Integration of cytogenetic aberrations and in silico pathway enrichment identifies novel candidate genes in esophageal squamous cell carcinoma

Abstract

BACKGROUND

Chromosomal instability, the dominant form of genomic instability in solid tumors, is defined as a high rate of chromosome missegregation caused by errors in mitosis. A high frequency of chromosomally relevant genomic alterations has been seen in esophageal cancer (EC), which is the leading cause of cancer death worldwide including India. For the identification of risk genes and pathways involved in EC, chromosomal analysis of esophageal squamous cell carcinoma (ESCC) could give insights into the genes involved in EC.

AIM

To identify candidate genes associated with ESCC by integrating cytogenetic aberrations detected in peripheral blood lymphocytes with in silico network analysis followed by validation using The Cancer Genome Atlas (TCGA) tumor datasets.

METHODS

Cytogenetic analysis was performed in 135 patients with EC (59 males and 76 females) and 135 controls (59 males and 76 females) on cultured peripheral blood lymphocytes. Recurrent cytobands were mapped to resident genes and analyzed using Reactome functional interaction network analysis to identify prioritized linker genes and enriched pathways from Cytoscape software version 3.7.1. Independent validation was conducted using TCGA ESCC cohort via cBioPortal to assess genomic alterations, copy number changes, gene-dosage effects, and co-expression patterns.

RESULTS

Patients with ESCC demonstrated significantly increased chromosomal aberration frequency compared with controls (P = 0.0001), with aberration burden increasing across clinical stages. Network analysis identified biologically relevant linker genes including TP53, STAT3, MAL, AR, and JUP. Pathway enrichment analysis highlighted RNA polymerase II-associated transcriptional regulation. In TCGA ESCC cohort (n = 184), alterations in at least one cytogenetically derived candidate gene were observed in 171 tumors (93%). TP53 represented the most frequently altered gene (84%), while recurrent copy number gains involved STAT3 and MAPK3 and deletions affected WWOX. Copy number alterations demonstrated concordant gene-dosage effects. Co-expression analysis revealed significant positive correlation between GATA2 and MAPK3 (Spearman ρ = 0.41, P < 0.001), supporting coordinated transcriptional regulation.

CONCLUSION

Peripheral chromosomal instability in patients with ESCC identifies recurrent genomic regions that corresponds to genomic alterations observed in ESCC tumors within TCGA datasets. These findings strengthen the mechanistic basis of cytogenetic analysis and represent an early step in the biomarker discovery continuum for ESCC risk stratification.

Key Words: Esophageal cancer; Cytogenetic analysis; Chromosomal aberrations; Genetic instability; Oncogenes; Pathway analysis

Core Tip: This study highlights the role of chromosomal instability in esophageal cancer. By analyzing 135 patients, researchers found significantly higher chromosomal aberrations compared to controls. In silico analysis identified key genes like signal transducer and activator of transcription 3 and tumor protein p53, plus 12 genes enriched in the RNA polymerase II pathway. These findings reveal new genetic markers, offering deeper insights into esophageal cancer development and progression.

INTRODUCTION

Cancer of the esophagus is among the top 10 most common cancers in world (Globocan, 2021)[1]. Esophageal cancer (EC) has a complex multistep process in which environmental, geographical, and genetic factors play a major role leading to a diverse incidence of EC among different geographical regions[2,3]. Genetic factors associated with esophageal carcinogenesis are chromosomal aneuploidy, allelic deletions, activation of oncogenes, and inactivation of tumor suppressor genes[4].

Genomic aberrations are the mechanisms leading to gene dysfunction, carcinogenesis, and tumor progression[5]. High frequency of chromosomally relevant genomic alterations has been seen in both esophageal adenocarcinoma and esophageal squamous cell carcinoma (ESCC)[6]. In esophageal carcinogenesis, the overexpression of many oncogenes, namely YES1, TYMS, HEC, TGIF, NCOA3, BTAK, DCR3, E2F1, MYC, EGFR, EGR2, CCND, FGF3/FGF4, EMS1, SAS, ERBB2, PDGFR1, BCL2, MDS1, and PRKCI, have been observed. Genomic losses leading to the deletion of known tumor suppressor genes CDKN2A, MTAP, and TP53 have been reported[7]. Still, as a search continues for more risk genes and pathways implicated in EC to identify novel targets for treatment, cytogenetic aberrations can be a source of genomic information. An average G band at 850 band level may have varying GC content and resolution of detection of chromosomal aberration can be approximately 5 Mb involving a region of DNA with multiple genes. Specific chromosomal aberrations have been identified as markers for the diagnosis and prognosis of solid tumors in different studies[6,8-11]. The identification of reliable biomarkers remains a cornerstone of precision oncology, bridging the gap between basic molecular biology and clinical intervention[12].

