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Genome editing tools, particularly the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) systems (e.g., CRISPR/Cas9), and their repurposing into epigenetic editing platforms, offer enormous potential as safe and customizable therapies for cancer. Specifically, various transcriptional abnormalities in human malignancies, such as silencing of tumor suppressors and ectopic re-expression of oncogenes, have been successfully targeted with virtually no off-target effects using CRISPR activation and repression systems. In these systems, the nuclease-deactivated Cas9 protein (dCas9) is fused to one or more domains inducing selective activation or repression of the targeted genes. Despite these advances, the efficient in vivo delivery of these molecules into the target cancer cells represents a critical barrier to accomplishing translation into a clinical therapy setting for cancer. Major obstacles include the large size of dCas9 fusion proteins, the necessity of multimodal delivery of protein and gRNAs, and the potential of these formulations to elicit detrimental immune responses.In this context, viral methods for delivering CRISPR face several limitations, such as the packaging capacity of the viral genome, the potential for integration of the nucleic acids into the host cells genome, and immunogenicity of viral proteins, posing serious safety concerns. The rapid development of mRNA vaccines in response to the COVID-19 pandemic has rekindled interest in mRNA-based approaches for CRISPR/dCas9 delivery. Simultaneously, due to their high loading capacity, scalability, customizable surface modification for cell targeting, and low immunogenicity, lipid nanoparticles (LNPs) have been widely explored as nonviral vectors. In this chapter, we first describe the design of optimized dCas9-effector mRNAs and gRNAs for epigenetic editing. We outline formulations of LNPs suitable for dCas9 mRNA delivery. Additionally, we provide a protocol for the co-encapsulation of t

Individual behaviors are critical for preventing the spread of coronavirus disease 2019 (COVID-19) infection. Given that both protective and risky behaviors influence risk of infection, it is critical that we understand how such behaviors cluster together and in whom. Using a data-driven approach, we identified clusters of COVID-19-related protective and risky behaviors and examined associations with socio-demographic, pandemic, and mental health factors. Data came from a cross-sectional online U.S. nationwide study of 832 adults with high levels of pre-pandemic trauma. Latent class analysis was performed with ten protective (e.g., washing hands, wearing masks) and eight risky (e.g., attending indoor restaurants, taking a flight) behaviors for COVID-19. Then, we examined distributions of socio-demographic and pandemic factors across behavior classes using ANOVA or Chi-square tests, and associations between mental health factors (depressive, anxiety, posttraumatic stress symptoms) and behavior classes using multinomial logistic regression. We identified four classes, including three classes with relatively low risky but high (28.8%), moderate (33.5%) and minimal (25.5%) protective behaviors and one high risky behaviors class with associated moderate protective behaviors (12.1%). Age, sexual orientation, political preference, and most pandemic factors differed significantly across behavior classes. Anxiety and posttraumatic stress symptoms, but not depression, were higher in the High Risk, but also Highly and Moderately Protective classes, relative to Minimally Protective. Prevention and intervention efforts should examine constellations of protective and risky behaviors to comprehensively understand risk, and consider current anxiety and posttraumatic stress symptoms as potential risk indicators.

BackgroundMeningiomas are the most common primary intracranial tumor in adults. Clinical care is currently guided by the World Health Organization (WHO) grade assigned to meningiomas, a 3-tiered grading system based on histopathology features, as well as extent of surgical resection. Clinical behavior, however, often fails to conform to the WHO grade. Additional prognostic information is needed to optimize patient management.MethodsWe evaluated whether chromosomal copy-number data improved prediction of time-to-recurrence for patients with meningioma who were treated with surgery, relative to the WHO schema. The models were developed using Cox proportional hazards, random survival forest, and gradient boosting in a discovery cohort of 527 meningioma patients and validated in 2 independent cohorts of 172 meningioma patients characterized by orthogonal genomic platforms.ResultsWe developed a 3-tiered grading scheme (Integrated Grades 1-3), which incorporated mitotic count and loss of chromosome 1p, 3p, 4, 6, 10, 14q, 18, 19, or CDKN2A. 32% of meningiomas reclassified to either a lower-risk or higher-risk Integrated Grade compared to their assigned WHO grade. The Integrated Grade more accurately identified meningioma patients at risk for recurrence, relative to the WHO grade, as determined by time-dependent area under the curve, average precision, and the Brier score.ConclusionWe propose a molecularly integrated grading scheme for meningiomas that significantly improves upon the current WHO grading system in prediction of progression-free survival. This framework can be broadly adopted by clinicians with relative ease using widely available genomic technologies and presents an advance in the care of meningioma patients.

