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Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition

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A special issue of Current Issues in Molecular Biology (ISSN 1467-3045). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 11807

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Prof. Dr. Javier Azúa-Romeo

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1. Department of Human Anatomy and Histology, Faculty of Medicine, University of Zaragoza, 50009 Zaragoza, Spain
2. Department of Pathology, Analiza, 28001 Madrid, Spain
Interests: pathology; histology; cancer; biomakers; molecular biology; cytology
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Dear Colleagues,

The arrival and evolution of next-generation sequencing (NGS) technology have enlarged our capacity to read genetic code in-depth, beginning a new era in the identification of disease-causing genetic changes. While our ability to “read” individual genetic changes has dramatically increased, the “translationability” of the identified changes is complex, and the establishment of a new driver gene/variant constitutes an NGS-based genetic screening bottleneck. This is particularly true in cancer, where only a very small fraction of the 10–20% of the cancers associated with familial aggregation have a known underlying genetic cause. Moreover, the profile of genomic changes in the 80–90% of the cancers arising sporadically is highly heterogeneous, making it difficult to distinguish driving, secondary, and progression-associated genomic variation.

In this Special Issue, we invite researchers to submit their work highlighting or discarding the identification of new genes/variants as a cause of cancer development or progression. Evidence may include case–control studies, segregation analysis, gene/variant specific gene editing (CRISPR/Cas9 or other), protein structure analysis, functional studies, or other approaches considered relevant for the validation of gene–disease association.

You can read the first and second volumes of our Special Issue here: https://www.mdpi.com/journal/cimb/special_issues/genomic_cancer_ https://www.mdpi.com/journal/cimb/special_issues/S44571XE42.

Prof. Dr. Javier Azúa-Romeo
Guest Editor

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Keywords

next-generation sequencing (NGS)
genetic variation
driver gene
functional validation
gene editing
cancer

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Published Papers (10 papers)

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Research

21 pages, 2271 KB

Open AccessArticle

EpiSNPdb: A Comprehensive Database of Genetic Epistasis Across Multiple Cancer Types

by Xiaohong Wu, Jianye Yang, Wen Cao, Jiaxin He, Congcong Min, Xiaohui Niu, Yuan Quan and Jing Gong

Curr. Issues Mol. Biol. 2026, 48(8), 753; https://doi.org/10.3390/cimb48080753 - 24 Jul 2026

Viewed by 249

Abstract

Increasing evidence shows that epistasis, defined as interactive effects between genetic loci, may contribute to the missing heritability of cancer. However, systematic genome-wide epistasis identification in cancer remains challenging. Here, by leveraging genotype and clinical data from 380,983 samples in the UK Biobank, we identified 202,032 candidate epistatic single nucleotide polymorphism (epiSNP) pairs associated with cancer risk across 16 cancer types. Notably, multivariable Cox regression identified 123 epiSNP pairs with significant interaction effects on overall survival, suggesting that interaction-level genetic signals can provide prognostic information beyond individual SNP effects. Through functional analysis of the 202,032 candidate epiSNP pairs, we identified 7152 pairs supported by gene co-expression data and 12,326 pairs with protein–protein interaction (PPI) evidence. By mapping epiSNP pairs to corresponding gene pairs and then linking these gene pairs to drug–target databases, we identified 1040 epistatic gene pairs with FDA-approved drug–target records. Additionally, through KM survival analysis of the candidate epiSNP pairs, we detected 7068 pairs significantly associated with patient overall survival. Finally, we constructed an open-access database, EpiSNPdb, to facilitate cancer epistasis research. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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16 pages, 241 KB

Open AccessArticle

Real-World Evaluation of Next-Generation Sequencing in Lung Cancer: Associations Between Histological Subtypes and Genomic Alterations

by Javier Azúa-Romeo, Maria Cabetas, Irene Rodriguez, Bárbara Angulo and Arantxa Andueza

