candidate regions that disproportionately impacted fitness when amplified. Consistent with our previous work with this strain collection, nearly all candidate regions were condition specific, with only five regions impacting fitness in multiple conditions.

Inference after latent variable estimation for single-cell RNA sequencing data.

In the analysis of single-cell RNA sequencing data, researchers often characterize the variation between cells by estimating a latent variable, such as cell type or pseudotime, representing some aspect of the cell's state. They then test each gene for association with the estimated latent variable. If the same data are used for both of these steps, then standard methods for computing p-values in the second step will fail to achieve statistical guarantees such as Type 1 error control. Furthermore, approaches such as sample splitting that can be applied to solve similar problems in other settings are not applicable in this context. In this article, we introduce count splitting, a flexible framework that allows us to carry out valid inference in this setting, for virtually any latent variable estimation technique and inference approach, under a Poisson assumption. We demonstrate the Type 1 error control and power of count splitting in a simulation study and apply count splitting to a data set of pluripotent stem cells differentiating to cardiomyocytes.

Patient-centered dosing: oncologists' perspectives about treatment-related side effects and individualized dosing for patients with metastatic breast cancer (MBC).

PURPOSE: Although metastatic breast cancer (MBC) is treatable, it is not curable and most patients remain on treatment indefinitely. While oncologists commonly prescribe the recommended starting dose (RSD) from the FDA-approved label, patient tolerance may differ from that seen in clinical trials. We report on a survey of medical oncologists' perspectives about treatment-related toxicity and willingness to discuss flexible dosing with patients. METHODS: We disseminated a confidential survey via social media/email in Spring 2021. Eligible respondents needed to be US-based medical oncologists with experience treating patients with MBC. RESULTS: Of 131 responses, 119 were eligible. Physicians estimated that 47% of their patients reported distressing treatment-related side effects; of these, 15% visited the Emergency Room/hospital and 37% missed treatment. 74% (n = 87) of doctors reported improvement of patient symptoms after dose reduction. 87% (n = 104) indicated that they had ever, if appropriate, initiated treatment at lower doses. Most (85%, n = 101) respondents did not believe that the RSD is always more effective than a lower dose and 97% (n = 115) were willing to discuss individualized dosing with patients. CONCLUSION: Treatment-related side effects are prevalent among patients with MBC, resulting in missed treatments and acute care visits. To help patients tolerate treatment, oncologists may decrease initial and/or subsequent doses. The majority of oncologists reject the premise that a higher dose is always superior and are willing to discuss individualized dosing with patients. Given potential improvements regarding quality of life and clinical care, dose modifications should be part of routine shared decision-making between patients and oncologists.

Improved zebra finch brain transcriptome identifies novel proteins with sex differences.

The zebra finch (Taeniopygia guttata), a representative oscine songbird species, has been widely studied to investigate behavioral neuroscience, most notably the neurobiological basis of vocal learning, a rare trait shared in only a few animal groups including humans. In 2019, an updated zebra finch genome annotation (bTaeGut1_v1.p) was released from the Ensembl database and is substantially more comprehensive than the first version published in 2010. In this study, we utilized the publicly available RNA-seq data generated from Illumina-based short-reads and PacBio single-molecule real-time (SMRT) long-reads to assess the bird transcriptome. To analyze the high-throughput RNA-seq data, we adopted a hybrid bioinformatic approach combining short and long-read pipelines. From our analysis, we added 220 novel genes and 8,134 transcript variants to the Ensembl annotation, and predicted a new proteome based on the refined annotation. We further validated 18 different novel proteins by using mass-spectrometry data generated from zebra finch caudal telencephalon tissue. Our results provide additional resources for future studies of zebra finches utilizing this improved bird genome annotation and proteome.

Testing for association in multiview network data.

In this paper, we consider data consisting of multiple networks, each composed of a different edge set on a common set of nodes. Many models have been proposed for the analysis of such multiview network data under the assumption that the data views are closely related. In this paper, we provide tools for evaluating this assumption. In particular, we ask: given two networks that each follow a stochastic block model, is there an association between the latent community memberships of the nodes in the two networks? To answer this question, we extend the stochastic block model for a single network view to the two-view setting, and develop a new hypothesis test for the null hypothesis that the latent community memberships in the two data views are independent. We apply our test to protein-protein interaction data from the HINT database. We find evidence of a weak association between the latent community memberships of proteins defined with respect to binary interaction data and the latent community memberships of proteins defined with respect to cocomplex association data. We also extend this proposal to the setting of a network with node covariates. The proposed methods extend readily to three or more network/multivariate data views.

Tree-Values: Selective Inference for Regression Trees.

