Keyword: Oncology

ABSTRACT: Precision oncology seeks to identify patient-specific therapeutic vulnerabilities; however, conventional genomic profiling is limited by intratumoral heterogeneity and its inability to distinguish functional driver alterations from passenger mutations, often resulting in incomplete prediction of therapeutic response. Recently, the combination of CRISPR functional genomics with single-cell multi-omics has proven to be a paradigm-shifting strategy for understanding context-specific cancer vulnerabilities by causal functional interrogation. The aim of this review is to critically examine recent progress in the integration of these technologies for discovering vulnerabilities in cancer, and introduces a new conceptual model, called the Integrated Functional Precision Oncology (IFPO) Framework, that brings together functional genomic perturbation, single-cell multi-omics, computational systems biology, and clinical translation. Literature was retrieved from Pubmed, Web of Science and Google Scholar and peer reviewed studies published between 2020 and 2025. Key findings from historic and recent research were analyzed to pinpoint methodological innovations, translational studies, limitations, and areas in need of further research. The results reveal that the integrated CRISPR–single-cell platforms, such as Perturb-seq, CROP-seq, and ECCITE-seq, can be used to causally interrogate gene function at the single-cell level, allowing for the identification of context-dependent essential genes, synthetic lethal interactions, regulatory networks, and therapeutic resistance mechanisms. All the evidence suggests that therapeutic response is not merely a function of genomic alterations but also the dynamic interplay between genomic alterations, cellular state, epigenetic plasticity, and the tumor microenvironment. The proposed IFPO Framework integrates these findings into a systems-level model that captures the mechanisms by which these functional perturbations, multimodal molecular profiling, and AI-driven integration of data converge to reveal clinically actionable cancer vulnerabilities. This integrated paradigm transforms precision oncology from descriptive molecular profiling to functional systems oncology and offers directions for further progress of precision cancer treatment based on enhanced biomarker discovery, therapeutic target identification, and prospective clinical translation.

ABSTRACT: Prostate cancer still remains one of the most common cancers in men worldwide, and it is a great therapeutic challenge, especially in the field of immunotherapeutics. The tumour microenvironment (TME) is immunologically “cold” in prostate cancer, and influenced by intrinsic molecular characteristics of the disease such as androgen receptor (AR) signalling, PTEN loss, and lineage plasticity towards neuroendocrine prostate cancer (NEPC). Together, these aspects inhibit antigen presentation, block the entry of cytotoxic T cells and help to establish spatially organised immunosuppressive niches, providing a rational explanation for the clinical variability and partial efficacy of immune-based therapies.
Traditional bulk genomic approaches have provided important insights into tumour biology but are unable to capture the cellular and spatial complexity of tumour–immune interactions. These developments have been spurred by recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics, which allow to detect individual cell subpopulations within intact tumour tissues, such as exhausted T cells co-expressing PD-1, TIM-3, LAG-3 and TIGIT, immunosuppressive SPP1+ macrophages and various cancer-associated fibroblast subpopulations. These technologies have identified specific immune exclusion sites, stromal–epithelial immune silencing barriers, and therapeutic resistance and immune evasion regulatory programs in the context of prostate cancer specifically.
However, there are still many technical challenges that need to be overcome, such as the lack of patient samples and their demographic diversity, data integration, lack of spatial characterisation of bone metastases and difficulties in clinical translation. Comprehensive multi-omics atlases, AI-driven spatial pattern recognition, functional validation of potential targets and prospective clinical trials based on biomarkers are all important areas for future research. They show significant potential for the creation of better, personalized immunotherapeutic treatment for prostate cancer.