Curr. Issues Mol. Biol. 2026, 48(6), 628; https://doi.org/10.3390/cimb48060628 - 16 Jun 2026

Viewed by 401

Abstract

Background: Lung cancer is a highly heterogeneous disease in which molecular characterization has become essential for guiding personalized therapies. The implementation of next-generation sequencing (NGS) allows for the simultaneous detection of multiple genomic alterations, improving tumor profiling and therapeutic decision-making. This study aimed to characterize the molecular landscape of lung cancer using NGS and to evaluate its association with histological subtypes and programmed death-ligand 1 (PD-L1) expression. Methods: A retrospective observational study was conducted on 96 patients diagnosed with lung cancer between 2023 and 2025. Molecular profiling was performed using the Action OncoKitDx panel. Associations between genetic alterations, histological subtypes, and PD-L1 expression were analyzed using Fisher’s exact test, with p < 0.05 considered statistically significant. Results: Adenocarcinoma was the most common histological subtype (67.7%), followed by squamous cell carcinoma (26%). The most common mutations were KRAS (34.4%), TP53 (29.2%), and EGFR (11.5%). KRAS mutations were significantly associated with adenocarcinoma (p = 0.001), while squamous cell carcinoma showed a higher frequency of cases without molecular alterations detected by the NGS panel (p = 0.002). Co-mutations were identified in 22.9% of cases, with KRAS–TP53 being the most common combination. Tumors harboring EGFR mutations showed a significantly lower frequency of co-mutations (p = 0.012). No significant associations were found between PD-L1 expression and either histological subtypes or the analyzed genetic alterations. Conclusions: Lung cancer exhibits marked molecular heterogeneity, with a predominance of KRAS mutations in adenocarcinoma. The low frequency of co-mutations in EGFR-mutated tumors supports their role as dominant driver alterations. The lack of association between PD-L1 expression and genomic alterations highlights the complexity of its regulation and suggests the involvement of multiple biological factors. These findings reinforce the clinical value of NGS in comprehensive tumor profiling and in the development of precision medicine strategies. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

21 pages, 4699 KB

Open AccessArticle

Leveraging Deep Learning to Construct a Programmed Cell Death-Driven Prognostic Signature in Acute Myeloid Leukemia

by Chunlong Zhang, Haisen Ni, Ziyi Zhao and Ning Zhao

Curr. Issues Mol. Biol. 2026, 48(4), 354; https://doi.org/10.3390/cimb48040354 - 27 Mar 2026

Viewed by 1052

Abstract

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy characterized by profound molecular heterogeneity and high relapse rates, posing significant clinical challenges. Programmed cell death (PCD), encompassing diverse regulated modalities such as apoptosis, necroptosis, and ferroptosis, plays a key role in leukemogenesis and therapeutic response; however, a comprehensive prognostic framework integrating multi-modal PCD pathways in AML remains elusive. In this study, we performed a systematic transcriptomic analysis of 1624 genes associated with 13 distinct PCD forms. A novel computational pipeline combining a variational autoencoder (VAE) for dimensionality reduction and a multilayer perceptron (MLP) for classification was employed to identify robust PCD-related biomarkers, interpreted via SHapley Additive exPlanations (SHAP) analysis. This approach identified 48 candidate genes with discriminative potential between AML and normal bone marrow. Unsupervised consensus clustering based on these genes delineated two molecular subtypes exhibiting divergent clinical outcomes and immune microenvironment profiles. The subtype demonstrated an immunosuppressive phenotype, characterized by enriched regulatory T cells, M2 macrophages, and elevated expression of inhibitory immune checkpoints, correlating with inferior survival. We developed an 8-gene prognostic signature (SORL1, PIK3R5, RIPK3, ELANE, GPX1, VNN1, CD74, and IL3RA) that effectively categorized patients into high- and low-risk groups with notable survival differences, validated across independent cohorts. A prognostic nomogram combining the risk score, age, and cytogenetic risk enhanced the prediction accuracy for overall survival. Our study presents an integrative model that connects multi-modal PCD pathways to AML prognosis, offering a new molecular subtyping system and a clinically applicable risk assessment tool for improved prognostication and personalized treatment strategies. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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10 pages, 636 KB

