Advances in personalized radiotherapy.

Radiotherapy is a mainstay of cancer treatment. The clinical response to radiotherapy is heterogeneous, from a complete response to early progression. Recent studies have explored the importance of patient characteristics in response to radiotherapy. In this editorial, we invite contributions for a BMC Cancer collection of articles titled 'Advances in personalized radiotherapy' towards the improvement of treatment response.

Tribulations and future opportunities for artificial intelligence in precision medicine.

Upon a diagnosis, the clinical team faces two main questions: what treatment, and at what dose? Clinical trials' results provide the basis for guidance and support for official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate the reported response from relevant clinical trials. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual's response to the treatment varies with the changes in their condition. In practice, the drug and the dose selection depend significantly on the medical protocol and the medical team's experience. As such, the results are inherently varied and often suboptimal. Big data and Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit their application. AI is a rapidly evolving and dynamic field with the potential to revolutionize various aspects of human life. AI has become increasingly crucial in drug discovery and development. AI enhances decision-making across different disciplines, such as medicinal chemistry, molecular and cell biology, pharmacology, pathology, and clinical practice. In addition to these, AI contributes to patient population selection and stratification. The need for AI in healthcare is evident as it aids in enhancing data accuracy and ensuring the quality care necessary for effective patient treatment. AI is pivotal in improving success rates in clinical practice. The increasing significance of AI in drug discovery, development, and clinical trials is underscored by many scientific publications. Despite the numerous advantages of AI, such as enhancing and advancing Precision Medicine (PM) and remote patient monitoring, unlocking its full potential in healthcare requires addressing fundamental concerns. These concerns include data quality, the lack of well-annotated large datasets, data privacy and safety issues, biases in AI algorithms, legal and ethical challenges, and obstacles related to cost and implementation. Nevertheless, integrating AI in clinical medicine will improve diagnostic accuracy and treatment outcomes, contribute to more efficient healthcare delivery, reduce costs, and facilitate better patient experiences, making healthcare more sustainable. This article reviews AI applications in drug development and clinical practice, making healthcare more sustainable, and highlights concerns and limitations in applying AI.

Precise execution of personalized surgical planning using three-dimensional printed guide template in severe and complex adult spinal deformity patients requiring three-column osteotomy: a retrospective, comparative matched-cohort study.

BACKGROUND: The surgical treatment of severe and complex adult spinal deformity (ASD) commonly required three-column osteotomy (3-CO), which was technically demanding with high risk of neurological deficit. Personalized three dimensional (3D)-printed guide template based on preoperative planning has been gradually applied in 3-CO procedure. The purpose of this study was to compare the efficacy, safety, and precision of 3D-printed osteotomy guide template and free-hand technique in the treatment of severe and complex ASD patients requiring 3-CO. METHODS: This was a single-centre retrospective comparative cohort study of patients with severe and complex ASD (Cobb angle of scoliosis > 80° with flexibility < 25% or focal kyphosis > 90°) who underwent posterior spinal fusion and 3-CO between January 2020 to January 2023, with a minimum 12 months follow-up. Personalized computer-assisted three-dimensional osteotomy simulation was performed for all recruited patients, who were further divided into template and non-template groups based on the application of 3D-printed osteotomy guide template according to the surgical planning. Patients in the two groups were age- and gender- propensity-matched. The radiographic parameters, postoperative neurological deficit, and precision of osteotomy execution were compared between groups. RESULTS: A total of 40 patients (age 36.53 ± 11.98 years) were retrospectively recruited, with 20 patients in each group. The preoperative focal kyphosis (FK) was 92.72° ± 36.77° in the template group and 93.47° ± 33.91° in the non-template group, with a main curve Cobb angle of 63.35° (15.00°, 92.25°) and 64.00° (20.25°, 99.20°), respectively. Following the correction surgery, there were no significant differences in postoperative FK, postoperative main curve Cobb angle, correction rate of FK (54.20% vs. 51.94%, P = 0.738), and correction rate of main curve Cobb angle (72.41% vs. 61.33%, P = 0.101) between the groups. However, the match ratio of execution to simulation osteotomy angle was significantly greater in the template group than the non-template group (coronal: 89.90% vs. 74.50%, P < 0.001; sagittal: 90.45% vs. 80.35%, P < 0.001). The operating time (ORT) was significantly shorter (359.25 ± 57.79 min vs. 398.90 ± 59.48 min, P = 0.039) and the incidence of postoperative neurological deficit (5.0% vs. 35.0%, P = 0.018) was significantly lower in the template group than the non-template group. CONCLUSION: Performing 3-CO with the assistance of personalized 3D-printed guide template could increase the precision of execution, decrease the risk of postoperative neurological deficit, and shorten the ORT in the correction surgery for severe and complex ASD. The personalized osteotomy guide had the advantages of 3D insight of the case-specific anatomy, identification of osteotomy location, and translation of the surgical planning or simulation to the real surgical site.