ABSTRACT: Artificial intelligence (AI) has become increasingly integrated into radiology and nuclear medicine, particularly in oncology, where imaging plays a central role in diagnosis, staging, treatment planning, and response assessment. To date, evaluation of AI-enabled radiology has been dominated by diagnostic accuracy metrics derived from retrospective validation studies. While such measures are essential for technical assessment, they provide limited insight into real-world clinical value. High algorithmic performance does not necessarily translate into improved decision-making, workflow efficiency, patient outcomes, or health system performance. This narrative review critically examines AI-enabled radiology as a digital health intervention in oncology and nuclear medicine, emphasizing the need to move beyond accuracy-centric evaluation paradigms. We analyze the translational gap between controlled validation and routine clinical deployment, highlighting challenges related to dataset bias, generalizability, and human–AI interaction. Key domains of real-world impact are explored, including clinical decision-making, multidisciplinary integration, workflow and operational performance, patient-centered outcomes, and system-level implications. Methodological considerations for outcome-focused evaluation are discussed, alongside regulatory, ethical, and governance frameworks necessary for responsible implementation. We propose a clinical-impact–centered evaluation framework that links AI-assisted imaging to patient, clinician, and system-level outcomes within a continuous monitoring model. Reframing AI-enabled radiology as a clinical intervention rather than a standalone algorithm is essential for ensuring meaningful, equitable, and sustainable adoption in oncology and nuclear medicine practice.

ABSTRACT: Liquid biopsies have developed as a revolutionary technique in cancer diagnosis, treatment evaluation, and the detection of therapeutic resistance. Unlike traditional tissue biopsies, which are invasive and limited to a single temporal analysis, liquid biopsies offer a non-invasive, real-time evaluation of tumour dynamics through the analysis of biomarkers such as circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), exosomes, and microRNAs. This approach enables continuous monitoring of tumour advancement, allowing for the early detection of cancer, the tracking of minimal residual disease, and the identification of emerging resistance mutations. As cancers advance and acquire resistance to therapies, liquid biopsy provides critical information that enables clinicians to customise treatment strategies and improve outcomes. Despite challenges such as sensitivity limitations in early-stage cancers and the necessity for standardised testing protocols, technological advancements, including next-generation sequencing (NGS), CRISPR, and AI-driven analytics, are enhancing the precision and accessibility of liquid biopsies. Through ongoing validation and cost-reduction efforts, liquid biopsies are set to become essential to precision oncology, offering a transformative approach to cancer therapy that could improve patient outcomes and foster equitable healthcare globally.

ABSTRACT: This inaugural editorial introduces the new journal, "Oncology, Nuclear Medicine and Transplantology," launched by the National Research Oncology Center (NROC) in Kazakhstan. It outlines the journal's mission to serve as a pivotal interdisciplinary platform integrating these three rapidly evolving and interconnected fields. The editorial emphasizes the journal's commitment to addressing significant healthcare challenges at the national level in Kazakhstan, stimulating regional collaboration across Central Asia, and contributing to the global scientific discourse. The goal is to foster the exchange of original research, clinical experiences, and innovative practices to ultimately improve patient care and advance medical science in these critical specialties.

ABSTRACT: Introduction: This study is aimed at assessing the operational efficiency of the admission department of the National Research Oncological Center (NROC) for the period from 2020 to 2024 with an emphasis on the impact of digitalization on patient management and workflow optimization. Telemedicine is a key tool for improving the availability and quality of medical care, especially for patients living in remote regions. In oncology, its importance is increasing due to the need for interdisciplinary interaction and quick routing of patients.
Methods: A retrospective analysis was conducted using internal hospital records, admission logs, and national healthcare regulations. Key performance indicators were assessed, including patient intake volume, processing time, and rejection rates. The impact of digital tools such as automated registration, routing algorithms, and remote clinical validation was examined.
Results: Patient visits increased from 5,664 in 2020 to 11,851 in 2024, while cancer-related hospitalizations rose from 1,477 to 6,102. The average waiting time for reception was reduced from 12 to 7 hours, and the processing time for documentation was reduced from 45 to 15 minutes. The introduction of digital solutions improved the accuracy of admission and reduced the number of inappropriate hospitalizations. Improvements in identifying clinical contraindications and infectious risks through remote screening technologies were also noted. The number of telemedicine consultations increased 3 times, especially in surgery and transplantology.
Conclusion: Digital transformation has significantly improved admissions efficiency, improving patient flow, reducing processing time and improving decision-making. Further development of digital infrastructure and staff competencies is recommended to ensure sustainable growth and quality of care in cancer care. The comprehensive implementation of telemedicine and interaction with air ambulance contribute to increasing the availability of cancer care, optimizing resources and reducing costs.