Open AccessArticle

Saturation Genome Editing Targeting KRAS Mutations in HCT 116 Colon Carcinoma Cells for Pooled SNV Functional Profiling in Diploid Cancer Model

by Taiji Hamada, Seiya Yokoyama, Ryo Nakabayashi, Yoshihiko Suzuki, Shinichi Morishita, Toshiaki Akahane, Kei Matsuo, Ikumi Kitazono, Tatsuhiko Furukawa and Akihide Tanimoto

Curr. Issues Mol. Biol. 2026, 48(4), 341; https://doi.org/10.3390/cimb48040341 - 25 Mar 2026

Viewed by 1125

Abstract

Evaluating cancer gene mutations is critical for effective therapeutic selection. Although massive parallel sequencing can efficiently detect gene mutations, most are variants of uncertain significance (VUS). Saturation genome editing (SGE) can facilitate VUS analysis by leveraging CRISPR-Cas9 and homology-directed repair to simultaneously introduce abundant gene mutations. Chronic myelogenous leukemia-derived HAP1 cells are widely used in SGE because of their clear genotype–phenotype relationship; however, the sole use of haploid cells limits SGE applicability in cancer research. Therefore, we developed an SGE-based system for evaluating KRAS mutations in diploid HCT 116 colon carcinoma cells. Single-nucleotide variants (SNVs) in KRAS codons A11–V14 were generated using Cas9-based SGE. Massive parallel sequencing revealed increased abundance of KRAS ^G12 and KRAS ^G13 SNVs and decreased abundance of the KRAS ^G12C SNV after KRAS ^G12C inhibitor treatment in SGE pooled cells. These results indicate that SGE is applicable to diploid HCT 116 cells and useful for evaluating SNV population changes and drug sensitivity. Thus, although haploid HAP1 cells are the primary models for SGE, the successful application of SGE to diploid HCT 116 colon carcinoma cells provides a practical framework for implementing SGE in KRAS-dependent carcinoma cells. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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15 pages, 2041 KB

Open AccessArticle

Upregulation of miR-4286 and miR-146a-5p in Metastatic Melanoma, Revealed by Multiplex Expression Analysis

by Iliyan Pochileev, Albena Fakirova, Desislava Tashkova, Aleksandra Gerdgikova, Nevena Ilieva, Denitsa Serteva, Gergana Shalamanova, Hristo Ivanov, Aleksandar Linev and Ivanka Dimova

Curr. Issues Mol. Biol. 2026, 48(3), 279; https://doi.org/10.3390/cimb48030279 - 5 Mar 2026

Viewed by 2433

Abstract

Background: Metastatic melanoma is an extremely aggressive malignancy with limited therapeutic options, despite advances in targeted and immunotherapy. MicroRNAs are key post-transcriptional regulators of gene expression and play a critical role in tumor adaptation, invasion, and metastasis. The aim of our study was to identify dysregulated miRNAs which may serve as novel biomarkers and therapeutic targets. Materials and Methods: The study was conducted on FFPE samples from metastatic melanoma (n = 15), compared to healthy skin tissue (n = 6). BRAF V600E/Ec mutation status was established by Real-Time qPCR. Expression miRNA analysis was performed, using digital counting of 827 miRNAs on the NanoString platform, with data normalization and fold change calculations. Results: Following normalization and quality control metrics, 58 differentially expressed miRNAs were identified in BRAFwt melanoma samples: 6 overexpressed and 52 inderexpressed miRNAs. In BRAFmut melanoma, 37 microRNAs were differentially expressed: 11 overexpressed and 26 underexpressed. Four miRNAs showed elevated expression in both melanoma groups. Among them, miR-146a-5p and miR-4286 demonstrated the highest elevation, especially in BRAFmut tumors. We focused further on their targeted genes. Conclusion: This study demonstrates significant alterations in the miRNA expression profile in metastatic melanoma and highlights the potential of miR-146a-5p and miR-4286 as key regulators of tumor biology. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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17 pages, 78428 KB