We consider conducting inference on the output of the Classification and Regression Tree (CART) (Breiman et al., 1984) algorithm. A naive approach to inference that does not account for the fact that the tree was estimated from the data will not achieve standard guarantees, such as Type 1 error rate control and nominal coverage. Thus, we propose a selective inference framework for conducting inference on a fitted CART tree. In a nutshell, we condition on the fact that the tree was estimated from the data. We propose a test for the difference in the mean response between a pair of terminal nodes that controls the selective Type 1 error rate, and a confidence interval for the mean response within a single terminal node that attains the nominal selective coverage. Efficient algorithms for computing the necessary conditioning sets are provided. We apply these methods in simulation and to a dataset involving the association between portion control interventions and caloric intake.

End-of-Life Care Decision-Making in Stroke.

Stroke is one of the leading causes of death and long-term disability in the United States. Though advances in interventions have improved patient survival after stroke, prognostication of long-term functional outcomes remains challenging, thereby complicating discussions of treatment goals. Stroke patients who require intensive care unit care often do not have the capacity themselves to participate in decision making processes, a fact that further complicates potential end-of-life care discussions after the immediate post-stroke period. Establishing clear, consistent communication with surrogates through shared decision-making represents best practice, as these surrogates face decisions regarding artificial nutrition, tracheostomy, code status changes, and withdrawal or withholding of life-sustaining therapies. Throughout decision-making, clinicians must be aware of a myriad of factors affecting both provider recommendations and surrogate concerns, such as cognitive biases. While decision aids have the potential to better frame these conversations within intensive care units, aids specific to goals-of-care decisions for stroke patients are currently lacking. This mini review highlights the difficulties in decision-making for critically ill ischemic stroke and intracerebral hemorrhage patients, beginning with limitations in current validated clinical scales and clinician subjectivity in prognostication. We outline processes for identifying patient preferences when possible and make recommendations for collaborating closely with surrogate decision-makers on end-of-life care decisions.

PRAgmatic Clinical Trial Design of Integrative MediCinE (PRACTICE): A Focus Group Series and Systematic Review on Trials of Diabetes and Kidney Disease.

Background: Pragmatic trials inform clinical decision with better generalizability and can bridge different streams of medicine. This study collated the expectations regarding pragmatic trial design of integrative medicine (IM) for diabetes and kidney diseases among patients and physicians. Dissonance between users' perspective and existing pragmatic trial design was identified. The association between risk of bias and pragmatism of study design was assessed. Method: A 10-group semi-structured focus group interview series [21 patients, 14 conventional medicine (ConM) and 15 Chinese medicine (CM) physicians] were purposively sampled from private and public clinics in Hong Kong. Perspectives were qualitatively analyzed by constant comparative method. A systematic search of four databases was performed to identify existing IM pragmatic clinical trials in diabetes or kidney disease. Primary outcomes were the pragmatism, risk of bias, and rationale of the study design. Risk of bias and pragmatism were assessed based on Cochrane risk-of-bias tool and PRECIS-2, respectively. The correlation between risk of bias and pragmatism was assessed by regression models with sensitivity analyses. Results: The subtheme on the motivation to seek IM service was analyzed, covering the perceived limitation of ConM effect, perceived benefits of IM service, and assessment of IM effectiveness. Patients expected IM service to retard disease progression, stabilize concomitant drug dosage, and reduce potential side effects associated with ConM. In the systematic review, 25 studies from six countries were included covering CM, Korean medicine, Ayurvedic medicine, and western herbal medicine. Existing study designs did not include a detailed assessment of concomitant drug change and adverse events. Majority of studies either recruited a non-representative proportion of patients as traditional, complementary, and integrative medicine (TCIM) diagnosis was used as inclusion criteria, or not reflecting the real-world practice of TCIM by completely dropping TCIM diagnosis in the trial design. Consultation follow-up frequency is the least pragmatic domain. Increase in pragmatism did not associate with a higher risk of bias. Conclusion: Existing IM pragmatic trial design does not match the patients' expectation in the analysis of incident concomitant drug change and adverse events. A two-layer design incorporating TCIM diagnosis as a stratification factor maximizes the generalizability of evidence and real-world translation of both ConM and TCIM.

Mapping Proximity Associations of Core Spindle Assembly Checkpoint Proteins.

