Phenotype prediction from single-cell RNA-seq data using attention-based neural networks.

MOTIVATION: A patient's disease phenotype can be driven and determined by specific groups of cells whose marker genes are either unknown or can only be detected at late-stage using conventional bulk assays such as RNA-Seq technology. Recent advances in single-cell RNA sequencing (scRNA-seq) enable gene expression profiling in cell-level resolution, and therefore have the potential to identify those cells driving the disease phenotype even while the number of these cells is small. However, most existing methods rely heavily on accurate cell type detection, and the number of available annotated samples is usually too small for training deep learning predictive models. RESULTS: Here, we propose the method ScRAT for phenotype prediction using scRNA-seq data. To train ScRAT with a limited number of samples of different phenotypes, such as coronavirus disease (COVID) and non-COVID, ScRAT first applies a mixup module to increase the number of training samples. A multi-head attention mechanism is employed to learn the most informative cells for each phenotype without relying on a given cell type annotation. Using three public COVID datasets, we show that ScRAT outperforms other phenotype prediction methods. The performance edge of ScRAT over its competitors increases as the number of training samples decreases, indicating the efficacy of our sample mixup. Critical cell types detected based on high-attention cells also support novel findings in the original papers and the recent literature. This suggests that ScRAT overcomes the challenge of missing marker genes and limited sample number with great potential revealing novel molecular mechanisms and/or therapies. AVAILABILITY AND IMPLEMENTATION: The code of our proposed method ScRAT is published at https://github.com/yuzhenmao/ScRAT.

Preclinical 3D model screening reveals digoxin as an effective therapy for a rare and aggressive type of endometrial cancer.

OBJECTIVE: Dedifferentiated endometrial carcinoma (DDEC) characterized by SWItch/Sucrose Non-Fermentable (SWI/SNF) complex inactivation is a highly aggressive type of endometrial cancer without effective systemic therapy options. Its uncommon nature and aggressive disease trajectory pose significant challenges for therapeutic progress. To address this obstacle, we focused on developing preclinical models tailored to this tumor type and established patient tumor-derived three-dimensional (3D) spheroid models of DDEC. METHODS: High-throughput drug repurposing screens were performed on in vitro 3D spheroid models of DDEC cell lines (SMARCA4-inactivated DDEC-1 and ARID1A/ARID1B co-inactivated DDEC-2). The dose-response relationships of the identified candidate drugs were evaluated in vitro, followed by in vivo evaluation using xenograft models of DDEC-1 and DDEC-2. RESULTS: Drug screen in 3D models identified multiple cardiac glycosides including digoxin and digitoxin as candidate drugs in both DDEC-1 and DDEC-2. Subsequent in vitro dose-response analyses confirmed the inhibitory activity of digoxin and digitoxin with both drugs showing lower IC50 in DDEC cells compared to non-DDEC endometrial cancer cells. In in vivo xenograft models, digoxin significantly suppressed the growth of DDEC tumors at clinically relevant serum concentrations. CONCLUSION: Using biologically precise preclinical models of DDEC derived from patient tumor samples, our study identified digoxin as an effective drug in suppressing DDEC tumor growth. These findings provide compelling preclinical evidence for the use of digoxin as systemic therapy for SWI/SNF-inactivated DDEC, which may also be applicable to other SWI/SNF-inactivated tumor types.

The spectrum of MAPK-ERK pathway genomic alterations in gynecologic malignancies: Opportunities for novel therapeutic approaches.