Individual behaviors are critical for preventing the spread of coronavirus disease 2019 (COVID-19) infection. Given that both protective and risky behaviors influence risk of infection, it is critical that we understand how such behaviors cluster together and in whom. Using a data-driven approach, we identified clusters of COVID-19-related protective and risky behaviors and examined associations with socio-demographic, pandemic, and mental health factors. Data came from a cross-sectional online U.S. nationwide study of 832 adults with high levels of pre-pandemic trauma. Latent class analysis was performed with ten protective (e.g., washing hands, wearing masks) and eight risky (e.g., attending indoor restaurants, taking a flight) behaviors for COVID-19. Then, we examined distributions of socio-demographic and pandemic factors across behavior classes using ANOVA or Chi-square tests, and associations between mental health factors (depressive, anxiety, posttraumatic stress symptoms) and behavior classes using multinomial logistic regression. We identified four classes, including three classes with relatively low risky but high (28.8%), moderate (33.5%) and minimal (25.5%) protective behaviors and one high risky behaviors class with associated moderate protective behaviors (12.1%). Age, sexual orientation, political preference, and most pandemic factors differed significantly across behavior classes. Anxiety and posttraumatic stress symptoms, but not depression, were higher in the High Risk, but also Highly and Moderately Protective classes, relative to Minimally Protective. Prevention and intervention efforts should examine constellations of protective and risky behaviors to comprehensively understand risk, and consider current anxiety and posttraumatic stress symptoms as potential risk indicators.

ObjectivePsychiatric disorders increase risk for contracting coronavirus disease 2019 (COVID-19), but we know little about relationships between psychiatric symptoms and COVID-19 risky and protective behaviors. Posttraumatic stress disorder (PTSD) has been associated with increased propensity to engage in risky behaviors, but may also be associated with increased COVID-19 protective behaviors due to increased threat sensitivity and social isolation.MethodWe examined associations of PTSD symptoms with COVID-19-related protective and risky behaviors using data from a cross-sectional online United States study among 845 US adults in August through September 2020. PTSD symptoms (PTSD Checklist-5), sociodemographics, COVID-19-related experiences and vulnerabilities, and past 30-day engagement in 10 protective and eight risky behaviors for COVID-19 were assessed via self-report. We examined associations between PTSD symptoms and COVID-19 protective and risky behaviors with linear regressions, adjusting for covariates.ResultsProbable PTSD and higher PTSD symptom severity were associated with greater engagement in protective behaviors, but also greater engagement in risky behaviors. Associations were only slightly attenuated by adjustment for COVID-19 exposures and perceived likelihood and severity of COVID-19. Associations varied by PTSD clusters: intrusions and arousal were associated with both more protective and more risky behaviors, whereas negative cognitions or mood was associated only with more risky, and avoidance only with more protective, behaviors.ConclusionHigher PTSD symptoms were associated with engagement in more protective but also more risky behaviors for COVID-19. Mental health should be considered in the design of public health campaigns dedicated to limiting infectious disease spread. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The coronavirus disease 2019 (COVID-19) pandemic has created a global health crisis, with disproportionate effects on vulnerable sociodemographic groups. Although the pandemic is showing potential to increase suicide ideation (SI), we know little about which sociodemographic characteristics or COVID-19 experiences are associated with SI. Our United States-based sample (n = 837 adults [mean age = 37.1 years]) completed an online survey during August-September 2020. The study utilized an online convenience sample from a prior study, which was enriched for exposure to trauma and experiences of posttraumatic stress symptoms. We assessed SI using the Beck Depression Inventory-II. Traditional (i.e., logistic regression) and machine learning (i.e., LASSO, random forest) methods evaluated associations of 148 self-reported COVID-19 factors and sociodemographic characteristics with current SI. 234 participants (28.0%) reported SI. Twenty items were significantly associated with SI from logistic regression. Of these 20 items, LASSO identified seven sociodemographic characteristics (younger age, lower income, single relationship status, sexual orientation other than heterosexual as well as specifically identifying as bisexual, non-full-time employment, and living in a town) and six COVID-19 factors (not engaging in protective COVID-19 behaviors, receiving mental health treatment (medication and/or psychotherapy) due to the COVID-19 pandemic, socializing during the pandemic, losing one's job due to COVID-19, having a friend with COVID-19, and having an acquaintance with COVID-19) associated with SI. Random forest findings were largely consistent with LASSO. These findings may inform multidisciplinary research and intervention work focused on understanding and preventing adverse mental health outcomes such as SI during and in the aftermath of the pandemic.

Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene amplified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC-dependent promoters. High AAMDC expression is associated with sensitization to dactolisib and everolimus, and these PI3K-mTOR inhibitors exhibit synergistic interactions with anti-estrogens in IntClust2 models. Ectopic AAMDC expression is sufficient to activate AKT signaling, resulting in estrogen-independent tumor growth. Thus, AAMDC-overexpressing tumors may be sensitive to PI3K-mTORC1 blockers in combination with anti-estrogens. Lastly, we provide evidence that AAMDC can interact with the RabGTPase-activating protein RabGAP1L, and that AAMDC, RabGAP1L, and Rab7a colocalize in endolysosomes. The discovery of the RabGAP1L-AAMDC assembly platform provides insights for the design of selective blockers to target malignancies having the AAMDC amplification.

Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene amplified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC-dependent promoters. High AAMDC expression is associated with sensitization to dactolisib and everolimus, and these PI3K-mTOR inhibitors exhibit synergistic interactions with anti-estrogens in IntClust2 models. Ectopic AAMDC expression is sufficient to activate AKT signaling, resulting in estrogen-independent tumor growth. Thus, AAMDC-overexpressing tumors may be sensitive to PI3K-mTORC1 blockers in combination with anti-estrogens. Lastly, we provide evidence that AAMDC can interact with the RabGTPase-activating protein RabGAP1L, and that AAMDC, RabGAP1L, and Rab7a colocalize in endolysosomes. The discovery of the RabGAP1L-AAMDC assembly platform provides insights for the design of selective blockers to target malignancies having the AAMDC amplification.

Despite decades of study, the molecular mechanisms and selectivity of the biomolecular components of honeybee (Apis mellifera) venom as anticancer agents remain largely unknown. Here, we demonstrate that honeybee venom and its major component melittin potently induce cell death, particularly in the aggressive triple-negative and HER2-enriched breast cancer subtypes. Honeybee venom and melittin suppress the activation of EGFR and HER2 by interfering with the phosphorylation of these receptors in the plasma membrane of breast carcinoma cells. Mutational studies reveal that a positively charged C-terminal melittin sequence mediates plasma membrane interaction and anticancer activity. Engineering of an RGD motif further enhances targeting of melittin to malignant cells with minimal toxicity to normal cells. Lastly, administration of melittin enhances the effect of docetaxel in suppressing breast tumor growth in an allograft model. Our work unveils a molecular mechanism underpinning the anticancer selectivity of melittin, and outlines treatment strategies to target aggressive breast cancers.

Despite decades of study, the molecular mechanisms and selectivity of the biomolecular components of honeybee (Apis mellifera) venom as anticancer agents remain largely unknown. Here, we demonstrate that honeybee venom and its major component melittin potently induce cell death, particularly in the aggressive triple-negative and HER2-enriched breast cancer subtypes. Honeybee venom and melittin suppress the activation of EGFR and HER2 by interfering with the phosphorylation of these receptors in the plasma membrane of breast carcinoma cells. Mutational studies reveal that a positively charged C-terminal melittin sequence mediates plasma membrane interaction and anticancer activity. Engineering of an RGD motif further enhances targeting of melittin to malignant cells with minimal toxicity to normal cells. Lastly, administration of melittin enhances the effect of docetaxel in suppressing breast tumor growth in an allograft model. Our work unveils a molecular mechanism underpinning the anticancer selectivity of melittin, and outlines treatment strategies to target aggressive breast cancers.

Mutations in the FMS-like tyrosine kinase 3 (FLT3) gene in 13q12.2 are among the most common driver events in acute leukemia, leading to increased cell proliferation and survival through activation of the phosphatidylinositol 3-kinase/AKT-, RAS/MAPK-, and STAT5-signaling pathways. In this study, we examine the pathogenetic impact of somatic hemizygous 13q12.2 microdeletions in B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) using 5 different patient cohorts (in total including 1418 cases). The 13q12.2 deletions occur immediately 59 of FLT3 and involve the PAN3 locus. By detailed analysis of the 13q12.2 segment, we show that the deletions lead to loss of a topologically associating domain border and an enhancer of FLT3. This results in increased cis interactions between the FLT3 promoter and another enhancer located distally to the deletion breakpoints, with subsequent allele-specific upregulation of FLT3 expression, expected to lead to ligand-independent activation of the receptor and downstream signaling. The 13q12.2 deletions are highly enriched in the high-hyperdiploid BCP ALL subtype (frequency 3.9% vs 0.5% in other BCP ALL) and in cases that subsequently relapsed. Taken together, our study describes a novel mechanism of FLT3 involvement in leukemogenesis by upregulation via chromatin remodeling and enhancer hijacking. These data further emphasize the role of FLT3 as a driver gene in BCP ALL., Funding Agencies|Swedish Cancer SocietySwedish Cancer Society [CAN 2017/291, CAN 2016/497]; Swedish Childhood Cancer Foundation [TJ2018-0061, PR2018-0004, PR2018-0023]; Swedish Research CouncilSwedish Research Council [2016-01084, 2016-01459]; Ministry of Health of the Czech Republic (Czech Health Research Council) [15-30626A]; University Hospital Motol [00064203]; National Health Service [ALFSKANE-623431]; Royal Physiographic Society of Lund