In the present study, we propose the use of a bioinformatics approach for the identification of functional networks and enriched pathways in EC based on the chromosomal regions that were observed to be frequently involved in cytogenetic anomalies in our study sample of patients with EC. The present study aims to find the key driven-genes and biological pathways in ESCC based on the cytogenetic aberrations data from subjects residing in Punjab, North-West India where EC is a leading site for cancer in both males and females (http://www.canceratlaspunjab.org).

MATERIALS AND METHODS

Study participants

The present case-control study included 135 patients with EC and 135 healthy control subjects. The study was conducted after due ethical clearance according to the tenets of the Declaration of Helsinki by the Institutional Ethics Committee of Guru Nanak Dev University, Amritsar, India. The preoperative patients with EC without a history of any other cancer or any treatment before sample collection were selected from Sri Guru Ram Das Institute of Medical Sciences and Research, (Amritsar, Punjab, India). Healthy controls, matched for age and sex but unrelated to patients, were selected from the same geographical region by random sampling. Information like age, sex, lifestyle, diet, family history, and disease history were recorded on a questionnaire after written informed consent from all the subjects. A 3-mL intravenous blood sample was collected in a heparin-coated vial from each subject.

Cytogenetic analysis

Peripheral blood lymphocyte culturing was done by standard 72-hours culturing method using phytohemagglutinin as mitogen[13]. G-banding was performed, and karyotyping was done following ISCN 2016[14]. For each subject, chromosomal aberrations were assessed in 50-100 metaphases, identified as numerical and structural, and counted. Chromosomal anomalies present in 2% or more than 2% of metaphases in an individual were considered as clonal anomalies[14].

In-silico analysis

The chromosomal regions that were frequently involved in cytogenetic anomalies in the present study were searched for the genes present in the regions using the Atlas of Genetics and Cytogenetics in Oncology and Haematology (http://atlasgeneticsoncology.org). The Reactome functional interaction (FI) plugin from Cytoscape software (version 3.7.1) was used to obtain FI networks and pathways from gene enrichment analysis on the genes that were present on the chromosomal regions that were frequently involved in cytogenetic anomalies in the present study. The procedure used for analysis has been detailed in our previous study (Supplementary material)[15].

Statistical analyses

The distribution of cytogenetic aberrations between patients and controls was performed using means and Standard Deviations. The t-test was used for the comparison of the cytogenetic abnormalities between patients with different stages. The statistically significant difference was considered at P < 0.05.

The Cancer Genome Atlas validation and co-expression analysis

To evaluate whether cytogenetically derived candidate genes correspond with tumor-specific genomic alterations, validation analysis was performed using publicly available ESCC datasets from The Cancer Genome Atlas (TCGA) via cBioPortal (https://www.cbioportal.org). TCGA Esophageal Squamous Cell Carcinoma (Firehose Legacy) cohort was queried for genomic alterations including mutations and copy number alterations. Copy number status was categorized as deep deletion, shallow deletion, diploid, gain, or amplification based on Genomic Identification of Significant Targets in Cancer thresholds. The mRNA expression (RNA Seq V2) data were analyzed to evaluate gene-dosage effects across copy number alterations categories. Co-expression analysis was performed using mRNA expression data within the same cohort, and correlation coefficients were calculated using Spearman’s rank correlation.

RESULTS

Cytogenetic analysis

Cytogenetic analysis of 135 patients with EC and 135 healthy controls was performed using peripheral blood lymphocyte culturing, and the different types of structural and numerical chromosomal aberrations observed were recorded. Structural aberrations included additions, acentric fragments, chromosome and chromatid break, chromatid and chromosome gap, deletions, endoreduplication, fission, marker chromosomes, premature centromeric division, pulverization, quadradials, ring chromosomes, Robertsonian translocations, telomeric associations and triradials. The frequency of acrocentric associations involving D and G group chromosomes was 52.75 ± 8.4 in patients with EC and 54.61 ± 9.8 in controls.

A significantly higher frequency of chromosomal aberrations was observed in patients with EC compared to controls (P < 0.0001; Table 1). Among the numerical aberrations, loss of chromosomes 6, 7, 15, 16, 17, 18, 19, 20, 21, 22, and X and Y were more frequent in EC patients whereas the loss of chromosomes 8, 9, 20, 22, X, and Y was more frequent in healthy controls. The gain of chromosomes 5, 8, 9, 10, 13, 14, 22, and X was more frequent in patients with EC whereas the frequency of gain in chromosomes 9, 10, 19, 21, and 22 was higher in control individuals. As the mean patient age was found to be 55 years old, a comparison was made between patients and controls with age greater than or less than 55 years old. The patients in both age groups had a higher frequency of aberrations as compared to controls (Supplementary Table 1).

