Personalized medicine最新文献

Organoids are three-dimensional, self-organizing cell structures grown from human biospecimens that allow researchers to study development, disease, and drug responses. Organoid technology holds promise for precision medicine, as it can tailor therapies to specific individuals. Including diverse groups within organoid research is essential to collect representative data for the development of treatments for all populations and to reduce health disparities. Commercial parties are increasingly involved in organoid research. The involvement of such parties can negatively affect the ways in which underrepresented groups are included and recruited and can affect their willingness to donate their biospecimen. In this paper, we argue that commercial involvement in organoid research poses three problems that can hinder the equal representation of groups or the equitable access to treatments derived from organoid research. First, commercially driven organoid research presents challenges to the informed consent process. Second, commercial involvement can undermine trust among underrepresented groups and reduce their willingness to donate biospecimens. Third, benefit sharing becomes ethically more complex when profits are generated and underrepresented groups are involved. Therefore, researchers and commercial parties should actively address these challenges by (re)establishing trust, using transparent and inclusive communication, ensuring ongoing reciprocity, and uphold shared responsibility.

Background: Pharmacogenomics (PGx) examines how genetic variations influence individual responses to medications, enabling more precise drug and dose selection. Drug labeling communicates PGx information to healthcare providers. However, in many countries, including Jordan, PGx integration into clinical practice remains limited.

Objective: This study aimed to evaluate the availability of PGx labeling in medications approved by the Jordan Food and Drug Administration (JFDA). It also compared PGx labeling in Jordan with that in drug labels from the United States and Hungary.

Methods: A manual review of drug leaflets was conducted using the JFDA online database between July and September 2024. Drugs were categorized based on the presence or absence of PGx information. Data were then compared with the U.S. FDA's PGx Biomarker Table and the Hungarian National Institute of Pharmacy's SmPCs.

Results: Among 75 reviewed JFDA-approved drugs, only 15 (20%) included complete PGx information. Neurology (50%), psychiatry (26.7%), and oncology (25%) had the highest representation, while cardiology (10%) and urology (0%) were underrepresented. Compared to the USA and Hungary, PGx labeling in Jordan was markedly limited.

Conclusion: The findings show a significant gap in PGx labeling in Jordan, emphasizing the need for regulatory updates to support personalized medicine.

Background: Validate a novel in vitro resistance platform for breast cancer (BC) by assessing resistance profiles of treatment-naïve and residual tumors after neoadjuvant chemotherapy (NACT) and applying a machine learning algorithm to predict NACT response using clinical biomarkers.

Methods: Tumor cells from primary BC and residual disease (RD) were cultured on the chemoresistance platform with various chemotherapies. Resistance was categorized as low ( < 40%), medium (40-60%), or high ( > 60%) after 72 h based on cell viability. Clinicopathological data from BC samples were analyzed using the XGBoost algorithm and SHAP interpretation to identify NACT-resistant patients.

Results: Patients undergoing upfront surgery (n = 70) exhibited significantly favorable prognosis compared to RD cases (n = 27), which had higher drug resistance and worse outcomes. AI analysis of 1,012 patients achieved 82% accuracy in predicting pathological response and RD, with age, estrogen receptor status, tumor grade and size, axillary status, and HER2 status identified as key predictors. The algorithm predicted NACT resistance with 81.8% accuracy in 11 patient samples.

Conclusion: The chemoresistance platform identified resistance patterns highlighting its utility in precision medicine. Additionally, the XGBoost algorithm accurately predicted NACT response, supporting the integration of AI with functional precision medicine for personalized BC treatment.

Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) has become increasingly utilized in the treatment of appendiceal adenocarcinoma (AA) with peritoneal metastases. There are multiple intraperitoneal chemotherapeutic agents and protocols used at different centers, however there is little data available to guide clinicians on the optimal treatment strategy for individual patients. While it is often treated with paradigms extrapolated from colorectal cancer, AA has been shown to have a distinct mutational profile. Commonly mutated genes in AA such as KRAS and GNAS have been targeted by recently described systemic therapies for various tumors with positive results, suggesting that there may be a role for a patient-centered approach to HIPEC as well. Data specific to AA remains limited, however ongoing research into novel strategies such as next-generation sequencing of tumor samples and in vitro testing of patient-derived organoids for a variety of gastrointestinal cancers with peritoneal metastases has shown promise in personalizingHIPEC regimens.

Background: Personalized medicine (PM) is advancing disease prevention and treatment, but regulatory and clinical concerns persist, requiring evaluation of healthcare professionals' (HPs) knowledge and attitudes.

Methods: His study assessed PM awareness among HPs at Tabriz University of Medical Sciences, Iran. Participants from diverse clinical departments completed a survey covering PM definitions, benefits, ethical concerns, genetic testing knowledge, attitudes, and barriers. A literature review guided question development.

Results: Among 141 HPs (55.3% male, 44.7% female), only 27.7% reported sufficient PM knowledge, though 82.3% acknowledged genetic health influences. Those with adequate knowledge more often endorsed PM tools (92.3% vs. 68.6%, p = 0.01) but expressed greater concern about healthcare disparities (82.1% vs. 67.6%, p = 0.03). Key barriers included cost (17%) and ethical risks, with 72% fearing PM would widen economic gaps and 23.4% anticipating insurance discrimination. Females and married HPs were more concerned about discrimination (p = 0.039 and p = 0.038, respectively). Despite concerns, 80% of physicians supported genome-guided prescribing.