Acute myeloid leukaemia (AML) is a heterogeneous disorder characterised by the accumulation of immature haematopoietic cells blocked at various stages of differentiation. Despite improved survival rates over the past decade, relapse occurs in approximately 70% patients undergoing chemotherapy. A potential reason for this is that current clinical protocols do not take account of the level of residual disease present at remission. Therefore, one strategy to reduce relapse rates is to monitor minimal residual disease and continue to treat until the patient is minimal residual disease negative. Current minimal residual disease markers are available for patients with characterised fusion genes but approximately 50% of patients have no detectable chromosomal aberration and therefore are without markers. Gene expression profiling is a powerful tool for disease classification, prognosis and therapeutic predictions. This study aimed to investigate the use gene expression profiling to identify novel minimal residual disease markers for specific AML sub-groups. Patient diagnostic samples were profiled to identify genes specific to AML patients with a favourable translocation in order to establish the "proof-of-principle". Several genes identified were followed in patient diagnostic and follow- up samples and compared to the markers currently used. Continuing with normal karyotype AML, genes were identified as specific to this sub-group. Several homeobox (HOX) genes and the Wilms' tumour (WT1) gene were identified and their MRD levels followed in diagnostic and follow-up samples. Only WT1 identified as specific to normal karyotype AML met the necessary criteria to be an MRD marker. Although the majority of genes selected from the GEP in this study proved unsuitable as markers, the identification and validation of a marker already used for MRD monitoring, WT1, demonstrates the ability of gene expression profiling to identify potential minimal residual disease markers in normal k

Acute myeloid leukaemia (AML) is a heterogeneous disorder characterised by the accumulation of immature haematopoietic cells blocked at various stages of differentiation. Despite improved survival rates over the past decade, relapse occurs in approximately 70% patients undergoing chemotherapy. A potential reason for this is that current clinical protocols do not take account of the level of residual disease present at remission. Therefore, one strategy to reduce relapse rates is to monitor minimal residual disease and continue to treat until the patient is minimal residual disease negative. Current minimal residual disease markers are available for patients with characterised fusion genes but approximately 50% of patients have no detectable chromosomal aberration and therefore are without markers. Gene expression profiling is a powerful tool for disease classification, prognosis and therapeutic predictions. This study aimed to investigate the use gene expression profiling to identify novel minimal residual disease markers for specific AML sub-groups. Patient diagnostic samples were profiled to identify genes specific to AML patients with a favourable translocation in order to establish the "proof-of-principle". Several genes identified were followed in patient diagnostic and follow- up samples and compared to the markers currently used. Continuing with normal karyotype AML, genes were identified as specific to this sub-group. Several homeobox (HOX) genes and the Wilms' tumour (WT1) gene were identified and their MRD levels followed in diagnostic and follow-up samples. Only WT1 identified as specific to normal karyotype AML met the necessary criteria to be an MRD marker. Although the majority of genes selected from the GEP in this study proved unsuitable as markers, the identification and validation of a marker already used for MRD monitoring, WT1, demonstrates the ability of gene expression profiling to identify potential minimal residual disease markers in normal k

Golden, E., Rashwan, R., Woodward, E. A., Sgro, A., Wang, E., Sorolla, A., ... Blancafort, P. (2021). The oncogene AAMDC links PI3K-AKT-mTOR signaling with metabolic reprograming in estrogen receptor-positive breast cancer. Nature Communications, 12, article 1920. https://doi.org/10.1038/s41467-021-22101-7

Members of the Dickinson State Teachers College Ensemble pose for a picture. The members are seated in chairs holding their instruments., Photographic prints, 26 x 20 cm., Title created by staff.