OBJECTIVE: To investigate the incidence of MAPK/ERK pathway genomic alterations among patients with gynecologic malignancies. METHODS: We accessed the American Association of Cancer Research Genomics Evidence of Neoplasia Information Exchange publicly available dataset (v13.0). Patients with malignant tumors of the ovary, uterus, and cervix were identified. Following stratification by tumor site and histology, we examined the prevalence of MAPK/ERK pathway gene alterations (somatic mutation, and/or structural chromosome alterations). We included the following RAS-MAPK pathway genes known to be implicated in the dysregulation of the pathway; KRAS, NRAS, BRAF, HRAS, MAP2K1, RAF1, PTPN11, NF1, and ARAF. Data from the OncoKB database, as provided by cBioPortal, were utilized to determine pathogenic gene alterations. RESULTS: We identified a total of 10,233 patients with gynecologic malignancies; 48.2% (n = 4937) with ovarian, 45.2% (n = 4621) with uterine and 6.6% (n = 675) with cervical cancer respectively. The overall incidence of MAPK pathway gene alterations was 21%; the most commonly altered gene was KRAS (13%), followed by NF1 (7%), NRAS (1.3%), and BRAF (1.2%). The highest incidence was observed among patients with mucinous ovarian (71%), low-grade serous ovarian (48%), endometrioid ovarian (37%), and endometrioid endometrial carcinoma (34%). CONCLUSIONS: Approximately 1 in 5 patients with a gynecologic tumor harbor a MAPK/ERK pathway genomic alteration. Novel treatment strategies capitalizing on these alterations are warranted.

Establishment and validation of preclinical models of SMARCA4-inactivated and ARID1A/ARID1B co-inactivated dedifferentiated endometrial carcinoma.

OBJECTIVE: Dedifferentiated endometrial cancer (DDEC) is an uncommon and clinically highly aggressive subtype of endometrial cancer characterized by genomic inactivation of SWItch/Sucrose Non-Fermentable (SWI/SNF) complex protein. It responds poorly to conventional systemic treatment and its rapidly progressive clinical course limits the therapeutic windows to trial additional lines of therapies. This underscores a pressing need for biologically accurate preclinical tumor models to accelerate therapeutic development. METHODS: DDEC tumor from surgical samples were implanted into immunocompromised mice for patient-derived xenograft (PDX) and cell line development. The histologic, immunophenotypic, genetic and epigenetic features of the patient tumors and the established PDX models were characterized. The SMARCA4-deficienct DDEC model was evaluated for its sensitivity toward a KDM6A/B inhibitor (GSK-J4) that was previously reported to be effective therapy for other SMARCA4-deficient cancer types. RESULTS: All three DDEC models exhibited rapid growth in vitro and in vivo, with two PDX models showing spontaneous development of metastases in vivo. The PDX tumors maintained the same undifferentiated histology and immunophenotype, and exhibited identical genomic and methylation profiles as seen in the respective parental tumors, including a mismatch repair (MMR)-deficient DDEC with genomic inactivation of SMARCA4, and two MMR-deficient DDECs with genomic inactivation of both ARID1A and ARID1B. Although the SMARCA4-deficient cell line showed low micromolecular sensitivity to GSK-J4, no significant tumor growth inhibition was observed in the corresponding PDX model. CONCLUSIONS: These established patient tumor-derived models accurately depict DDEC and represent valuable preclinical tools to gain therapeutic insights into this aggressive tumor type.

Can Signal Delay be Functional? Including Delay in Evolved Robot Controllers.

Engineers, control theorists, and neuroscientists often view the delay imposed by finite signal propagation velocities as a problem that needs to be compensated for or avoided. In this article, we consider the alternative possibility that in some cases, signal delay can be used functionally, that is, as an essential component of a cognitive system. To investigate this idea, we evolve a minimal robot controller to solve a basic stimulus-distinction task. The controller is constrained so that the solution must utilize a delayed recurrent signal. Different from previous evolutionary robotics studies, our controller is modeled using delay differential equations, which (unlike the ordinary differential equations of conventional continuous-time recurrent neural networks) can accurately capture delays in signal propagation. We analyze the evolved controller and its interaction with its environment using classical dynamical systems techniques. The analysis shows what kinds of invariant sets underlie the various successful and unsuccessful performances of the robot, and what kinds of bifurcations produce these invariant sets. In the second phase of our analysis, we turn our attention to the parameter θ, which describes the amount of signal delay included in the model. We show how the delay destabilizes certain attractors that would exist if there were no delay and creates other stable attractors, resulting in an agent that performs well at the target task.