Table 1 Cytogenetic aberrations in patients with esophageal cancer and controls, mean ± SD.

Item	Patients (n = 135)	Controls (n = 135)	P value
Mean (%) aberrant metaphases	27.45 ± 9.7	11.6 ± 4.1	< 0.0001
Mean (%) metaphases with structural aberrations	8.6 ± 5.7	4.7 ± 2.7	< 0.0001
Mean (%) metaphases with numerical aberrations	15.4 ± 7.1	5.8 ± 3.1	< 0.0001
Mean (%) metaphases with both structural and numerical aberrations	3.3 ± 2.7	2.3 ± 0.9	< 0.0001

A higher number of patients was observed in stage II (n = 41) and stage III (n = 51) whereas very few patients were observed in stage I (n = 8) and stage IV (n = 9), likely because of the late diagnosis and poor prognosis of the disease (Table 2). The mean and standard deviation of total aberrant metaphases in stage I (19.15 ± 4.62), stage II (25.52 ± 4.9), stage III (27.06 ± 8.73), and stage IV (33.7 ± 4.86) were higher in male patients with EC compared to male controls (10.53 ± 3.0). A higher frequency of mean (%) total aberrant metaphases (33.7 ± 4.86), total metaphases with structural anomalies (10.18 ± 4.39), total metaphases with numerical aberrations (16.35 ± 4.46), and total metaphases with both structural and numerical aberrations (4.83 ± 3.34) was observed in patients with stage IV disease compared to the other three stages. Mean (%) metaphases with structural and numerical aberrations showed a higher number in patients with stage IV (4.83 ± 3.34) disease.

Table 2 Stage wise comparison of chromosomal aberrations in males and female patients and in controls, mean ± SD.

Chromosomal aberration	Controls		Patients with esophageal cancer
			Stage I		Stage II		Stage III		Stage IV
	Males (n = 59)	Females (n = 76)	Males (n = 4)	Females (n = 4)	Males (n = 19)	Females (n = 22)	Males (n = 30)	Females (n = 21)	Males (n = 6)	Females (n = 3)
Mean (%) aberrant metaphases	10.53 ± 3.0	12.3 ± 4.7	19.15 ± 4.62	17.25 ± 4.90	25.52 ± 4.9	23.52 ± 8.4	27.06 ± 8.73	27.46 ± 9.00	33.7 ± 4.86	34.3 ± 3.8
P value	0.01a		0.59		0.36		0.87		0.75
Mean (%) metaphases with structural aberrations	4.6 ± 2.9	4.8 ± 2.5	12.07 ± 3.41	7.0 ± 3.60	7.35 ± 4.28	6.01 ± 6.24	8.17 ± 5.10	13.04 ± 13.81	10.18 ± 4.39	17.66 ± 3.29
P value	0.66		0.08		0.43		0.08		0.23
Mean (%) metaphases with numerical aberrations	4.9 ± 2.0	6.5 ± 3.8	9.07 ± 3.55	8.0 ± 2.73	15.82 ± 4.49	15.54 ± 5.86	15.55 ± 8.54	15.75 ± 8.79	16.35 ± 4.46	14.43 ± 0.80
P value	0.004b		0.64		0.89		0.93		0.49
Mean (%) metaphases with both structural and numerical aberrations	2.2 ± 1.1	2.4 ± 0.9	1.0 ± 0.0	3.0 ± 1.41	2.66 ± 1.34	2.33 ± 1.31	3.23 ± 1.62	3.45 ± 4.83	4.83 ± 3.34	2.6 ± 205
P value	0.24		-		0.43		0.81		0.33

^aP < 0.05.

^bP < 0.01.

A mosaic karyotype with both structural and numerical clonal chromosomal anomalies was observed in many EC patients. Clonal structural chromosomal anomalies were observed in nine patients with EC (Supplementary Table 2). Clonal numerical chromosomal anomalies were observed in 23 cases. The loss of chromosome 22 was observed in 6 cases, of chromosome 21 in 4 cases, and of chromosome 16 in 2 cases. Other clonal anomalies included loss of chromosomes 4, 5, 7, 10, 18, 19, and 20 in a single case each. Chromosome X was involved in both a clonal loss and gain in separate cases. Polymorphic structural variants of chromosomes 1, 9, 14, 16, 21 and 22 were found in 22 patients with EC; add(9)(q13) in 12 patients; 22stk+ in 4 patients; 21ps+, 16qh+, 14stk+, and 15stk+ in 1 subject each; 1qh+ and add(9)(q13) in 1 subject; and add(9)(q13) and 22stk+ in 1 subject.