Conclusion: While HPs recognize PM's potential, limited awareness and ethical concerns hinder adoption. Addressing knowledge gaps and equity issues through education is crucial for PM integration in Iran.

Chronic lymphocytic leukemia (CLL) is a common, incurable leukemia. Precision treatment for CLL uses genetic testing to align therapeutic selection with patient characteristics. Insurers are uneven in their reimbursement of precision CLL treatment, partly due to uncertain evidence of cost-effectiveness. This review surveys the current cost-effectiveness evidence for precision CLL treatment and identifies areas for future research. We conducted a scoping review of economic evaluations of precision CLL treatments indexed in PubMed, Embase, and Web of Science and published by October 2024. Eight articles were retrieved. Studies examined heterogeneous patient populations, treatment regimens, and stratification strategies. Four studies (50%) focused on subgroups with del(17p) and/or TP53 mutations only. Three studies (38%) analyzed the costs and outcomes of both treatment and genetic testing, while 62% did not include the cost or outcomes of genetic testing. All studies obtained clinical model parameters from published trials. Five studies (63%) reported that precision CLL treatment was likely cost-effective at willingness to pay thresholds ranging from $26,489/QALY to $130,477/QALY. Future research should focus on generating real-world data, broadening the scope of analysis to include societal perspectives, and exploring distributional impacts to more effectively address the heterogeneity of precision CLL treatments when determining their cost-effectiveness.

Aim: On-aspirin platelet reactivity, wherein patients show sub-optimal or no response to antiplatelet therapy, occurs in 5-60% of subjects. The genetic etiology of such reactivity in patients with vascular diseases, especially ischemic stroke in the Indian population, is unknown. This study aimed to examine the genetic variations in the pathways of platelet aggregation and aspirin metabolism that could predict aspirin response.

Methods: This is a prospective cohort study, which included 293 ischemic stroke patients on 150 mg aspirin for over 7 days. Platelet aggregation was assessed using light transmission aggregometry with 10 µM ADP and 0.5 mM arachidonic acid as agonist. After excluding patients with serum salicylic acid levels < 30 µg/mL, 230 individuals were analyzed. Candidate gene variants in COX1, COX2, GpIIb/IIIa, P2RY1, PEAR1, ITGB3, and UGT1A6, were genotyped using PCR-RFLP or allelic discrimination assays.

Results: The T allele of P2RY1 (rs1371097 C > T) was significantly associated with inadequate platelet response with an odds ratio of 1.71 (95% CI: 1.122-2.61; p = 0.0131). Carriers of this allele had a 3.46-fold increased risk of inadequate response after adjustment for age and gender.

Conclusions: The P2RY1 (rs1371097 C > T) variant may be a potential genetic marker for inadequate response to aspirin in Indian ischemic stroke patients.

The severity of COVID-19 disease can vary greatly, influenced by genetic factors and comorbid conditions that may increase mortality. This study has examined potential genetic influences on the disease for a young adult aged 36 years with T2DM-CAD multi-morbidity with severe COVID-19 disease and in-hospital mortality using whole-exome sequencing. The patient exhibited a constellation of severe symptoms and abnormality in several biochemical markers associated with COVID-19 disease and comorbid conditions. A total of 756 variants were discovered in the patient, including several rare and novel variants associated with immune pathways. A set of 10 unique candidate variants in 10 distinct genes were identified with nine variants located within genes associated with the COVID-19 panel (HLA-DRB1, IL23R, PRKDC, RNF31, SLC37A4, TAP2, TCIRG1, TCN2, and TPP2), while one variant was found in a gene (PAX6) from Diabetes panel. Enrichment analysis showed that the top three enriched GO biological processes were a response to stimulus (n = 23, p = 6.8E-3), immune system process (n = 22, p = 3.6E-12), and regulation of immune system process (n = 19, p = 1.57E-11). The Maximal Clique Centrality algorithm identified HLA-DRB1 as a prominent hub gene and potential loss-of-function mutation in HLA-DRB1, suggests a compromised antigen presentation mechanism within this patient.

Understanding the regional differences in approved gene therapies, clinical trial development, and regulatory frameworks is crucial for ensuring equitable access and addressing justice issues in advanced therapeutics. This review aimed to evaluate the differences between the US, the EU, Japan, and China and offer policy recommendations to promote harmonization between these countries and regions. Gene therapy approvals show significant regional disparities, with the US leading with 23 approved therapies, followed by the EU with 16. Few products are accessible worldwide reflecting challenges in obtaining cross-border approvals. Moreover, access is uneven within regions like the EU, with high-income countries having better accessibility. High costs and complex reimbursement processes exacerbate these issues, with some products being withdrawn from the market due to pricing disputes. Regulatory differences, such as differing data needs, further delay access in countries, like Japan, where gene therapy products are unavailable until years after a product is ready for approval. Clinical trial activity mirrors these disparities, with China's growing number of trials potentially reshaping the landscape. Harmonizing regulations across regions could streamline the approval process for therapies, making them more efficient and reducing disparities. Furthermore, key solutions include incentivizing cost reductions, adopting innovative payment models, and aligning evidence/reimbursement requirements.