Nontransformed and Cancer Cells Can Utilize Different Endocytic Pathways To Internalize Dendritic Nanoparticle Variants: Implications on Nanocarrier Design.

Three hyperbranched polyglycerol nanoparticle (HPG NP) variants were synthesized and fluorescently labeled for the study of their cellular interactions. The polymeric nanoparticle that contains a hydrophobic core and a hydrophilic HPG shell, HPG-C10-HPG, is taken up faster by HT-29 cancer cells than nontransformed cells, while similar uptake rates are observed with both cell types for the nanoparticle HPG-C10-PEG that contains a hydrophobic core and a polyethylene glycol shell. The nanoparticle HPG-104, containing neither the hydrophobic core nor the polyethylene glycol shell, is taken up faster by nontransformed cells than HT-29 cells. Importantly, cancer and normal cells can utilize different endocytic mechanisms for the internalization of these HPG NPs. Both HPG-C10-HPG and HPG-C10-PEG are taken up by HT-29 cells through clathrin-mediated endocytosis and macropinocytosis. Nontransformed cells, however, take up HPG-C10-HPG and HPG-104 through macropinocytosis, while these cells utilize both clathrin-mediated endocytosis and macropinocytosis to internalize HPG-C10-PEG.

The "Flipped Classroom" Model for Teaching in the Intensive Care Unit.

INTRODUCTION: The intensive care unit (ICU) is a dynamic and complex learning environment. The wide range in trainee's experience, specialty training, fluctuations in patient acuity and volume, limitations in trainee duty hours, and additional responsibilities of the faculty contribute to the challenge in providing a consistent experience with traditional educational strategies. The "flipped classroom" is an educational model with the potential to improve the learning environment. In this paradigm, students gain exposure to new material outside class and then use class time to assimilate the knowledge through problem-solving exercises or discussion. The rationale and pedagogical foundations for the flipped classroom are reviewed, practical considerations are discussed, and an example of successful implementation is provided. METHODS: An education curriculum was devised and evaluated prospectively for teaching point-of-care echocardiography to residents rotating in the surgical ICU. RESULTS: Preintervention and postintervention scores of knowledge, confidence, perceived usefulness, and likelihood of use the skills improved for each module. The quality of the experience was rated highly for each of the sessions. CONCLUSION: The flipped classroom education curriculum has many advantages. This pilot study was well received, and learners showed improvement in all areas evaluated, across several demographic subgroups and self-identified learning styles.

Delayed sequence intubation: a prospective observational study.

STUDY OBJECTIVE: We investigate a new technique for the emergency airway management of patients with altered mental status preventing adequate preoxygenation. METHODS: This was a prospective, observational, multicenter study of patients whose medical condition led them to impede optimal preintubation preparation because of delirium. A convenience sample of emergency department and ICU patients was enrolled. Patients received a dissociative dose of ketamine, allowing preoxygenation with high-flow nonrebreather mask or noninvasive positive pressure ventilation (NIPPV). After preoxygenation, patients were paralyzed and intubated. The primary outcome of this study was the difference in oxygen saturations after maximal attempts at preoxygenation before delayed sequence intubation compared with saturations just before intubation. Predetermined secondary outcomes and complications were also assessed. RESULTS: A total of 62 patients were enrolled: 19 patients required delayed sequence intubation to allow nonrebreather mask, 39 patients required it to allow NIPPV, and 4 patients required it for nasogastric tube placement. Saturations increased from a mean of 89.9% before delayed sequence intubation to 98.8% afterward, with an increase of 8.9% (95% confidence interval 6.4% to 10.9%). Thirty-two patients were in a predetermined group with high potential for critical desaturation (pre-delayed sequence intubation saturations ≤93%). All of these patients increased their saturations post-delayed sequence intubation; 29 (91%) of these patients increased their post-delayed sequence intubation saturations to greater than 93%. No complications were observed in the patients receiving delayed sequence intubation. CONCLUSION: Delayed sequence intubation could offer an alternative to rapid sequence intubation in patients requiring emergency airway management who will not tolerate preoxygenation or peri-intubation procedures. It is essentially procedural sedation, with the procedure being preoxygenation. Delayed sequence intubation seems safe and effective for use in emergency airway management.