Open AccessArticle

Assessment of Homologous Recombination System Gene Expression in Chemologically Induced Carcinogenesis In Vivo Models

by Matvey M. Tsyganov, Danna Zh. Bulatova, Anastasia A. Fedorenko, Dmitry M. Loos, Pavel E. Nikiforov, Irina A. Tsydenova, Aigerim A. Bayanbayeva, Zhansaya Sharipkhanova, Sofia S. Timoshenko and Marina K. Ibragimova

Curr. Issues Mol. Biol. 2026, 48(3), 275; https://doi.org/10.3390/cimb48030275 - 4 Mar 2026

Cited by 1 | Viewed by 848

Abstract

Understanding the molecular mechanisms of carcinogenesis, including disruptions in the homologous recombination system, is fundamental to understanding malignant transformation. Dysfunction of homologous recombination genes, such as BRCA1 and BRCA2, contributes to genomic instability and the development of more aggressive tumor clones. The use of chemical carcinogens enables the modeling of tumor formation and the monitoring of changes in molecular genetic parameters. This approach is important for understanding how tumor cells adapt to genotoxic stress and for advancing the development of personalized cancer therapies. The objective of this study was to evaluate the expression of key homologous recombination system genes in a model of chemically induced carcinogenesis in mice. Materials and Methods: Male outbred ICR (CD-1) laboratory mice (n = 40) were used to study chemically induced carcinogenesis. The animals were divided into four groups: two control groups and two experimental groups, which received 3-methylcholanthrene (MC) or trichloroacetic acid (TCA). Tumor cells were identified by histological analysis of autopsy material using light microscopy after standard hematoxylin and eosin staining. RNA and DNA were extracted from cell suspensions using the RNeasy Plus Mini Kit and QIAamp DNA Mini Kit (Qiagen, Hilden, Germany), respectively. The expression levels of homologous recombination genes were assessed by RT-PCR and microarray analysis. Digital PCR was performed to assess chromosomal aberrations in the Brca1 gene. Results: Tumor formations were identified in laboratory animals two months after 3-methylcholanthrene. Histological analysis revealed morphological changes in a pleomorphic cell tumor, forming diverse, multidirectional fascicular and swirling structures, as well as large solid foci composed of markedly polymorphic spindle-shaped and epithelioid cells. Analysis of copy number aberrations in the examined samples showed that the frequency of Brca1 deletions was 60%, while 40% of animals had normal gene copy number. To further characterize the molecular changes, we assessed gene expression levels through expression microarray analysis. A total of 14 genes were hypoexpressed in the tumor compared to the normal tissue, with p < 0.05. A high level of differential expression was characteristic for Rad50, Rad51, Brca1, Brca2, and Pold4. Two genes, Rad52 and Bard1, exhibited increased expression levels. It was shown that as the tumor mass increased, so did the frequency of homologous recombination genes with hypoexpression. Conclusions: Our findings confirm that MC and TCA influence tumor formation and reveal that suppression of homologous recombination genes may contribute to this process. In addition, it has been established that as tumors progress, the expression of DNA repair genes declines and aberrant gene states accumulate. These data emphasize the importance of studying the state of DNA repair genes for the development of more effective strategies for cancer diagnosis and therapy. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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20 pages, 44649 KB

Open AccessArticle

Multi-Omic and Spatial Profiling Identifies an Epithelial DKK1 Associated with Microenvironmental Remodeling in Pancreatic Ductal Adenocarcinoma

by Jiajia Xu, Kaiqiang Qian, Yanyu Ding, Jianghao Cheng, Xu Zhang, Yong Huang and Bo Liu

Curr. Issues Mol. Biol. 2026, 48(2), 182; https://doi.org/10.3390/cimb48020182 - 5 Feb 2026