The spindle assembly checkpoint (SAC) is critical for sensing defective microtubule-kinetochore attachments and tension across the kinetochore and functions to arrest cells in prometaphase to allow time to repair any errors before proceeding into anaphase. Dysregulation of the SAC leads to chromosome segregation errors that have been linked to human diseases like cancer. Although much has been learned about the composition of the SAC and the factors that regulate its activity, the proximity associations of core SAC components have not been explored in a systematic manner. Here, we have taken a BioID2-proximity-labeling proteomic approach to define the proximity protein environment for each of the five core SAC proteins BUB1, BUB3, BUBR1, MAD1L1, and MAD2L1 in mitotic-enriched populations of cells where the SAC is active. These five protein association maps were integrated to generate a SAC proximity protein network that contains multiple layers of information related to core SAC protein complexes, protein-protein interactions, and proximity associations. Our analysis validated many known SAC complexes and protein-protein interactions. Additionally, it uncovered new protein associations, including the ELYS-MAD1L1 interaction that we have validated, which lend insight into the functioning of core SAC proteins and highlight future areas of investigation to better understand the SAC.

A disordered rock salt anode for fast-charging lithium-ion batteries.

Rechargeable lithium-ion batteries with high energy density that can be safely charged and discharged at high rates are desirable for electrified transportation and other applications1-3. However, the sub-optimal intercalation potentials of current anodes result in a trade-off between energy density, power and safety. Here we report that disordered rock salt4,5 Li3+xV2O5 can be used as a fast-charging anode that can reversibly cycle two lithium ions at an average voltage of about 0.6 volts versus a Li/Li+ reference electrode. The increased potential compared to graphite6,7 reduces the likelihood of lithium metal plating if proper charging controls are used, alleviating a major safety concern (short-circuiting related to Li dendrite growth). In addition, a lithium-ion battery with a disordered rock salt Li3V2O5 anode yields a cell voltage much higher than does a battery using a commercial fast-charging lithium titanate anode or other intercalation anode candidates (Li3VO4 and LiV0.5Ti0.5S2)8,9. Further, disordered rock salt Li3V2O5 can perform over 1,000 charge-discharge cycles with negligible capacity decay and exhibits exceptional rate capability, delivering over 40 per cent of its capacity in 20 seconds. We attribute the low voltage and high rate capability of disordered rock salt Li3V2O5 to a redistributive lithium intercalation mechanism with low energy barriers revealed via ab initio calculations. This low-potential, high-rate intercalation reaction can be used to identify other metal oxide anodes for fast-charging, long-life lithium-ion batteries.

Regulation of Iron Homeostasis through Parkin-Mediated Lactoferrin Ubiquitylation.

Somatic mutations that perturb Parkin ubiquitin ligase activity and the misregulation of iron homeostasis have both been linked to Parkinson's disease. Lactotransferrin (LTF) is a member of the family of transferrin iron binding proteins that regulate iron homeostasis, and increased levels of LTF and its receptor have been observed in neurodegenerative disorders like Parkinson's disease. Here, we report that Parkin binds to LTF and ubiquitylates LTF to influence iron homeostasis. Parkin-dependent ubiquitylation of LTF occurred most often on lysines (K) 182 and 649. Substitution of K182 or K649 with alanine (K182A or K649A, respectively) led to a decrease in the level of LTF ubiquitylation, and substitution at both sites led to a major decrease in the level of LTF ubiquitylation. Importantly, Parkin-mediated ubiquitylation of LTF was critical for regulating intracellular iron levels as overexpression of LTF ubiquitylation site point mutants (K649A or K182A/K649A) led to an increase in intracellular iron levels measured by ICP-MS/MS. Consistently, RNAi-mediated depletion of Parkin led to an increase in intracellular iron levels in contrast to overexpression of Parkin that led to a decrease in intracellular iron levels. Together, these results indicate that Parkin binds to and ubiquitylates LTF to regulate intracellular iron levels. These results expand our understanding of the cellular processes that are perturbed when Parkin activity is disrupted and more broadly the mechanisms that contribute to Parkinson's disease.

Diminished viability of human ovarian cancer cells by antigen-specific delivery of carbon monoxide with a family of photoactivatable antibody-photoCORM conjugates.

Carbon monoxide (CO)-releasing antibody conjugates were synthesized utilizing a photoactivatable CO-releasing molecule (photoCORM) and mouse monoclonal antibodies linked by a biotin-streptavidin system. Different monoclonal antibodies raised against different surface-expressed antigens that are implicated in ovarian cancer afforded a family of antibody-photoCORM conjugates (Ab-photoCORMs). In an immunosorbent/cell viability assay, Ab-photoCORMs accumulated onto ovarian cancer cells expressing the target antigens, delivering cytotoxic doses of CO in vitro. The results described here provide the first example of an "immunoCORM", a proof-of-the-concept antibody-drug conjugate that delivers a gaseous molecule as a warhead to ovarian cancer.