Investigation of hydrophobically derivatized hyperbranched polyglycerol with PEGylated shell as a nanocarrier for systemic delivery of chemotherapeutics.

We report the synthesis and characterization of a polymeric nanoparticle (NP) based on hyperbranched polyglycerol (HPG) containing a hydrophobic core and a hydrophilic shell, and assessed its suitability to be developed as a systemic anticancer drug carrier. HPG NP displayed low toxicity to primary cell cultures and were well-tolerated in mice after intravenous administration. When tested in mice tumor xenograft models, HPG NP accumulated significantly in the tumors with low accumulation in the liver and the spleen. In vitro studies demonstrated that HPG NP was capable of hydrophobically binding docetaxel and releasing it in a controlled manner. The HPG NP formulation of docetaxel conferred a preferential protective effect on primary non-cancerous cells while effectively killing cancer cells, indicating great potential for widening its therapeutic index. Taken together, these data indicate that HPG NP is a highly promising nanocarrier platform for systemic delivery of anticancer drugs. FROM THE CLINICAL EDITOR: The use of polyethylene glycol on nano-carriers as "stealth" to deliver intravenous drugs is well known. Here, the authors developed polymeric nanoparticle (NP) with hyperbranched polyglycerol (HPG) and tested its efficacy in delivering docetaxel. The results showed that this formulation could preferentially killed cancer cells with a high therapeutic index. It seems that this platform could have a great potential in cancer therapy.

Evaluation of off-label rapamycin use on oral health.

Rapamycin (sirolimus) is an FDA approved drug with immune modulating properties that is being prescribed off-label in adults as a preventative therapy to maintain healthspan. We recently published one of the first reports on 333 adults with a history of off-label rapamycin use. Along with presenting evidence that rapamycin can be used safely in adults of normal health status, we discovered that about 26% of rapamycin users also reported oral health changes. Given the recent evidence highlighting the potential benefits of rapamycin and its derivatives in enhancing oral health, we conducted a secondary data analysis to profile the oral health of off-label rapamycin users, the true incidence of mouth sores, and present specific case studies of periodontal bone loss quantification using an FDA-approved artificial intelligence platform. Contrary to expected findings and previous literature, dimensions of rapamycin usage (such as length of use, dosage, and interval) were not found to be related to the incidence of mouth ulcers in rapamycin users. Notably, among rapamycin users, the most deleterious forms of ulcers were found to be infrequent and not statistically linked to rapamycin usage, with most rapamycin users having a common transient form of mouth ulcers. Additionally, we describe the general oral health outcomes of off-label rapamycin users and provide recommendations for individuals engaging in off-label rapamycin to be regularly checked by a dentist or an oral health care provider. This report was limited by being a secondary data analysis taken from survey data that focused on a more holistic health model. Future studies will use a focused survey that collects data on more dimensions of oral health outcomes while including questions on oral health for non-rapamycin-using participants.

Harnessing natural killer cells to develop next-generation cellular immunotherapy.

Cellular immunotherapy harnesses the body's own immune system to fight cancer by using engineered T cells, macrophages, or natural killer (NK) cells. Compared to chimeric antigen receptor T (CAR-T) cells that are commonly used to treat hematological malignancies, CAR-NK cells have shown remarkable therapeutic effectiveness while exhibiting enhanced safety, reduced risk of graft-versus-host disease, fewer side effects, and amplified antitumor efficacy. Preclinical trials have unveiled the high potential of adoptive CAR-NK cell therapy to curtail or even eliminate both hematological malignancies and solid tumors in animal models. We brought forth herein the design principle of CAR-NK cells, highlighted the latest progress in the preclinical testing and clinical trials of CAR-NK cells, briefly delved into discussed major roadblocks in CAR-NK therapy, and discussed potential solutions to surmount these challenges. Given the accelerated progress in both basic and translational studies on immune cell engineering, CAR-NK cell therapy promises to become a serious contender and important addition to the next-generation cell-based immunotherapy.

