Precision cancer medicine: Concepts, current practice, and future developments

Overcoming barriers to advanced biomolecular technologies that inform treatment of solid tumors: a roadmap to access

The advent of advanced biomolecular technologies for detecting molecular and genomic signatures of individual tumors has transformed oncology care, introducing proven methodologies that can inform treatment with matched targeted therapies and predict response at the individual patient level. However, access to these technologies has been hampered by multiple barriers, most notably price and obtainability. Other barriers include lack of knowledge of available technologies, concerns about value, and outdated infrastructures that impede critical operations within the clinic or laboratory. Accessibility barriers to advanced biomolecular testing are critically important to patient care, as new technological advances in molecular medicine continue to outpace the implementation of solutions. Given the proven evidence for improved patient outcomes with precision oncology medicines, it is imperative to understand the value afforded by these technologies. The purpose of this narrative review is to describe existing and emerging barriers to access and present a "roadmap to access" that will facilitate the urgently needed discussions to identify solutions for improving access. Implementation of these solutions will raise awareness of available technologies and treatments and their prognostic significance, improve evidence collection for demonstration of value, and fortify clinical and laboratory infrastructure and operations.

Machine learning for modeling and identifying risk factors of pancreatic fistula

BACKGROUND

Pancreatic fistula is the most common complication of pancreatic surgeries that causes more serious conditions, including bleeding due to visceral vessel erosion and peritonitis.

AIM

To develop a machine learning (ML) model for postoperative pancreatic fistula and identify significant risk factors of the complication.

METHODS

A single-center retrospective clinical study was conducted which included 150 patients, who underwent pancreatoduodenectomy. Logistic regression, random forest, and CatBoost were employed for modeling the biochemical leak (symptomless fistula) and fistula grade B/C (clinically significant complication). The performance was estimated by receiver operating characteristic (ROC) area under the curve (AUC) after 5-fold cross-validation (20% testing and 80% training data). The risk factors were evaluated with the most accurate algorithm, based on the parameter "Importance" (Im), and Kendall correlation, P < 0.05.

RESULTS

The CatBoost algorithm was the most accurate with an AUC of 74%-86%. The study provided results of ML-based modeling and algorithm selection for pancreatic fistula prediction and risk factor evaluation. From 14 parameters we selected the main pre- and intraoperative prognostic factors of all the fistulas: Tumor vascular invasion (Im = 24.8%), age (Im = 18.6%), and body mass index (Im = 16.4%), AUC = 74%. The ML model showed that biochemical leak, blood and drain amylase level (Im = 21.6% and 16.4%), and blood leukocytes (Im = 11.2%) were crucial predictors for subsequent fistula B/C, AUC = 86%. Surgical techniques, morphology, and pancreatic duct diameter less than 3 mm were insignificant (Im < 5% and no correlations detected). The results were confirmed by correlation analysis.

CONCLUSION

This study highlights the key predictors of postoperative pancreatic fistula and establishes a robust ML-based model for individualized risk prediction. These findings contribute to the advancement of personalized perioperative care and may guide targeted preventive strategies.

Translating the Post-Mortem Brain Multi-Omics Molecular Taxonomy of Alzheimer's Dementia to Living Humans

Alzheimer's disease (AD) dementia is characterized by significant molecular and phenotypic heterogeneity, which confounds its mechanistic understanding, diagnosis, and effective treatment. In this study, we harness the most comprehensive dataset of paired ante-mortem blood omics, clinical, psychological, and post-mortem brain multi-omics data and neuroimaging to extensively characterize and translate the molecular taxonomy of AD dementia to living individuals. First, utilizing a comprehensive integration of eight complementary molecular layers from brain multi-omics data (N = 1,189), we identified three distinct molecular AD dementia subtypes exhibiting strong associations with cognitive decline, sex, psychological traits, brain morphology, and characterized by specific cellular and molecular drivers involving immune, vascular, and oligodendrocyte precursor cells. Next, in a significant translational effort, we developed predictive models to convert these advanced brain-derived molecular profiles (AD dementia pseudotimes and subtypes) into blood-, MRI- and psychological traits-based markers. The translation results underscore both the promise of these models and the opportunities for further enhancement. Our findings enhance the understanding of AD heterogeneity, underscore the value of multi-scale molecular approaches for elucidating causal mechanisms, and lay the groundwork for the development of novel therapies in living persons that target multi-level brain molecular subtypes of AD dementia.