The Stress Phenotyping Framework: A multidisciplinary biobehavioral approach for assessing and therapeutically targeting maladaptive stress physiology.

Although dysregulated stress biology is becoming increasingly recognized as a key driver of lifelong disparities in chronic disease, we presently have no validated biomarkers of toxic stress physiology; no biological, behavioral, or cognitive treatments specifically focused on normalizing toxic stress processes; and no agreed-upon guidelines for treating stress in the clinic or evaluating the efficacy of interventions that seek to reduce toxic stress and improve human functioning. We address these critical issues by (a) systematically describing key systems and mechanisms that are dysregulated by stress; (b) summarizing indicators, biomarkers, and instruments for assessing stress response systems; and (c) highlighting therapeutic approaches that can be used to normalize stress-related biopsychosocial functioning. We also present a novel multidisciplinary Stress Phenotyping Framework that can bring stress researchers and clinicians one step closer to realizing the goal of using precision medicine-based approaches to prevent and treat stress-associated health problems.

Personalized Timing for Allogeneic Stem-Cell Transplantation in Hematologic Neoplasms: A Target Trial Emulation Approach Using Multistate Modeling and Microsimulation.

PURPOSE: Decision about the optimal timing of a treatment procedure in patients with hematologic neoplasms is critical, especially for cellular therapies (most including allogeneic hematopoietic stem-cell transplantation [HSCT]). In the absence of evidence from randomized trials, real-world observational data become beneficial to study the effect of the treatment timing. In this study, a framework to estimate the expected outcome after an intervention in a time-to-event scenario is developed, with the aim of optimizing the timing in a personalized manner. METHODS: Retrospective real-world data are leveraged to emulate a target trial for treatment timing using multistate modeling and microsimulation. This case study focuses on myelodysplastic syndromes, serving as a prototype for rare cancers characterized by a heterogeneous clinical course and complex genomic background. A cohort of 7,118 patients treated according to conventional available treatments/evidence across Europe and United States is analyzed. The primary clinical objective is to determine the ideal timing for HSCT, the only curative option for these patients. RESULTS: This analysis enabled us to identify the most appropriate time frames for HSCT on the basis of each patient's unique profile, defined by a combination relevant patients' characteristics. CONCLUSION: The developed methodology offers a structured framework to address a relevant clinical issue in the field of hematology. It makes several valuable contributions: (1) novel insights into how to develop decision models to identify the most favorable HSCT timing, (2) evidence to inform clinical decisions in a real-world context, and (3) the incorporation of complex information into decision making. This framework can be applied to provide medical insights for clinical issues that cannot be adequately addressed through randomized clinical trials.

Harnessing polyelectrolyte complexes for precision cancer targeting: a comprehensive review.

Polyelectrolytes represent a unique class of polymers abundant in ionizable functional groups. In a solution, ionized polyelectrolytes can intricately bond with oppositely charged counterparts, giving rise to a fascinating phenomenon known as a polyelectrolyte complex. These complexes arise from the interaction between oppositely charged entities, such as polymers, drugs, and combinations thereof. The polyelectrolyte complexes are highly appealing in cancer management, play an indispensable role in chemotherapy, crafting biodegradable, biocompatible 3D membranes, microcapsules, and nano-sized formulations. These versatile complexes are pivotal in designing controlled and targeted release drug delivery systems. The present review emphasizes on classification of polyelectrolyte complex along with their formation mechanisms. This review comprehensively explores the applications of polyelectrolyte complex, highlighting their efficacy in targeted drug delivery strategies for combating different forms of cancer. The innovative use of polyelectrolyte complex presents a potential breakthrough in cancer therapeutics, demonstrating their role in enhancing treatment precision and effectiveness.

