Genetic and functional analysis of Raynaud's syndrome implicates loci in vasculature and immunity.

Raynaud's syndrome is a dysautonomia where exposure to cold causes vasoconstriction and hypoxia, particularly in the extremities. We performed meta-analysis in four cohorts and discovered eight loci (ADRA2A, IRX1, NOS3, ACVR2A, TMEM51, PCDH10-DT, HLA, and RAB6C) where ADRA2A, ACVR2A, NOS3, TMEM51, and IRX1 co-localized with expression quantitative trait loci (eQTLs), particularly in distal arteries. CRISPR gene editing further showed that ADRA2A and NOS3 loci modified gene expression and in situ RNAscope clarified the specificity of ADRA2A in small vessels and IRX1 around small capillaries in the skin. A functional contraction assay in the cold showed lower contraction in ADRA2A-deficient and higher contraction in ADRA2A-overexpressing smooth muscle cells. Overall, our study highlights the power of genome-wide association testing with functional follow-up as a method to understand complex diseases. The results indicate temperature-dependent adrenergic signaling through ADRA2A, effects at the microvasculature by IRX1, endothelial signaling by NOS3, and immune mechanisms by the HLA locus in Raynaud's syndrome.

Targeting CD33+ Acute Myeloid Leukemia with GLK-33, a Lintuzumab-Auristatin Conjugate with a Wide Therapeutic Window.

CD33 (Siglec-3) is a cell surface receptor expressed in approximately 90% of acute myeloid leukemia (AML) blasts, making it an attractive target for therapy of AML. Although previous CD33-targeting antibody-drug conjugates (ADC) like gemtuzumab ozogamicin (GO, Mylotarg) have shown efficacy in AML treatment, they have suffered from toxicity and narrow therapeutic window. This study aimed to develop a novelADCwith improved tolerability and a wider therapeutic window. GLK-33 consists of the anti-CD33 antibody lintuzumab and eight mavg-MMAU auristatin linkerpayloads per antibody. The experimental methods included testing in cell cultures, patient-derived samples, mouse xenograft models, and rat toxicology studies. GLK-33 exhibited remarkable efficacy in reducing cell viability within CD33-positive leukemia cell lines and primary AML samples. Notably, GLK-33 demonstrated antitumor activity at single dose as low as 300 mg/kg in mice, while maintaining tolerability at single dose of 20 to 30 mg/kg in rats. In contrast with both GO and lintuzumab vedotin, GLK-33 exhibited a wide therapeutic window and activity against multidrug-resistant cells. The development of GLK-33 addresses the limitations of previous ADCs, offering a wider therapeutic window, improved tolerability, and activity against drug-resistant leukemia cells. These findings encourage further exploration of GLK-33 in AML through clinical trials.

Designing patient-oriented combination therapies for acute myeloid leukemia based on efficacy/toxicity integration and bipartite network modeling.

Acute myeloid leukemia (AML), a heterogeneous and aggressive blood cancer, does not respond well to single-drug therapy. A combination of drugs is required to effectively treat this disease. Computational models are critical for combination therapy discovery due to the tens of thousands of two-drug combinations, even with approved drugs. While predicting synergistic drugs is the focus of current methods, few consider drug efficacy and potential toxicity, which are crucial for treatment success. To find effective new drug candidates, we constructed a bipartite network using patient-derived tumor samples and drugs. The network is based on drug-response screening and summarizes all treatment response heterogeneity as drug response weights. This bipartite network is then projected onto the drug part, resulting in the drug similarity network. Distinct drug clusters were identified using community detection methods, each targeting different biological processes and pathways as revealed by enrichment and pathway analysis of the drugs' protein targets. Four drugs with the highest efficacy and lowest toxicity from each cluster were selected and tested for drug sensitivity using cell viability assays on various samples. Results show that ruxolitinib-ulixertinib and sapanisertib-LY3009120 are the most effective combinations with the least toxicity and the best synergistic effect on blast cells. These findings lay the foundation for personalized and successful AML therapies, ultimately leading to the development of drug combinations that can be used alongside standard first-line AML treatment.