Framework of Intrinsic Immune Landscape of Dormant Prostate Cancer.

Androgen deprivation therapy (ADT) is the standard therapy for men with advanced prostate cancer (PCa). PCa often responds to ADT and enters a dormancy period, which can be recognized clinically as a minimal residual disease. However, the majority of these patients will eventually experience a relapse in the form of castration-resistant PCa with poor survival. Therefore, ADT-induced dormancy is a unique time window for treatment that can provide a cure. The study of this well-recognized phase of prostate cancer progression is largely hindered by the scarcity of appropriate clinical tissue and clinically relevant preclinical models. Here, we report the utility of unique and clinically relevant patient-derived xenograft models in the study of the intrinsic immune landscape of dormant PCa. Using data from RNA sequencing, we have reconstructed the immune evasion mechanisms that can be utilized by dormant PCa cells. Since dormant PCa cells need to evade the host immune surveillance for survival, our results provide a framework for further study and for devising immunomodulatory mechanisms that can eliminate dormant PCa cells.

Accreditation of Simulation Fellowships and Training Programs: More Checkboxes or Elevating the Field?

SUMMARY STATEMENT: As the field of healthcare simulation matures, formal accreditation for simulation fellowships and training programs has become increasingly available and touted as a solution to standardize the education of those specializing in healthcare simulation. Some simulation experts hold opposing views regarding the potential value of simulation fellowship program accreditation. We report on the proceedings of a spirited debate at the 20th International Meeting on Simulation in Healthcare in January 2020. Pro arguments view accreditation as the logical evolution of a maturing profession: improving training quality through standard setting, providing external validation for individual programs, and enhancing the program's return on investment. Con arguments view accreditation as an incompletely formulated construct; burdensome to the "financially strapped" fellowship director, misaligned with simulation fellows' needs and expectations, and confusing to administrators mistakenly equating accreditation with credentialing. In addition, opponents of accreditation postulate that incorporating curricular standards, practice guidelines, and strategies derived and implemented without rigor, supporting evidence and universal consensus is premature. This narrative review of our debate compares and contrasts contemporary perspectives on simulation fellowship program accreditation, concluding with formal recommendations for learners, administrators, sponsors, and accrediting bodies.

A Scoping Literature Review of Simulation Training Program Curriculum Standards.

SUMMARY STATEMENT: Simulation educator training is well supported in the literature and endorsed by the Society of Simulation in Healthcare as well as the International Nursing Association for Clinical Simulation and Learning. Despite growth of domestic and international training programs, there is a lack of consensus regarding curriculum standards. Our aim was to identify core curricular components of comprehensive simulation training programs. A scoping literature review of all relevant publications from 2000 to 2020 was conducted using a 6-step design. A team of 10 multidisciplinary, international simulation educators independently reviewed all citations with discrepancies resolved by third-person review. Of the initial 320 identified unique publications, a total of 15 articles were included, all published within the last 6 years. Four themes were identified: domains (n = 6), competencies (n = 3), objectives (n = 8), and other characteristics (n = 3). The findings support a greater understanding of the core curricular content across simulation training programs to support standardization.

NOTCH Signaling Limits the Response of Low-Grade Serous Ovarian Cancers to MEK Inhibition.

