Keyword: Sequencing

ABSTRACT: Introduction: Germline mutations in the BRCA1 and BRCA2 genes are an important hereditary risk factor for the development of breast cancer. The spectrum of pathogenic variants of these genes is characterized by pronounced ethnic and population specificity, including the presence of founder mutations. Data on the spectrum of germline BRCA1/BRCA2 variants in the Kazakh population remain limited, which hinders their application in clinical practice and genetic counseling.
Objective: To study the spectrum of germline mutations in the BRCA1 and BRCA2 genes in patients with breast cancer and women with a family history in the Kazakh population and to identify the founder mutation.
Materials and Methods: The study included 544 women of Kazakh ethnicity with breast cancer or a family history of cancer. DNA was isolated from peripheral blood lymphocytes according to the manufacturer's protocol. Exons and adjacent intronic regions of the BRCA1 and BRCA2 genes were sequenced by NGS. Variants were classified by clinical significance, and their spectrum and distribution by gene, type, and localization were analyzed.
Results: Of the 544 examined patients, 178 (32.7%) were found to have mutations in the BRCA genes. Mutations in the BRCA1 gene were detected in 35 patients (19.7%), in the BRCA2 gene — in 119 patients (66.8%), and mutations in both genes — in 24 patients (13.5%).
The study identified a total of 125 BRCA gene variants. Sequence analysis revealed 37 pathogenic variants in 81 patients, 83 likely pathogenic variants in 104 patients, 1 likely benign variant in 6 patients, 2 benign variants in 6 patients, and 2 variants of uncertain clinical significance in 2 patients.
Among BRCA1 gene variants, the most common was a deletion of exon 6, detected in 11 patients (6.1%). Deletions of exons 2, 13, and 20 were found in 7 patients each (3.9%), while deletions of exons 8 and 23, as well as variants BRCA1 c.3214delC and BRCA1 c.1044_1045insC, were found in 3 patients each (1.7%).
Among the identified BRCA2 gene variants, the most common was a deletion of exon 16, detected in 37 patients. The variant c.24_27delGCCAinsCG was identified in 15 patients, c.2600_2601insA in 12 patients, and c.9241_9242insA in 11 patients.
Conclusions: The spectrum of germline BRCA1/BRCA2 mutations in the Kazakh population is characterized by a predominance of BRCA2 gene variants. Deletion of exon 16 of the BRCA2 gene was identified as a founder mutation.

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: Minimal residual disease (MRD) has become a significant predictor of relapse and survival in acute myeloid leukemia (AML), indicating the extent of remission beyond traditional morphological evaluation. Although multicolor flow cytometry and quantitative PCR are essential methodologies in minimal residual disease identification, both are constrained by immunophenotypic variability, the necessity for stable molecular targets, and limited sensitivity. Advancements in next-generation sequencing (NGS) have revolutionized the minimal residual disease (MRD) field by enabling highly sensitive, mutation-driven identification of leukemic clones across a broad genomic landscape. Contemporary error-suppressed next-generation sequencing techniques—such as unique molecular identifiers, duplex sequencing, and single-molecule molecular inversion probes—have enhanced analytical sensitivity to the 10⁻⁵ to 10⁻⁶ range, enabling the detection of ultra-low-frequency variations with greater specificity. These techniques improve clinical risk classification, refine prognostication within genetically defined AML subtypes, and guide therapeutic options, including post-remission therapy, targeted inhibition, and the timing and intensity of allogeneic stem cell transplantation. Innovative applications, such as single-cell sequencing, cell-free DNA studies, and integrative multi-omic MRD evaluation, enhance the capabilities of genomics-based monitoring. Nonetheless, obstacles remain, such as differentiating cancer mutations from clonal hematopoiesis, standardizing analytical pipelines, establishing clinically relevant thresholds, and incorporating NGS MRD into standardized treatment protocols. This review encapsulates contemporary NGS methods for AML MRD diagnosis, assesses their clinical ramifications and constraints, and suggests future pathways necessary for comprehensive clinical integration. With advancements in the area, NGS-based MRD is set to become a pivotal element of precision-guided AML control.