Monosomy 7/del(7q) cause sensitivity to inhibitors of nicotinamide phosphoribosyltransferase in acute myeloid leukemia.

ABSTRACT: Monosomy 7 and del(7q) (-7/-7q) are frequent chromosomal abnormalities detected in up to 10% of patients with acute myeloid leukemia (AML). Despite unfavorable treatment outcomes, no approved targeted therapies exist for patients with -7/-7q. Therefore, we aimed to identify novel vulnerabilities. Through an analysis of data from ex vivo drug screens of 114 primary AML samples, we discovered that -7/-7q AML cells are highly sensitive to the inhibition of nicotinamide phosphoribosyltransferase (NAMPT). NAMPT is the rate-limiting enzyme in the nicotinamide adenine dinucleotide salvage pathway. Mechanistically, the NAMPT gene is located at 7q22.3, and deletion of 1 copy due to -7/-7q results in NAMPT haploinsufficiency, leading to reduced expression and a therapeutically targetable vulnerability to the inhibition of NAMPT. Our results show that in -7/-7q AML, differentiated CD34+CD38+ myeloblasts are more sensitive to the inhibition of NAMPT than less differentiated CD34+CD38- myeloblasts. Furthermore, the combination of the BCL2 inhibitor venetoclax and the NAMPT inhibitor KPT-9274 resulted in the death of significantly more leukemic blasts in AML samples with -7/-7q than the NAMPT inhibitor alone. In conclusion, our findings demonstrate that AML with -7/-7q is highly sensitive to NAMPT inhibition, suggesting that NAMPT inhibitors have the potential to be an effective targeted therapy for patients with monosomy 7 or del(7q).

Robust scoring of selective drug responses for patient-tailored therapy selection.

Most patients with advanced malignancies are treated with severely toxic, first-line chemotherapies. Personalized treatment strategies have led to improved patient outcomes and could replace one-size-fits-all therapies, yet they need to be tailored by testing of a range of targeted drugs in primary patient cells. Most functional precision medicine studies use simple drug-response metrics, which cannot quantify the selective effects of drugs (i.e., the differential responses of cancer cells and normal cells). We developed a computational method for selective drug-sensitivity scoring (DSS), which enables normalization of the individual patient's responses against normal cell responses. The selective response scoring uses the inhibition of noncancerous cells as a proxy for potential drug toxicity, which can in turn be used to identify effective and safer treatment options. Here, we explain how to apply the selective DSS calculation for guiding precision medicine in patients with leukemia treated across three cancer centers in Europe and the USA; the generic methods are also widely applicable to other malignancies that are amenable to drug testing. The open-source and extendable R-codes provide a robust means to tailor personalized treatment strategies on the basis of increasingly available ex vivo drug-testing data from patients in real-world and clinical trial settings. We also make available drug-response profiles to 527 anticancer compounds tested in 10 healthy bone marrow samples as reference data for selective scoring and de-prioritization of drugs that show broadly toxic effects. The procedure takes <60 min and requires basic skills in R.

Using Proteomics Data to Identify Personalized Treatments in Multiple Myeloma: A Machine Learning Approach.

This paper describes a machine learning (ML) decision support system to provide a list of chemotherapeutics that individual multiple myeloma (MM) patients are sensitive/resistant to, based on their proteomic profile. The methodology used in this study involved understanding the parameter space and selecting the dominant features (proteomics data), identifying patterns of proteomic profiles and their association to the recommended treatments, and defining the decision support system of personalized treatment as a classification problem. During the data analysis, we compared several ML algorithms, such as linear regression, Random Forest, and support vector machines, to classify patients as sensitive/resistant to therapeutics. A further analysis examined data-balancing techniques that emerged due to the small cohort size. The results suggest that utilizing proteomics data is a promising approach for identifying effective treatment options for patients with MM (reaching on average an accuracy of 81%). Although this pilot study was limited by the small patient cohort (39 patients), which restricted the training and validation of the explored ML solutions to identify complex associations between proteins, it holds great promise for developing personalized anti-MM treatments using ML approaches.

An ischemic myelopathy case series: Flaccid paraplegia following a spike ball save and numbness while walking normally.