Low-grade serous ovarian cancer (LGSOC) is a rare subtype of epithelial ovarian cancer with high fatality rates in advanced stages due to its chemoresistant properties. LGSOC is characterized by activation of MAPK signaling, and recent clinical trials indicate that the MEK inhibitor (MEKi) trametinib may be a good treatment option for a subset of patients. Understanding MEKi-resistance mechanisms and subsequent identification of rational drug combinations to suppress resistance may greatly improve LGSOC treatment strategies. Both gain-of-function and loss-of-function CRISPR-Cas9 genome-wide libraries were used to screen LGSOC cell lines to identify genes that modulate the response to MEKi. Overexpression of MAML2 and loss of MAP3K1 were identified, both leading to overexpression of the NOTCH target HES1, which has a causal role in this process as its knockdown reversed MEKi resistance. Interestingly, increased HES1 expression was also observed in selected spontaneous trametinib-resistant clones, next to activating MAP2K1 (MEK1) mutations. Subsequent trametinib synthetic lethality screens identified SHOC2 downregulation as being synthetic lethal with MEKis. Targeting SHOC2 with pan-RAF inhibitors (pan-RAFis) in combination with MEKi was effective in parental LGSOC cell lines, in MEKi-resistant derivatives, in primary ascites cultures from patients with LGSOC, and in LGSOC (cell line-derived and patient-derived) xenograft mouse models. We found that the combination of pan-RAFi with MEKi downregulated HES1 levels in trametinib-resistant cells, providing an explanation for the synergy that was observed. Combining MEKis with pan-RAFis may provide a promising treatment strategy for patients with LGSOC, which warrants further clinical validation.

Modeling Androgen Deprivation Therapy-Induced Prostate Cancer Dormancy and Its Clinical Implications.

Treatment-induced tumor dormancy is a state in cancer progression where residual disease is present but remains asymptomatic. Dormant cancer cells are treatment-resistant and responsible for cancer recurrence and metastasis. Prostate cancer treated with androgen-deprivation therapy (ADT) often enters a dormant state. ADT-induced prostate cancer dormancy remains poorly understood due to the challenge in acquiring clinical dormant prostate cancer cells and the lack of representative models. In this study, we aimed to develop clinically relevant models for studying ADT-induced prostate cancer dormancy. Dormant prostate cancer models were established by castrating mice bearing patient-derived xenografts (PDX) of hormonal naïve or sensitive prostate cancer. Dormancy status and tumor relapse were monitored and evaluated. Paired pre- and postcastration (dormant) PDX tissues were subjected to morphologic and transcriptome profiling analyses. As a result, we established eleven ADT-induced dormant prostate cancer models that closely mimicked the clinical courses of ADT-treated prostate cancer. We identified two ADT-induced dormancy subtypes that differed in morphology, gene expression, and relapse rates. We discovered transcriptomic differences in precastration PDXs that predisposed the dormancy response to ADT. We further developed a dormancy subtype-based, predisposed gene signature that was significantly associated with ADT response in hormonal naïve prostate cancer and clinical outcome in castration-resistant prostate cancer treated with ADT or androgen-receptor pathway inhibitors. IMPLICATIONS: We have established highly clinically relevant PDXs of ADT-induced dormant prostate cancer and identified two dormancy subtypes, leading to the development of a novel predicative gene signature that allows robust risk stratification of patients with prostate cancer to ADT or androgen-receptor pathway inhibitors.

Physician Wellness Measures and Clinical Performance on a Critically Ill Simulated Patient: Does a Lack of Well-Being Impact Patient Care?

