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1. Meta-Analysis of Gastrointestinal Adverse Events from Tyrosine Kinase Inhibitors for Chronic Myeloid Leukemia

   https://doi.org/10.3390/cancers13071643  

   Mohanavelu, Prahathishree; Mutnick, Mira; Mehra, Nidhi; White, Brandon; Kudrimoti, Sparsh; Hernandez Kluesner, Kaci; Chen, Xinyu; Nguyen, Tim; Horlander, Elaina; Thenot, Helena; et al (April 2021, Cancers)

   null (Ed.)

   Tyrosine kinase inhibitors (TKIs) are the frontline therapy for BCR-ABL (Ph+) chronic myeloid leukemia (CML). A systematic meta-analysis of 43 peer-reviewed studies with 10,769 CML patients compared the incidence of gastrointestinal adverse events (GI AEs) in a large heterogeneous CML population as a function of TKI type. Incidence and severity of nausea, vomiting, and diarrhea were assessed for imatinib, dasatinib, bosutinib, and nilotinib. Examination of combined TKI average GI AE incidence found diarrhea most prevalent (22.5%), followed by nausea (20.6%), and vomiting (12.9%). Other TKI GI AEs included constipation (9.2%), abdominal pain (7.6%), gastrointestinal hemorrhage (3.5%), and pancreatitis (2.2%). Mean GI AE incidence was significantly different between TKIs (p < 0.001): bosutinib (52.9%), imatinib (24.2%), dasatinib (20.4%), and nilotinib (9.1%). Diarrhea was the most prevalent GI AE with bosutinib (79.2%) and dasatinib (28.1%), whereas nausea was most prevalent with imatinib (33.0%) and nilotinib (13.2%). Incidence of grade 3 or 4 severe GI AEs was ≤3% except severe diarrhea with bosutinib (9.5%). Unsupervised clustering revealed treatment efficacy measured by the complete cytogenetic response, major molecular response, and overall survival is driven most by disease severity, not TKI type. For patients with chronic phase CML without resistance, optimal TKI selection should consider TKI AE profile, comorbidities, and lifestyle. 

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2. Hematological Adverse Events with Tyrosine Kinase Inhibitors for Chronic Myeloid Leukemia: A Systematic Review with Meta-Analysis

   https://doi.org/10.3390/cancers15174354  

   Kronick, Olivia; Chen, Xinyu; Mehra, Nidhi; Varmeziar, Armon; Fisher, Rachel; Kartchner, David; Kota, Vamsi; Mitchell, Cassie S. (September 2023, Cancers)

   Chronic myeloid leukemia (CML) is treated with tyrosine kinase inhibitors (TKI) that target the pathological BCR-ABL1 fusion oncogene. The objective of this statistical meta-analysis was to assess the prevalence of other hematological adverse events (AEs) that occur during or after predominantly first-line treatment with TKIs. Data from seventy peer-reviewed, published studies were included in the analysis. Hematological AEs were assessed as a function of TKI drug type (dasatinib, imatinib, bosutinib, nilotinib) and CML phase (chronic, accelerated, blast). AE prevalence aggregated across all severities and phases was significantly different between each TKI (p < 0.05) for anemia—dasatinib (54.5%), bosutinib (44.0%), imatinib (32.8%), nilotinib (11.2%); neutropenia—dasatinib (51.2%), imatinib (29.8%), bosutinib (14.1%), nilotinib (14.1%); thrombocytopenia—dasatinib (62.2%), imatinib (30.4%), bosutinib (35.3%), nilotinib (22.3%). AE prevalence aggregated across all severities and TKIs was significantly (p < 0.05) different between CML phases for anemia—chronic (28.4%), accelerated (66.9%), blast (55.8%); neutropenia—chronic (26.7%), accelerated (63.8%), blast (36.4%); thrombocytopenia—chronic (33.3%), accelerated (65.6%), blast (37.9%). An odds ratio (OR) with 95% confidence interval was used to compare hematological AE prevalence of each TKI compared to the most common first-line TKI therapy, imatinib. For anemia, dasatinib OR = 1.65, [1.51, 1.83]; bosutinib OR = 1.34, [1.16, 1.54]; nilotinib OR = 0.34, [0.30, 0.39]. For neutropenia, dasatinib OR = 1.72, [1.53, 1.92]; bosutinib OR = 0.47, [0.38, 0.58]; nilotinib OR = 0.47, [0.42, 0.54]. For thrombocytopenia, dasatinib OR = 2.04, [1.82, 2.30]; bosutinib OR = 1.16, [0.97, 1.39]; nilotinib OR = 0.73, [0.65, 0.82]. Nilotinib had the greatest fraction of severe (grade 3/4) hematological AEs (30%). In conclusion, the overall prevalence of hematological AEs by TKI type was: dasatinib > bosutinib > imatinib > nilotinib. Study limitations include inability to normalize for dosage and treatment duration. 