Spinal cord infarctions in children are rare and early magnetic resonance imaging studies are often negative. A high clinical suspicion must be maintained to identify stroke and initiate workup for underlying etiology to suggest appropriate treatment. We present two cases of spinal cord infarction without major preceding trauma. The first was caused by disc herniation and external impingement of a radiculomedullary artery and the second was due to fibrocartilaginous embolism with classic imaging findings of ventral and dorsal cord infarctions, respectively. These cases were treated conservatively with diagnostic workup and aspirin, though additional treatments which can be considered with prompt diagnosis are also explored in our discussion. Both cases recovered the ability to ambulate independently within months. Case 1 is attending college and ambulates campus with a single-point cane. Case 2 ambulates independently, though has some difficulty with proprioception of the feet so uses wheelchairs for long-distance ambulation.

Proteomic and Metabolomic Analysis of Bone Marrow and Plasma from Patients with Extramedullary Multiple Myeloma Identifies Distinct Protein and Metabolite Signatures.

Multiple myeloma (MM) is an incurable haematological malignancy of plasma cells in the bone marrow. In rare cases, an aggressive form of MM called extramedullary multiple myeloma (EMM) develops, where myeloma cells enter the bloodstream and colonise distal organs or soft tissues. This variant is associated with refractoriness to conventional therapies and a short overall survival. The molecular mechanisms associated with EMM are not yet fully understood. Here, we analysed the proteome of bone marrow mononuclear cells and blood plasma from eight patients (one serial sample) with EMM and eight patients without extramedullary spread. The patients with EMM had a significantly reduced overall survival with a median survival of 19 months. Label-free mass spectrometry revealed 225 proteins with a significant differential abundance between bone marrow mononuclear cells (BMNCs) isolated from patients with MM and EMM. This plasma proteomics analysis identified 22 proteins with a significant differential abundance. Three proteins, namely vascular cell adhesion molecule 1 (VCAM1), pigment epithelium derived factor (PEDF), and hepatocyte growth factor activator (HGFA), were verified as the promising markers of EMM, with the combined protein panel showing excellent accuracy in distinguishing EMM patients from MM patients. Metabolomic analysis revealed a distinct metabolite signature in EMM patient plasma compared to MM patient plasma. The results provide much needed insight into the phenotypic profile of EMM and in identifying promising plasma-derived markers of EMM that may inform novel drug development strategies.

Personalizing precision medicine: Patients with AML perceptions about treatment decisions.

BACKGROUND: This study aims to explore patients' with acute myeloid leukemia perceptions about precision medicine and their preferences for involvement in this new area of shared decision-making. METHODS: Individual semi-structured interviews were conducted in Finland, Italy and Germany (n = 16). The study population included patients aged 24-79 years. Interviews were analyzed with thematic content analysis. RESULTS: Patient's perceived lack of knowledge as a barrier for their involvement in decision-making. Treatment decisions were often made rapidly based on the patient's intuition and trust for the physician rather than on information, in situations that decrease the patient's decision capacity. The patients emphasized that they are in a desperate situation that makes them willing to accept treatment with low probabilities of being cured. CONCLUSIONS: The study raised important issues regarding patients' understanding of precision medicine and challenges concerning how to involve patients in medical decision-making. Although technical advances were viewed positively, the role of the physician as an expert and person-of-trust cannot be replaced. PRACTICE IMPLICATIONS: Regardless of patients' preferences for involvement in decision-making, information plays a crucial role for patients' perceived involvement in their care. The concepts related to precision medicine are complex and will imply challenges to patient education.

Deep Immune Profiling of Multiple Myeloma at Diagnosis and under Lenalidomide Maintenance Therapy.