Digital Health Technologies in Pediatric Infectious Disease and the Perspective of Patients and Healthcare Professionals: A Review

BACKGROUND AND AIMS

Pediatric infectious diseases pose a global health challenge, causing 13.7 million deaths in 2019 and three million in children under four. Early recognition and management are vital, and challenges in effectively addressing this persist, particularly in resource-limited areas. Digital health tools, such as telemedicine and mHealth, offer promising solutions. In this review, we aim to evaluate digital health applications in managing pediatric infectious diseases from patient and healthcare perspectives.

METHODS

A literature search was conducted using PubMed, Google Scholar, and Scopus with keywords including "digital health," "telemedicine," and "pediatric infectious disease." Studies published up to January 2024 were included and critically reviewed.

RESULTS

Digital health technologies aid in real-time monitoring and early diagnosis of infectious diseases, improving access to specialized care for pediatric populations. Tools like telemedicine and mHealth enhance communication between patients, caregivers, and physicians, facilitating shared decision-making. Wearable devices and mobile applications enable proactive health management and timely interventions. Despite access challenges in resource-limited settings, caregivers report benefits such as improved healthcare coordination, reduced delays in care, and better health outcomes for children.

CONCLUSION

Digital health shows promise in addressing pediatric infectious disease management, particularly in resource-limited settings, enhancing outcomes through timely interventions and better communication.

The role of exosomal hsa-miR-125b-5p and hsa-miR-320c as non-invasive biomarkers in high-radon areas of Kazakhstan

BACKGROUND

Radon, a radioactive gas, is a significant risk factor for lung cancer, especially in non-smokers. This study examines the expression of exosomal microRNAs (miRNAs) as potential biomarkers for radon-induced effects.

METHODS

A total of 109 participants from high- and low-radon areas in Kazakhstan were included. Exosomal hsa-miR-125b-5p and hsa-miR-320c levels were quantified using real-time PCR.

RESULTS

Results revealed a 25.4-fold increase in hsa-miR-125b-5p and a 12.5-fold decrease in hsa-miR-320c in participants exposed to high-radon levels compared to controls. Bioinformatic analysis identified key target genes, such as PRDM1 and IRF4, which are implicated in cancer development.

CONCLUSION

These findings suggest that exosomal miRNAs could serve as non-invasive biomarkers for radon exposure, offering potential for early diagnosis and monitoring of radon-induced lung cancer. The study underscores the need for further research to validate these miRNAs as reliable diagnostic tools.

Precision medicine in colorectal cancer: genomics profiling and targeted treatment

Precision medicine has revolutionized the treatment of colorectal cancer by enabling a personalized approach tailored to each patient's unique genetic characteristics. Genomic profiling allows for the identification of specific mutations in genes such as KRAS, BRAF, and PIK3CA, which play a crucial role in cell signaling pathways that regulate cell proliferation, apoptosis, and differentiation. This information enables doctors to select targeted therapies that inhibit specific molecular pathways, maximizing treatment effectiveness and minimizing side effects. Precision medicine also facilitates adaptive monitoring of tumor progression, allowing for adjustments in therapy to maintain treatment effectiveness. While challenges such as high costs, limited access to genomic technology, and the need for more representative genomic data for diverse populations remain, collaboration between researchers, medical practitioners, policymakers, and the pharmaceutical industry is crucial to ensure that precision medicine becomes a standard of care accessible to all. With continued advances and support, precision medicine has the potential to improve treatment outcomes, reduce morbidity and mortality rates, and enhance the quality of life for colorectal cancer patients worldwide.