Viewed by 998

Abstract

Objective: This study aimed to identify clinically relevant regulators of pancreatic ductal adenocarcinoma (PDAC), a disease characterized by stromal remodeling and immune suppression, and to define their links to malignant progression and microenvironmental reprogramming. Methods: We integrated multi-cohort bulk, single-cell, and spatial transcriptomic datasets and subsequently validated bulk differential expression and network analyses with machine learning-based prioritization in an independent combined cohort (TCGA-PAAD plus GSE62452). Single-cell mapping was used to assess cell-type specificity, positioning candidates along inferCNV- and pseudotime-defined malignant continua. In Visium sections, a DKK1-associated program score quantified intratumoral spatial heterogeneity and informed our analyses of ligand–receptor communication. Bulk immune deconvolution linked gene levels to immune infiltration patterns, and functional assays were used to test the impact of DKK1 knockdown on migration, proliferation, clonogenic growth, and apoptosis in PDAC cells. Results: Four reproducible tumor-associated genes—DKK1, COL10A1, SULF1, and SLC24A3—were prioritized and validated externally. DKK1 was predominantly expressed by epithelial tumor cells and tracked along a malignant progression continuum. Spatially, the DKK1 program localized to epithelial-dominant regions, revealed pronounced intratumoral heterogeneity, and highlighted epithelial–endothelial and endothelial–immune signaling in high-score areas. Immune deconvolution associated higher DKK1 expression with increased myeloid infiltration and reduced cytotoxic lymphocyte signatures. Functionally, DKK1 knockdown impaired migration, proliferation, and clonogenicity while increasing apoptosis. Conclusions: We demonstrate that DKK1 is an epithelial-derived regulator linked to malignant progression and tumor–stroma–immune remodeling, supporting its potential as a biomarker and therapeutic target in PDAC treatment, including rational combinations with stroma-modulating strategies and immunotherapy. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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23 pages, 4496 KB

Open AccessArticle

A Multi-Gene Signature Associated with 1-Year Survival in Patients with Stage I Liver Cancer: Integration of Preclinical and TCGA Data

by Ritam Adhikari, Bhaskar V. S. Kallakury, Chiranjeev Dash and Rabindra Roy

Curr. Issues Mol. Biol. 2026, 48(2), 136; https://doi.org/10.3390/cimb48020136 - 27 Jan 2026

Viewed by 1438

Abstract

Approximately 50% of individuals diagnosed with Stage I liver cancer live beyond four years; however, a small subset of Stage I patients die within the first year. A prognostic biomarker panel that can identify high-risk Stage I patients may be extremely valuable. In this study, we used the Long–Evans Cinnamon (LEC) rat model of Wilson’s Disease and hepatocellular carcinoma (HCC), along with data from The Cancer Genome Atlas (TCGA) human database, to create a novel biomarker panel. We generated and analyzed a rat microarray gene expression profile by comparing liver tumor tissues with adjacent normal tissues from the same animals, covering approximately 30,000 genes. The microarray results were translated into a five-gene panel associated with 1-year survival in Stage I liver cancer patients based on TCGA data, in combination with machine learning and bioinformatics approaches. The panel was internally validated following the “REporting recommendations for Tumor MARKer prognostic studies (REMARK)” guidelines. With no existing Stage-I-specific prognostic tools, a biomarker panel associated with 1-year survival in patients with Stage I liver cancer is a potential candidate for rigorous external validation. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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16 pages, 21309 KB

Open AccessArticle

Comprehensive Transcriptomic Analysis and Biomarker Prioritization of Hydroxyprogesterone in Breast Cancer

by Abdallah Rafi, Şükrü Tüzmen, Osman Uğur Sezerman and Fikret Dirilenoğlu

Curr. Issues Mol. Biol. 2026, 48(1), 108; https://doi.org/10.3390/cimb48010108 - 20 Jan 2026