The bone marrow microenvironment interacts with malignant cells and regulates cancer survival and immune evasion in multiple myeloma (MM). We investigated the immune profiles of longitudinal bone marrow samples from patients with newly diagnosed MM (n = 18) using cytometry by time-of-flight. The results before and during treatment were compared between patients with good (GR, n = 11) and bad (BR, n = 7) responses to lenalidomide/bortezomib/dexamethasone-based treatment. Before treatment, the GR group had a lower tumor cell burden and a higher number of T cells with a phenotype shifted toward CD8+ T cells expressing markers attributed to cytotoxicity (CD45RA and CD57), a higher abundance of CD8+ terminal effector cells, and a lower abundance of CD8+ naïve T cells. On natural killer (NK) cells, increased expression of CD56 (NCAM), CD57, and CD16 was seen at baseline in the GR group, indicating their maturation and cytotoxic potential. During lenalidomide-based treatment, the GR patients showed an increase in effector memory CD4+ and CD8+ T-cell subsets. These findings support distinct immune patterns in different clinical contexts, suggesting that deep immune profiling could be used for treatment guidance and warrants further exploration.

Integrative phosphoproteomics defines two biologically distinct groups of KMT2A rearranged acute myeloid leukaemia with different drug response phenotypes.

Acute myeloid leukaemia (AML) patients harbouring certain chromosome abnormalities have particularly adverse prognosis. For these patients, targeted therapies have not yet made a significant clinical impact. To understand the molecular landscape of poor prognosis AML we profiled 74 patients from two different centres (in UK and Finland) at the proteomic, phosphoproteomic and drug response phenotypic levels. These data were complemented with transcriptomics analysis for 39 cases. Data integration highlighted a phosphoproteomics signature that define two biologically distinct groups of KMT2A rearranged leukaemia, which we term MLLGA and MLLGB. MLLGA presented increased DOT1L phosphorylation, HOXA gene expression, CDK1 activity and phosphorylation of proteins involved in RNA metabolism, replication and DNA damage when compared to MLLGB and no KMT2A rearranged samples. MLLGA was particularly sensitive to 15 compounds including genotoxic drugs and inhibitors of mitotic kinases and inosine-5-monosphosphate dehydrogenase (IMPDH) relative to other cases. Intermediate-risk KMT2A-MLLT3 cases were mainly represented in a third group closer to MLLGA than to MLLGB. The expression of IMPDH2 and multiple nucleolar proteins was higher in MLLGA and correlated with the response to IMPDH inhibition in KMT2A rearranged leukaemia, suggesting a role of the nucleolar activity in sensitivity to treatment. In summary, our multilayer molecular profiling of AML with poor prognosis and KMT2A-MLLT3 karyotypes identified a phosphoproteomics signature that defines two biologically and phenotypically distinct groups of KMT2A rearranged leukaemia. These data provide a rationale for the potential development of specific therapies for AML patients characterised by the MLLGA phosphoproteomics signature identified in this study.

Large registry-based analysis of genetic predisposition to tuberculosis identifies genetic risk factors at HLA.

Tuberculosis is a significant public health concern resulting in the death of over 1 million individuals each year worldwide. While treatment options and vaccines exist, a substantial number of infections still remain untreated or are caused by treatment resistant strains. Therefore, it is important to identify mechanisms that contribute to risk and prognosis of tuberculosis as this may provide tools to understand disease mechanisms and provide novel treatment options for those with severe infection. Our goal was to identify genetic risk factors that contribute to the risk of tuberculosis and to understand biological mechanisms and causality behind the risk of tuberculosis. A total of 1895 individuals in the FinnGen study had International Classification of Diseases-based tuberculosis diagnosis. Genome-wide association study analysis identified genetic variants with statistically significant association with tuberculosis at the human leukocyte antigen (HLA) region (P < 5e-8). Fine mapping of the HLA association provided evidence for one protective haplotype tagged by HLA DQB1*05:01 (P = 1.82E-06, OR = 0.81 [CI 95% 0.74-0.88]), and predisposing alleles tagged by HLA DRB1*13:02 (P = 0.00011, OR = 1.35 [CI 95% 1.16-1.57]). Furthermore, genetic correlation analysis showed association with earlier reported risk factors including smoking (P < 0.05). Mendelian randomization supported smoking as a risk factor for tuberculosis (inverse-variance weighted P < 0.05, OR = 1.83 [CI 95% 1.15-2.93]) with no significant evidence of pleiotropy. Our findings indicate that specific HLA alleles associate with the risk of tuberculosis. In addition, lifestyle risk factors such as smoking contribute to the risk of developing tuberculosis.

Ex vivo venetoclax sensitivity testing predicts treatment response in acute myeloid leukemia.