The combination of breast cancer PDO and mini-PDX platform for drug screening and individualized treatment.

The majority of advanced breast cancers exhibit strong aggressiveness, heterogeneity, and drug resistance, and currently, the lack of effective treatment strategies is one of the main challenges that cancer research must face. Therefore, developing a feasible preclinical model to explore tailored treatments for refractory breast cancer is urgently needed. We established organoid biobanks from 17 patients with breast cancer and characterized them by immunohistochemistry (IHC) and next generation sequencing (NGS). In addition, we in the first combination of patient-derived organoids (PDOs) with mini-patient-derived xenografts (Mini-PDXs) for the rapid and precise screening of drug sensitivity. We confirmed that breast cancer organoids are a high-fidelity three-dimension (3D) model in vitro that recapitulates the original tumour's histological and genetic features. In addition, for a heavily pretreated patient with advanced drug-resistant breast cancer, we combined PDO and Mini-PDX models to identify potentially effective combinations of therapeutic agents for this patient who were alpelisib + fulvestrant. In the drug sensitivity experiment of organoids, we observed changes in the PI3K/AKT/mTOR signalling axis and oestrogen receptor (ER) protein expression levels, which further verified the reliability of the screening results. Our study demonstrates that the PDO combined with mini-PDX model offers a rapid and precise drug screening platform that holds promise for personalized medicine, improving patient outcomes and addressing the urgent need for effective therapies in advanced breast cancer.

Addressing Social Determinants in the Era of Precision Medicine in Breast Cancer: Is It Sufficient to Reduce Disparities?

The Oncotype DX (ODX) assay predicts recurrence risk and demonstrates the benefits of adjuvant therapy in patients with early-stage, hormone receptor (HR)-positive/HER2-negative breast cancer. ODX uptake varies by patients' racial/ethnic backgrounds and socioeconomic status (SES). However, community-level variability remains unknown, and research regarding the association between testing status and receipt of adjuvant chemotherapy is limited. To fill these knowledge gaps, Van Alsten and colleagues found a 6% lower prevalence of ODX uptake among patients residing in high SES-deprived areas than among those residing in low SES-deprived areas. Among patients with low and median ODX recurrence scores, those who underwent testing were 28% and 21% less likely to receive adjuvant chemotherapy than those who did not, respectively. The findings emphasize the role of social determinants of health. However, to further reduce or eliminate racial/ethnic disparities and SES inequities, we would need sufficient and effective multi-level approaches. These involve lower ODX testing costs, health insurance coverage expansion, re-classification and validation of ODX recurrence scores in patients of minority ancestry, and the development of a faster, more accurate, and affordable test. See related article by Van Alsten et al., p. 654.

Personalized mechanical ventilation guided by ultrasound in patients with acute respiratory distress syndrome (PEGASUS): study protocol for an international randomized clinical trial.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a frequent cause of hypoxemic respiratory failure with a mortality rate of approximately 30%. Identifying ARDS subphenotypes based on "focal" or "non-focal" lung morphology has the potential to better target mechanical ventilation strategies of individual patients. However, classifying morphology through chest radiography or computed tomography is either inaccurate or impractical. Lung ultrasound (LUS) is a non-invasive bedside tool that can accurately distinguish "focal" from "non-focal" lung morphology. We hypothesize that LUS-guided personalized mechanical ventilation in ARDS patients leads to a reduction in 90-day mortality compared to conventional mechanical ventilation. METHODS: The Personalized Mechanical Ventilation Guided by UltraSound in Patients with Acute Respiratory Distress Syndrome (PEGASUS) study is an investigator-initiated, international, randomized clinical trial (RCT) that plans to enroll 538 invasively ventilated adult intensive care unit (ICU) patients with moderate to severe ARDS. Eligible patients will receive a LUS exam to classify lung morphology as "focal" or "non-focal". Thereafter, patients will be randomized within 12 h after ARDS diagnosis to receive standard care or personalized ventilation where the ventilation strategy is adjusted to the morphology subphenotype, i.e., higher positive end-expiratory pressure (PEEP) and recruitment maneuvers for "non-focal" ARDS and lower PEEP and prone positioning for "focal" ARDS. The primary endpoint is all-cause mortality at day 90. Secondary outcomes are mortality at day 28, ventilator-free days at day 28, ICU length of stay, ICU mortality, hospital length of stay, hospital mortality, and number of complications (ventilator-associated pneumonia, pneumothorax, and need for rescue therapy). After a pilot phase of 80 patients, the correct interpretation of LUS images and correct application of the intervention within the safe limits of mechanical ventilation will be evaluated. DISCUSSION: PEGASUS is the first RCT that compares LUS-guided personalized mechanical ventilation with conventional ventilation in invasively ventilated patients with moderate and severe ARDS. If this study demonstrates that personalized ventilation guided by LUS can improve the outcomes of ARDS patients, it has the potential to shift the existing one-size-fits-all ventilation strategy towards a more individualized approach. TRIAL REGISTRATION: The PEGASUS trial was registered before the inclusion of the first patient, https://clinicaltrials.gov/ (ID: NCT05492344).