Patient-derived xenograft model in cancer: establishment and applications

The patient-derived xenograft (PDX) model is a crucial in vivo model extensively employed in cancer research that has been shown to maintain the genomic characteristics and pathological structure of patients across various subtypes, metastatic, and diverse treatment histories. Various treatment strategies utilized in PDX models can offer valuable insights into the mechanisms of tumor progression, drug resistance, and the development of novel therapies. This review provides a comprehensive overview of the establishment and applications of PDX models. We present an overview of the history and current status of PDX models, elucidate the diverse construction methodologies employed for different tumors, and conduct a comparative analysis to highlight the distinct advantages and limitations of this model in relation to other in vivo models. The applications are elucidated in the domain of comprehending the mechanisms underlying tumor development and cancer therapy, which highlights broad applications in the fields of chemotherapy, targeted therapy, delivery systems, combination therapy, antibody-drug conjugates and radiotherapy. Furthermore, the combination of the PDX model with multiomics and single-cell analyses for cancer research has also been emphasized. The application of the PDX model in clinical treatment and personalized medicine is additionally emphasized.

Personalized treatment approaches in hepatocellular carcinoma

Personalized medicine is an emerging field that provides novel approaches to disease's early diagnosis, prevention, treatment, and prognosis based on the patient's criteria in gene expression, environmental factors, lifestyle, and diet. To date, hepatocellular carcinoma (HCC) is a significant global health burden, with an increasing incidence and significant death rates, despite advancements in surveillance, diagnosis, and therapeutic approaches. The majority of HCC lesions develop in patients with liver cirrhosis, carrying the risks of mortality associated with both the tumor burden and the cirrhosis. New therapeutic agents involving immune checkpoint inhibitors and targeted agents have been developed for sequential or concomitant application for advanced HCC but only a tiny percentage of patients benefit from each approach. Moreover, clinicians encounter difficulties determining the most appropriate regimen for each patient. This emphasizes the need for a personalized treatment approach. In other words, patients should no longer undergo treatment based on their tumor's histology but depending on the distinct molecular targets specific to their tumor biology. However, the utilization of precision medicine in managing HCC is still challenging. This review aims to discuss the role of personalized medicine in diagnosing, managing, and defining the prognosis of HCC. We also discuss the role of liquid biopsy and their clinical applications for immunotherapies in HCC. More clinical studies are still necessary to improve the precision of biomarkers used in the treatment decision for patients with HCC.

An Interdisciplinary Perspective on Improving Cancer Care in the State of Mississippi as an Example of Cancer Care Improvements in the Global South

Cancer disparities, a critical public health issue, particularly in states such as Mississippi, where socioeconomic factors significantly influence health outcomes, require our collective attention. This paper delves into the multifaceted nature of cancer disparities through a macro-level analysis of cancer data, specifically focusing on Mississippi as a microcosm of broader national and global trends. Two key indices, the Socio-Demographic Index (SDI) and the Social Deprivation Index (SDeI), provide valuable insights. The former offers a macro-level understanding of the socioeconomic factors that shape health and cancer outcomes. The latter quantifies disadvantages in small areas, identifying regions that need scientific, policy, and administrative support. The poor health care and cancer care (CC) outcomes in Mississippi are well documented and detailed here. However, SDI and SDeI data are not yet available in Mississippi. With biological, technological, and clinical research design advancements and other new innovative strategies emerging in the past decade in CC, a 'leapfrogging' of CC outcomes in Mississippi is within our reach. To achieve this goal, an interdisciplinary approach (IDA) addressing and solving the challenges faced in Mississippi is required. The IDA team must include disciplines that can determine SDI and SDeI for Mississippi and tie those findings to successfully apply new technological advances and innovations efficiently and cost-effectively by building infrastructure and developing implementation strategies. This can serve as a pilot demonstration project that will also help other similar regions within the United States, as well as the Global South.