The BCL-2 inhibitor venetoclax has revolutionized the treatment of acute myeloid leukemia (AML) in patients not benefiting from intensive chemotherapy. Nevertheless, treatment failure remains a challenge, and predictive markers are needed, particularly for relapsed or refractory AML. Ex vivo drug sensitivity testing may correlate with outcomes, but its prospective predictive value remains unexplored. Here we report the results of the first stage of the prospective phase II VenEx trial evaluating the utility and predictiveness of venetoclax sensitivity testing using different cell culture conditions and cell viability assays in patients receiving venetoclax-azacitidine. Participants with de novo AML ineligible for intensive chemotherapy, relapsed or refractory AML, or secondary AML were included. The primary endpoint was the treatment response in participants showing ex vivo sensitivity and the key secondary endpoints were the correlation of sensitivity with responses and survival. Venetoclax sensitivity testing was successful in 38/39 participants. Experimental conditions significantly influenced the predictive accuracy. Blast-specific venetoclax sensitivity measured in conditioned medium most accurately correlated with treatment outcomes; 88% of sensitive participants achieved a treatment response. The median survival was significantly longer for participants who were ex vivo-sensitive to venetoclax (14.6 months for venetoclax-sensitive patients vs. 3.5 for venetoclax-insensitive patients, P<0.001). This analysis illustrates the feasibility of integrating drug-response profiling into clinical practice and demonstrates excellent predictivity. This trial is registered with ClinicalTrials.gov identifier: NCT04267081.

Erythroid/megakaryocytic differentiation confers BCL-XL dependency and venetoclax resistance in acute myeloid leukemia.

Myeloid neoplasms with erythroid or megakaryocytic differentiation include pure erythroid leukemia, myelodysplastic syndrome with erythroid features, and acute megakaryoblastic leukemia (FAB M7) and are characterized by poor prognosis and limited treatment options. Here, we investigate the drug sensitivity landscape of these rare malignancies. We show that acute myeloid leukemia (AML) cells with erythroid or megakaryocytic differentiation depend on the antiapoptotic protein B-cell lymphoma (BCL)-XL, rather than BCL-2, using combined ex vivo drug sensitivity testing, genetic perturbation, and transcriptomic profiling. High-throughput screening of >500 compounds identified the BCL-XL-selective inhibitor A-1331852 and navitoclax as highly effective against erythroid/megakaryoblastic leukemia cell lines. In contrast, these AML subtypes were resistant to the BCL-2 inhibitor venetoclax, which is used clinically in the treatment of AML. Consistently, genome-scale CRISPR-Cas9 and RNAi screening data demonstrated the striking essentiality of BCL-XL-encoding BCL2L1 but not BCL2 or MCL1, for the survival of erythroid/megakaryoblastic leukemia cell lines. Single-cell and bulk transcriptomics of patient samples with erythroid and megakaryoblastic leukemias identified high BCL2L1 expression compared with other subtypes of AML and other hematological malignancies, where BCL2 and MCL1 were more prominent. BCL-XL inhibition effectively killed blasts in samples from patients with AML with erythroid or megakaryocytic differentiation ex vivo and reduced tumor burden in a mouse erythroleukemia xenograft model. Combining the BCL-XL inhibitor with the JAK inhibitor ruxolitinib showed synergistic and durable responses in cell lines. Our results suggest targeting BCL-XL as a potential therapy option in erythroid/megakaryoblastic leukemias and highlight an AML subgroup with potentially reduced sensitivity to venetoclax-based treatments.

A germline exome analysis reveals harmful POT1 variants in multiple myeloma patients and families.

Observations of inherited susceptibility to multiple myeloma have led to active research in defining predisposing genes to the disease. Here, we analysed 128 plasma cell dyscrasia patients' germline whole-exome sequencing data. Rare dominantly inherited pathogenic or likely pathogenic (P/LP) variant was found in 9.4% of the patients. Among the P/LP variants, CHEK2 (p. Thr410MetfsTer15) was the most prevalent (n = 5, 3.9%). Interestingly, P/LP variants in POT1 were identified in three patients (2.3%). Our findings broaden the spectrum of POT1-related cancers and demonstrate the importance of the germline genetic analysis in hematological malignancies.