It provides families with other avenues for treatment when there are no other options Surgeons' perspectives of being part of a precision medicine trial for poor prognosis paediatric cancer patients: A short report.

OBJECTIVE: Precision medicine is transforming cancer treatment, yet the perspectives of surgeons who often play a critical role in the delivery of precision medicine remain understudied. METHODS: We conducted semi-structured interviews with 13 surgeons involved in a precision medicine trial for children with poor prognosis cancer. We explored knowledge of genetics, confidence with somatic and germline results, ratings of benefit to stakeholders and willingness to undertake surgical procedures. RESULTS: Surgeons generally had positive attitudes towards precision medicine but expressed concerns about families' unrealistic expectations, mixed opinions on the benefits and the use of research-only biopsies. Most surgeons rated their genetics knowledge as 'good' (69%) and felt 'very confident' in identifying genetic specialists (66%), but 'not confident' (66.6%) in making treatment recommendations. Surgeons' willingness to undertake a procedure was influenced by potential patient benefit. CONCLUSIONS: Our findings support the need for more workforce and training support for surgeons to fully engage with precision medicine.

Can Machine Learning Personalize Cardiovascular Therapy in Sepsis?

Large randomized trials in sepsis have generally failed to find effective novel treatments. This is increasingly attributed to patient heterogeneity, including heterogeneous cardiovascular changes in septic shock. We discuss the potential for machine learning systems to personalize cardiovascular resuscitation in sepsis. While the literature is replete with proofs of concept, the technological readiness of current systems is low, with a paucity of clinical trials and proven patient benefit. Systems may be vulnerable to confounding and poor generalization to new patient populations or contemporary patterns of care. Typical electronic health records do not capture rich enough data, at sufficient temporal resolution, to produce systems that make actionable treatment suggestions. To resolve these issues, we recommend a simultaneous focus on technical challenges and removing barriers to translation. This will involve improving data quality, adopting causally grounded models, prioritizing safety assessment and integration into healthcare workflows, conducting randomized clinical trials and aligning with regulatory requirements.

The French multicentric molecular analysis platforms and personalized medicine trials MOST, MOST Plus and MEGAMOST.

BACKGROUND AND PURPOSE: In this manuscript we describe the academic French multicentric molecular analysis platforms including PROFILER, promoted by Centre Léon Berard, and the multicentric personalized medicine trials MOST, MOST Plus and MEGAMOST. PATIENTS/MATERIAL AND METHODS: MOST, MOST Plus and MEGAMOST comprise 14 cohorts with different targeted agents and immunotherapies. RESULTS AND INTERPRETATION: PROFILER has recruited 5,991 patients in 10 years, MOST and MOST Plus 875 patients since 2014 and MEGAMOST 172 patients since 2020, and are still ongoing. We provide a description of the local, national and international implications of these initiatives, and we review the results of the sorafenib and olaparib cohorts.

Towards personalized medicine: a scoping review of immunotherapy in sepsis.