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3. Predictive nonlinear modeling of malignant myelopoiesis and tyrosine kinase inhibitor therapy

   https://doi.org/10.7554/eLife.84149  

   Rodriguez, Jonathan; Iniguez, Abdon; Jena, Nilamani; Tata, Prasanthi; Liu, Zhong-Ying; Lander, Arthur D; Lowengrub, John; Van Etten, Richard A (April 2023, eLife)

   Chronic myeloid leukemia (CML) is a blood cancer characterized by dysregulated production of maturing myeloid cells driven by the product of the Philadelphia chromosome, the BCR-ABL1 tyrosine kinase. Tyrosine kinase inhibitors (TKIs) have proved effective in treating CML, but there is still a cohort of patients who do not respond to TKI therapy even in the absence of mutations in the BCR-ABL1 kinase domain that mediate drug resistance. To discover novel strategies to improve TKI therapy in CML, we developed a nonlinear mathematical model of CML hematopoiesis that incorporates feedback control and lineage branching. Cell–cell interactions were constrained using an automated model selection method together with previous observations and new in vivo data from a chimericBCR-ABL1transgenic mouse model of CML. The resulting quantitative model captures the dynamics of normal and CML cells at various stages of the disease and exhibits variable responses to TKI treatment, consistent with those of CML patients. The model predicts that an increase in the proportion of CML stem cells in the bone marrow would decrease the tendency of the disease to respond to TKI therapy, in concordance with clinical data and confirmed experimentally in mice. The model further suggests that, under our assumed similarities between normal and leukemic cells, a key predictor of refractory response to TKI treatment is an increased maximum probability of self-renewal of normal hematopoietic stem cells. We use these insights to develop a clinical prognostic criterion to predict the efficacy of TKI treatment and design strategies to improve treatment response. The model predicts that stimulating the differentiation of leukemic stem cells while applying TKI therapy can significantly improve treatment outcomes. 

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4. Literature-Based Discovery Predicts Antihistamines Are a Promising Repurposed Adjuvant Therapy for Parkinson’s Disease

   https://doi.org/10.3390/ijms241512339  

   Tandra, Gabriella; Yoone, Amy; Mathew, Rhea; Wang, Minzhi; Hales, Chadwick M.; Mitchell, Cassie S. (August 2023, International Journal of Molecular Sciences)

   Parkinson’s disease (PD) is a movement disorder caused by a dopamine deficit in the brain. Current therapies primarily focus on dopamine modulators or replacements, such as levodopa. Although dopamine replacement can help alleviate PD symptoms, therapies targeting the underlying neurodegenerative process are limited. The study objective was to use artificial intelligence to rank the most promising repurposed drug candidates for PD. Natural language processing (NLP) techniques were used to extract text relationships from 33+ million biomedical journal articles from PubMed and map relationships between genes, proteins, drugs, diseases, etc., into a knowledge graph. Cross-domain text mining, hub network analysis, and unsupervised learning rank aggregation were performed in SemNet 2.0 to predict the most relevant drug candidates to levodopa and PD using relevance-based HeteSim scores. The top predicted adjuvant PD therapies included ebastine, an antihistamine for perennial allergic rhinitis; levocetirizine, another antihistamine; vancomycin, a powerful antibiotic; captopril, an angiotensin-converting enzyme (ACE) inhibitor; and neramexane, an N-methyl-D-aspartate (NMDA) receptor agonist. Cross-domain text mining predicted that antihistamines exhibit the capacity to synergistically alleviate Parkinsonian symptoms when used with dopamine modulators like levodopa or levodopa–carbidopa. The relationship patterns among the identified adjuvant candidates suggest that the likely therapeutic mechanism(s) of action of antihistamines for combatting the multi-factorial PD pathology include counteracting oxidative stress, amending the balance of neurotransmitters, and decreasing the proliferation of inflammatory mediators. Finally, cross-domain text mining interestingly predicted a strong relationship between PD and liver disease. 

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5. Future Trends in Semiconducting Gas-Selective Sensing Probes for Skin Diagnostics

   https://doi.org/10.3390/s21227554  

   Annerino, Anthony; Gouma, Pelagia-Irene (November 2021, Sensors)

   This paper presents sensor nanotechnologies that can be used for the skin-based gas “smelling” of disease. Skin testing may provide rapid and reliable results, using specific “fingerprints” or unique patterns for a variety of diseases and conditions. These can include metabolic diseases, such as diabetes and cholesterol-induced heart disease; neurological diseases, such as Alzheimer’s and Parkinson’s; quality of life conditions, such as obesity and sleep apnea; pulmonary diseases, such as cystic fibrosis, asthma, and chronic obstructive pulmonary disease; gastrointestinal tract diseases, such as irritable bowel syndrome and colitis; cancers, such as breast, lung, pancreatic, and colon cancers; infectious diseases, such as the flu and COVID-19; as well as diseases commonly found in ICU patients, such as urinary tract infections, pneumonia, and infections of the blood stream. Focusing on the most common gaseous biomarkers in breath and skin, which is nitric oxide and carbon monoxide, and certain abundant volatile organic compounds (acetone, isoprene, ammonia, alcohols, sulfides), it is argued here that effective discrimination between the diseases mentioned above is possible, by capturing the relative sensor output signals from the detection of each of these biomarkers and identifying the distinct breath print for each disease. 

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