BACKGROUND/OBJECTIVE: Burnout is common among resident physicians, which has the potential to translate into diagnostic and management errors. Our study investigates the relationship between sleepiness, depression, anxiety, burnout, and lack of professional fulfillment with clinical performance during a critically ill patient simulation. Methods/Approach: Emergency medicine residents were recruited to participate in a high-fidelity simulation case of a critically ill patient. A survey with validated wellbeing measures (National Institutes of Health Patient-Reported Outcomes Measurement Information System (NIH PROMIS), Linzer burnout measure, and professional fulfillment index) was administered prior to the simulation. Each encounter was video-recorded and analyzed by two blinded raters based on a binary critical-actions checklist. Time-to-intubation, management errors, and misdiagnosis rates were assessed. RESULTS: Twenty residents participated, with most subjects endorsing sleepiness (70%) and less than half reporting depression (40%) and anxiety (45%). Burnout was identified to be in 50% of participants by the Linzer measure and 85% by the professional fulfillment index. No significant difference was found between mean performance scores in sleepy, depressed, and anxious cohorts in comparison to groups without those symptoms. Similarly, burnout and professional fulfillment did not yield any significant difference, nor did comparisons with time to intubation, management errors, and frequency of misdiagnosis. CONCLUSION: Resident burnout, depression, anxiety, sleepiness, and lack of professional fulfillment did not appear to have a measurable impact on clinical performance in managing a critically ill patient. There is no evidence from this study that the lack of resident physician well-being adversely impacts patient care by increasing errors in management or misdiagnoses during this high-fidelity simulation.

Longer duration of anti-retroviral therapy is associated with decreased risk of human papillomaviruses detection in Kenyan women living with HIV.

OBJECTIVE: A longitudinal study was conducted among women living with HIV in Kenya to determine if duration of anti-retroviral (ART) usage altered detection and persistence of oncogenic (high-risk) human papillomaviruses (HR-HPV). METHODS: Women living with HIV without cervical dysplasia were enrolled at a cervical cancer screening clinic. Three cervical swabs, HIV viral loads, and CD4 cell counts were obtained at enrollment and at two annual visits. HPV genotyping was performed on swabs (Roche Linear Array). Linear regression models assessed effects of ART duration on HR-HPV detection and persistence. RESULTS: Seventy-seven women, median age 38 years, completed three study visits and were included in the analysis. The mean time from HIV diagnosis to enrollment was 9.6 years (SD 3.9 years). The mean ART duration was 6.2 years (SD 3.1 years). Most women had undetectable HIV viral loads and CD4 cell counts above 500 cells/L. Each additional year of ART use reduced the likelihood of detection of HR-HPV by 10-15% and persistent detection of A9 HR-HPV by 20%. CONCLUSION: Among Kenyan women living with HIV, longer duration of ART use was associated with significantly reduced risk of all detection and persistent detection of HR-HPV.

Multiomics Characterization of Low-Grade Serous Ovarian Carcinoma Identifies Potential Biomarkers of MEK Inhibitor Sensitivity and Therapeutic Vulnerability.

Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates in patients with metastatic disease. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. Here, we use multiomics integration of whole-exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on 14 LGSOC cell lines to elucidate novel biomarkers and therapeutic vulnerabilities. Comparison of LGSOC cell line data with LGSOC tumor data enabled predictive biomarker identification of MEK inhibitor (MEKi) efficacy, with KRAS mutations found exclusively in MEKi-sensitive cell lines and NRAS mutations found mostly in MEKi-resistant cell lines. Distinct patterns of Catalogue of Somatic Mutations in Cancer mutational signatures were identified in MEKi-sensitive and MEKi-resistant cell lines. Deletions of CDKN2A/B and MTAP genes were more frequent in cell lines than tumor samples and possibly represent key driver events in the absence of KRAS/NRAS/BRAF mutations. These LGSOC cell lines were representative models of the molecular aberrations found in LGSOC tumors. For prediction of in vitro MEKi efficacy, proteomic data provided better discrimination than gene expression data. Condensin, minichromosome maintenance, and replication factor C protein complexes were identified as potential treatment targets in MEKi-resistant cell lines. This study suggests that CDKN2A/B or MTAP deficiency may be exploited using synthetically lethal treatment strategies, highlighting the importance of using proteomic data as a tool for molecular drug prediction. Multiomics approaches are crucial to improving our understanding of the molecular underpinnings of LGSOC and applying this information to develop new therapies. SIGNIFICANCE: These findings highlight the utility of global multiomics to characterize LGSOC cell lines as research models, to determine biomarkers of MEKi resistance, and to identify potential novel therapeutic targets.