Comparative analysis of extracellular vesicles miRNAs (EV-miRNAs) and cell-free microRNAs (cf-miRNAs) reveals that EV-miRNAs are more promising as diagnostic and prognostic biomarkers for prostate cancer

MicroRNAs can be found intracellularly incorporated into extracellular vesicles (EV-miRNAs) or extracellularly as cell-free miRNAs (cf-miRNAs). This study aimed to compare the diagnostic and prognostic potential of four miRNAs with recognized roles in prostate cancer as cf-miRNAs and EV-miRNAs, obtained from liquid biopsies (LB). Total RNA was isolated from whole plasma and plasma EVs from 15 controls (CTR) and 30 patients (20 with localized prostate cancer (PCa), 10 with metastatic prostate cancer (mPCa)). The miRNAs were quantified by RT-qPCR and the relative expression of these miRNAs was compared between the three groups, and their associations with clinicopathological parameters were assessed. Receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic potential of the miRNAs in discriminating different groups. Overall, EV-miRNAs showed higher expression compared to cf-miRNAs. All EV-miRNAs analyzed showed diagnostic potential with an area under the curve (AUC) above 0.744. EV-miR-21-5p, EV-miR-375-3p, and EV-miR-1290-3p were overexpressed in PCa and mPCa compared to CTR, while EV-miR-200c-3p was overexpressed only in mPCa in comparison to CTR. Remarkably, EV-miR-375-3p and EV-miR-1290-3p could differentiate mPCa with ISUP ≥ 3, demonstrating their prognostic potential. In addition, EV-miR-1290-3p and EV-4-miR-panel detected patients with PSA > 10 ng/mL. Cf-miRNAs performed lower than EV-miRNAs, which can be explained by the greater stability and specificity of EV-miRNAs, making them superior to cf-miRNA. The results show that LB, a non-invasive strategy, is clinically feasible to identify EV-miRNAs as biomarkers for PCa and may provide additional information for assessing PCa risk stratification.

Use of Drug Sensitisers to Improve Therapeutic Index in Cancer

The clinical management of malignant tumours is challenging, often leading to severe adverse effects and death. Drug resistance (DR) antagonises the effectiveness of treatments, and increasing drug dosage can worsen the therapeutic index (TI). Current efforts to overcome DR predominantly involve the use of drug combinations, including applying multiple anti-cancerous drugs, employing drug sensitisers, which are chemical agents that enhance pharmacokinetics (PK), including the targeting of cellular pathways and regulating pertinent membrane transporters. While combining multiple compounds may lead to drug-drug interactions (DDI) or polypharmacy effect, the use of drug sensitisers permits rapid attainment of effective treatment dosages at the disease site to prevent early DR and minimise side effects and will reduce the chance of DDI as lower drug doses are required. This review highlights the essential use of TI in evaluating drug dosage for cancer treatment and discusses the lack of a unified standard for TI within the field. Commonly used benefit-risk assessment criteria are summarised, and the critical exploration of the current use of TI in the pharmaceutical industrial sector is included. Specifically, this review leads to the discussion of drug sensitisers to facilitate improved ratios of effective dose to toxic dose directly in humans. The combination of drug and sensitiser molecules might see additional benefits to rekindle those drugs that failed late-stage clinical trials by the removal of detrimental off-target activities through the use of lower drug doses. Drug combinations and employing drug sensitisers are potential means to combat DR. The evolution of drug combinations and polypharmacy on TI are reviewed. Notably, the novel binary weapon approach is introduced as a new opportunity to improve TI. This review emphasises the urgent need for a criterion to systematically evaluate drug safety and efficiency for practical implementation in the field.

The future of collaborative precision oncology approaches in sub-Saharan Africa: learnings from around the globe

As the projected incidence and mortality of cancer in Sub-Saharan Africa (SSA) rises to epidemic proportions, it is imperative that more is done to identify the genomic differences and commonalities between patients of African and European ancestry to fulfil the promise of precision oncology. Here, we summarize the utility of precision oncology approaches, with a focus on comprehensive genomic profiling (CGP) and consolidate examples of national and international consortia that are driving the field forward. We describe the importance of genomic diversity and its relevance in cancer, and propose recommendations, success factors and desired outcomes for precision oncology consortia to adopt in SSA. Through this, we hope to catalyze the initiation of such projects and to contribute to improving cancer patient outcomes in the region.