Megakaryopoiesis impairment through acute innate immune signaling activation by azacitidine.

Thrombocytopenia, prevalent in the majority of patients with myeloid malignancies, such as myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML), is an independent adverse prognostic factor. Azacitidine (AZA), a mainstay therapeutic agent for stem cell transplant-ineligible patients with MDS/AML, often transiently induces or further aggravates disease-associated thrombocytopenia by an unknown mechanism. Here, we uncover the critical role of an acute type-I interferon (IFN-I) signaling activation in suppressing megakaryopoiesis in AZA-mediated thrombocytopenia. We demonstrate that megakaryocytic lineage-primed progenitors present IFN-I receptors and, upon AZA exposure, engage STAT1/SOCS1-dependent downstream signaling prematurely attenuating thrombopoietin receptor (TPO-R) signaling and constraining megakaryocytic progenitor cell growth and differentiation following TPO-R stimulation. Our findings directly implicate RNA demethylation and IFN-I signal activation as a root cause for AZA-mediated thrombocytopenia and suggest mitigation of TPO-R inhibitory innate immune signaling as a suitable therapeutic strategy to support platelet production, particularly during the early phases of AZA therapy.

An immunity and pyroptosis gene-pair signature predicts overall survival in acute myeloid leukemia.

Treatment responses of patients with acute myeloid leukemia (AML) are known to be heterogeneous, posing challenges for risk scoring and treatment stratification. In this retrospective multi-cohort study, we investigated whether combining pyroptosis- and immune-related genes improves prognostic classification of AML patients. Using a robust gene pairing approach, which effectively eliminates batch effects across heterogeneous patient cohorts and transcriptomic data, we developed an immunity and pyroptosis-related prognostic (IPRP) signature that consists of 15 genes. Using 5 AML cohorts (n = 1327 patients total), we demonstrate that the IPRP score leads to more consistent and accurate survival prediction performance, compared with 10 existing signatures, and that IPRP scoring is widely applicable to various patient cohorts, treatment procedures and transcriptomic technologies. Compared to current standards for AML patient stratification, such as age or ELN2017 risk classification, we demonstrate an added prognostic value of the IPRP risk score for providing improved prediction of AML patients. Our web-tool implementation of the IPRP score and a simple 4-factor nomogram enables practical and robust risk scoring for AML patients. Even though developed for AML patients, our pan-cancer analyses demonstrate a wider application of the IPRP signature for prognostic prediction and analysis of tumor-immune interplay also in multiple solid tumors.

Aminopeptidases in Cancer, Biology and Prospects for Pharmacological Intervention.

Aminopeptidases, which catalyze the cleavage of amino acids from the amino terminus of proteins, are widely distributed in the natural world and play a crucial role in cellular processes and functions, including metabolism, signaling, angiogenesis, and immunology. They are also involved in the homeostasis of amino acids and proteins that are required for cellular proliferation. Tumor cells are highly dependent on the exogenous supply of amino acids for their survival, and overexpression of aminopeptidase facilitates rapid tumor cell proliferation. In addition, clinical studies have demonstrated that patients with cancers with high aminopeptidase expression often have poorer outcomes. Emerging evidence supports the rationale of inhibiting aminopeptidase activity as a targeted approach for novel treatment options, as limiting the availability of amino acids can be selectively lethal to tumor cells. While there are agents that directly target aminopeptidases that demonstrate potential as cancer therapies, such as bestatin and tosedostat, more selective and more targeted therapeutic approaches are needed. This article specifically looks at the biological role of aminopeptidases in both normal and cancer processes, and their potential as a biological target for future therapeutic strategies. When examining previous publications, most do not cover aminopeptidases and their role in cancer processes. Aminopeptidases play a vital role in cell processes and functions; however, their overexpression may lead to a rapid proliferation of tumor cells. Emerging evidence supports the rationale of leveraging aminopeptidase activity as a targeted approach for new oncological treatments. This article specifically looks at the biological role of aminopeptidases in both normal and cancer processes, and their potential as a biological target for future therapeutic strategies.