Viewed by 942

Abstract

Hydroxyprogesterone (HP) is a synthetic progestogen widely used in obstetric care, and its potential influence on breast cancer biology has become an emerging area of interest. Despite its clinical use, the molecular mechanisms by which HP affects tumor tissue remain insufficiently explored. In this study, transcriptomic profiling was performed to investigate gene expression changes associated with HP in operable breast cancer. Pre-operative 17α-HP caproate (17-OHPC) exposure was associated, in normal adjacent tissue (NAT), with activation of steroid-hormone and lipid/xenobiotic-metabolism programs and crosstalk to phosphoinositide 3-kinase (PI3K)–Akt and nuclear factor kappa B (NF-κB). In NAT, these pathways showed the largest absolute log₂ fold-change (|log₂FC|); significance is reported as false discovery rate (FDR) throughout (e.g., FKBP5↑ with HP). In tumor tissue, the dominant signal reflected tight-junction/apical-junction and extracellular matrix (ECM)-receptor remodeling (e.g., CLDN4↑). We prioritized FKBP5 (HP pharmacodynamics) and CLDN4 (tumor baseline) as the main candidates; TSPO and SGK1 are reported as exploratory. This discovery-level, hypothesis-generating analysis nominates candidate biomarkers and pathway signals for prioritization and evaluation in independent datasets and future studies. These findings provide mechanistic insight into HP’s molecular effects in breast cancer and suggest potential applications in biomarker perioperative management. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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14 pages, 633 KB

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Genomic Landscape of Thymic Carcinoma: A Large-Scale Analysis of Somatic Mutations, Demographic Disparities, and Metastatic Drivers from the AACR Project GENIE^® Cohort

by Aden V. Chudziak, Tyson J. Morris, David Maliy, Grace S. Saglimbeni, Akaash Surendra, Beau Hsia, Huijun Li and Abubakar Tauseef

Curr. Issues Mol. Biol. 2026, 48(1), 90; https://doi.org/10.3390/cimb48010090 - 16 Jan 2026

Viewed by 1470

Abstract

Thymic carcinoma (TC) is a rare and aggressive malignancy with poor prognosis, and its genomic landscape remains incompletely defined. Identifying the somatic alterations that shape TC biology is essential for improving diagnostic precision, developing targeted therapies, and informing early detection strategies. We performed a retrospective genomic analysis of 141 TC tumor specimens from 134 patients using de-identified data from the American Association for Cancer Research (AACR) Project GENIE^® database. Somatic mutations and copy number alterations (CNAs) were characterized, and statistical analyses were conducted to evaluate associations with patient demographics (sex, race) and tumor site (primary vs. metastatic). The cohort was predominantly male (56.7%) and White (56.7%). The most frequently altered genes were TP53 (27.7%), CYLD (17.6%), and CDKN2A (12.1%). Recurrent homozygous deletions at chromosome 9p21.3 involving CDKN2A and CDKN2B were common. Sex-stratified analysis revealed several significant male-specific alterations. Although the Pacific Islander subgroup was small (n = 2), preliminary analysis suggested enrichment of alterations in key cancer-associated genes, including TP53, BRCA1, and STAT5B, underscoring the need for diverse representation in TC genomics. Notably, MTOR mutations were significantly enriched in a subset of local recurrences and lymph node metastases (n = 3; q = 0.013), suggesting a potential role in disease progression. This large-scale genomic analysis reinforces the central involvement of TP53, cell-cycle control, and chromatin-modifying pathways in TC. The identification of sex-associated and race-associated mutational patterns, together with the enrichment of MTOR alterations in recurrent and metastatic disease, highlights biologically plausible mechanisms of progression and potential therapeutic vulnerabilities. These findings support the value of comprehensive genomic profiling in TC and emphasize the need for prospective, multi-omic studies to validate these observations and guide the development of more personalized treatment strategies. Full article

(This article belongs to the Special Issue Linking Genomic Changes with Cancer in the NGS Era, 3rd Edition)

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