Despite significant progress in our understanding of the pathophysiology of sepsis and extensive clinical research, there are few proven therapies addressing the underlying immune dysregulation of this life-threatening condition. The aim of this scoping review is to describe the literature evaluating immunotherapy in adult patients with sepsis, emphasizing on methods providing a "personalized immunotherapy" approach, which was defined as the classification of patients into a distinct subgroup or subphenotype, in which a patient's immune profile is used to guide treatment. Subgroups are subsets of sepsis patients, based on any cut-off in a variable. Subphenotypes are subgroups that can be reliably discriminated from other subgroup based on data-driven assessments. Included studies were randomized controlled trials and cohort studies investigating immunomodulatory therapies in adults with sepsis. Studies were identified by searching PubMed, Embase, Cochrane CENTRAL and ClinicalTrials.gov, from the first paper available until January 29th, 2024. The search resulted in 15,853 studies. Title and abstract screening resulted in 1409 studies (9%), assessed for eligibility; 771 studies were included, of which 282 (37%) were observational and 489 (63%) interventional. Treatment groups included were treatments targeting the innate immune response, the complement system, coagulation and endothelial dysfunction, non-pharmalogical treatment, pleiotropic drugs, immunonutrition, concomitant treatments, Traditional Chinese Medicine, immunostimulatory cytokines and growth factors, intravenous immunoglobulins, mesenchymal stem cells and immune-checkpoint inhibitors. A personalized approach was incorporated in 70 studies (9%). Enrichment was applied using cut-offs in temperature, laboratory, biomarker or genetic variables. Trials often showed conflicting results, possibly due to the lack of patient stratification or the potential influence of severity and timing on immunomodulatory therapy results. When a personalized approach was applied, trends of clinical benefit for several interventions emerged, which hold promise for future clinical trials using personalized immunotherapy.

State-of-the-Art Advancements in Gastroesophageal Cancer Treatment: Harnessing Biomarkers for Precision Care.

Gastroesophageal cancers (GECs) represent a significant clinical challenge. For early resectable GEC, the integration of immune checkpoint inhibitors into the perioperative chemotherapy and chemoradiation treatment paradigms are being explored and showing promising results. Frontline management of metastatic GEC is exploring the role of targeted therapies beyond PD-1 inhibitors, including anti-human epidermal growth factor receptor 2 agents, Claudin 18.2 inhibitors, and FGFR2 inhibitors, which have shown considerable efficacy in recent trials. Looking ahead, ongoing trials and emerging technologies such as bispecific antibodies, antibody-drug conjugates, and adoptive cell therapies like chimeric antigen receptor T cells are expected to define the future of GEC management. These advancements signify a paradigm shift toward personalized and immunotherapy-based approaches, offering the potential for improved outcomes and reduced toxicity for patients with GEC.

Personalized Intervention Based on Early Detection of Atherosclerosis: JACC State-of-the-Art Review.

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide and challenges the capacity of health care systems globally. Atherosclerosis is the underlying pathophysiological entity in two-thirds of patients with CVD. When considering that atherosclerosis develops over decades, there is potentially great opportunity for prevention of associated events such as myocardial infarction and stroke. Subclinical atherosclerosis has been identified in its early stages in young individuals; however, there is no consensus on how to prevent progression to symptomatic disease. Given the growing burden of CVD, a paradigm shift is required-moving from late management of atherosclerotic CVD to earlier detection during the subclinical phase with the goal of potential cure or prevention of events. Studies must focus on how precision medicine using imaging and circulating biomarkers may identify atherosclerosis earlier and determine whether such a paradigm shift would lead to overall cost savings for global health.

Pharmacogenomics in Lebanon: current status, challenges and opportunities.

Pharmacogenomics (PGx) research and applications are of utmost relevance in Lebanon considering its population genetic diversity. Moreover, as a country with regional leadership in medicine and higher education, Lebanon holds a strong potential in contributing to PGx research and clinical implementation. In this manuscript, we first review and evaluate the available PGx research conducted in Lebanon, then describe the current status of PGx practice in Lebanon while reflecting on the local and regional challenges, and highlighting areas for action, and opportunities to move forward. We specifically expand on the status of PGx at the American University of Beirut Faculty of Medicine and Medical Center as a case study and guide for the further development of local and regional comprehensive PGx research, teaching, and clinical implementation programs. We also delve into the status of PGx knowledge and education, and prospects for further advancement such as with online courses and certificates.

Advancing Prostate Cancer Care: Treatment Approaches to Precision Medicine, Biomarker Innovations, and Equitable Access.

Genetic testing and molecular imaging have great promise in the accurate diagnosis and treatment of #prostate #cancer, but only if they can be developed and implemented to achieve equitable benefit for all men.