Comprehensive molecular and clinical insights into non-small cell lung cancer transformation to small cell lung cancer with an illustrative case report

Histologic transformation to small cell lung cancer (tSCLC) is a rare but increasingly recognised mechanism of acquired resistance to tyrosine kinase inhibitors (TKI) in patients with epidermal growth factor receptor (EGFR)-positive non-small cell lung cancer (NSCLC). Beyond its acknowledged role in TKI resistance, histologic transformation to SCLC might be an important, yet under-recognised, mechanism of resistance in NSCLC treated with immunotherapy. Our review identified 32 studies that investigated tSCLC development in patients with EGFR-mutated NSCLC treated with TKI therapy and 16 case reports of patients treated with immunotherapy. It revealed the rarity of tSCLC, with a predominance of EGFR exon 19 mutations and limited therapeutic options and outcomes. Across all analysed studies in EGFR-mutated NSCLC treated with TKI therapy, the median time to tSCLC development was ∼17 months, with a median overall survival of 10 months. Histologic transformation of EGFR-mutated NSCLC to SCLC is a rare, but challenging clinical problem with a poor prognosis. A small number of documented cases of tSCLC after immunotherapy highlight the need for rebiopsies at progression to diagnose this potential resistance mechanism. Further research is needed to better understand the mechanisms underlying this phenomenon and to develop more effective treatment strategies for patients with tSCLC.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

Nanoparticle-Mediated Drug Delivery Systems for Precision Targeting in Oncology

Nanotechnology has emerged as a transformative force in oncology, facilitating advancements in site-specific cancer therapy and personalized oncomedicine. The development of nanomedicines explicitly targeted to cancer cells represents a pivotal breakthrough, allowing the development of precise interventions. These cancer-cell-targeted nanomedicines operate within the intricate milieu of the tumour microenvironment, further enhancing their therapeutic efficacy. This comprehensive review provides a contemporary perspective on precision cancer medicine and underscores the critical role of nanotechnology in advancing site-specific cancer therapy and personalized oncomedicine. It explores the categorization of nanoparticle types, distinguishing between organic and inorganic variants, and examines their significance in the targeted delivery of anticancer drugs. Current insights into the strategies for developing actively targeted nanomedicines across various cancer types are also provided, thus addressing relevant challenges associated with drug delivery barriers. Promising future directions in personalized cancer nanomedicine approaches are delivered, emphasising the imperative for continued optimization of nanocarriers in precision cancer medicine. The discussion underscores translational research's need to enhance cancer patients' outcomes by refining nanocarrier technologies in nanotechnology-driven, site-specific cancer therapy.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

Liver X Receptors (LXRs) in cancer-an Eagle's view on molecular insights and therapeutic opportunities

Cancer has become a serious health burden that results in high incidence and mortality rates every year, mainly due to various molecular alterations inside the cell. Liver X receptors (LXRs) dysregulation is one among them that plays a vital role in cholesterol metabolism, lipid metabolism and inflammation and also plays a crucial role in various diseases such as obesity, metabolic dysfunction-associated fatty liver disease (MAFLD), cardiovascular diseases, Type 2 diabetes, osteoporosis, and cancer. Studies report that the activation of LXRs inhibits cancer growth by inhibiting cellular proliferation, inducing apoptosis and autophagy, regulating cholesterol metabolism, various signalling pathways such as Wnt, and PI3K/AKT, modulating the expression levels of cell-cycle regulators, and promoting antitumor immunity inside the tumor microenvironment. In this review, we have discussed the role, structure, and functions of LXRs and also summarized their ligands along with their mechanism of action. In addition, the role of LXRs in various cancers, tumor immunity and tumor microenvironment (TME) along with the importance of precision medicine in LXR-targeted therapies has been discussed to emphasize the LXRs as potent targets for the development of novel cancer therapeutics.