In silico analysis

The list of genes present on the chromosome regions observed to be involved in aberrations in EC patients in the present study were retrieved from Atlas of Genetics and Cytogenetics in Oncology and Haematology and validated in TCGA ESCC cohort (Table 3). As majority of the patients (89.2%) in the present study had ESCC, FI analysis was performed to identify the linker genes involved in ESCC. The linker genes that were reported to be involved in ESCC in the present study were EGFR, STAT3, AR, JUP, MAL, and TP53 (Figure 1).

Figure 1 Hub gene interaction network of esophageal squamous cell carcinoma associated genes. Nodes represent genes and edges represent functional interactions. Node size corresponds to degree centrality highlighting major regulatory genes STAT3, TP53, MYC, EGFR, MAPK3, and AR.

Table 3 Prioritized candidate genes derived from recurrent cytobands and validated in The Cancer Genome Atlas esophageal squamous cell carcinoma cohort.

Gene	Cytoband	Functional role	TCGA alteration type	TCGA frequency (%)	Supporting evidence
TP53	17p13	Linker gene/tumor suppressor	Mutation	84%	Established ESCC driver
STAT3	17q21	Linker gene/signaling	Amplification	4%	Copy-number gene-dosage (increase)
MAPK3	16p11	Pathway gene/MAPK signaling	Amplification	2%	Copy-number gene-dosage (increase)
WWOX	16q23	Tumor suppressor	Deep deletion	36%	Copy-number gene-dosage (reduce)
JUP	17q21	Linker gene/adhesion	Mutation/copy number alterations	10%	Network hub connectivity
AR	Xq12	Linker gene/hormone signaling	Amplification	4%	Hormonal pathway involvement
GATA2	3q21	Pathway gene/transcription	Low-frequency alteration	7%	Significant co-expression (ρ = 0.41)
MAL	2q11	Linker gene/tumor suppressor	Deletion (low frequency)	2%	Silenced in ESCC (literature)
GALNT3	2q24	Linker gene/glycosylation	Low-frequency alteration	2%	Network connectivity

The Cancer Genome Atlas dataset: Esophageal squamous cell carcinoma (Firehose Legacy), n-184 tumors. ESCC: Esophageal squamous cell carcinoma; TCGA: The Cancer Genome Atlas.

Furthermore, pathway enrichment analysis found that NR3C2, GATA2, SOCS3, CAV1, ESR2, HDAC3, THBS1, HSPD1, SPP1, E2F4, MAPK3, and WWOX genes were enriched in the RNA polymerase II transcription pathway in the present study (Figure 2).

Figure 2  Functional interaction subnetwork showing the genes as highlighted in yellow that are enriched in the RNA polymerase II transcription pathway in esophageal cancer.

TCGA validation of cytogenetically derived genes

To evaluate whether cytogenetically identified loci correspond to tumor genomic architecture, candidate genes were interrogated in TCGA ESCC cohort using cBioPortal. Alterations in at least one cytogenetically derived gene were observed in 171 of 184 (93%) ESCC tumors in TCGA cohort (Figure 3). TP53 represented the most frequently altered gene (84%), while additional recurrent alterations included copy number gains involving STAT3 and MAPK3 and deletions affecting WWOX. These findings demonstrate substantial concordance between cytogenetically derived loci and genomic alterations present in ESCC tumors.

Figure 3 The Cancer Genome Atlas Validation of Cytogenetically Derived Genes in esophageal squamous cell carcinoma. A: OncoPrint demonstrating genomic alterations across The Cancer Genome Atlas esophageal squamous cell carcinoma tumors; B: Copy number-dependent expression changes for STAT3 and WWOX; C: Co-expression analysis showing significant correlation between GATA2 and MAPK3 (Spearman ρ = 0.41, P < 0.001).

Copy number alterations demonstrated gene-dosage effects, with progressive increases in expression observed in gain and amplification categories for STAT3 and MAPK3, and reduced expression in WWOX deletions. Co-expression analysis revealed significant positive correlation between GATA2 and MAPK3 (Spearman ρ = 0.41, P < 0.001), suggesting coordinated transcriptional regulation within RNA polymerase II-associated pathways.

DISCUSSION

Several epidemiological studies have reported that cytogenetic aberration frequency in peripheral blood lymphocytes was associated with higher cancer risk[16]. Comparative genomic hybridization analysis has reported increased frequency of chromosomal aberrations in peripheral blood lymphocytes in cancer patients as compared to controls along with an association with cancer stage[9]. While peripheral blood cytogenetic analysis does not directly represent tumor karyotypes, accumulating evidence suggests that systemic chromosomal instability (CIN) reflects underlying genomic vulnerability. In the present study, independent TCGA validation demonstrated that 171 of 184 ESCC tumors (93%) harbored alterations in at least one cytogenetically derived candidate gene, supporting concordance rather than equivalence between peripheral instability and tumor genomic architecture.

In the present study, the mean frequency of numerical aberrations was significantly higher in both male and female patients with EC compared to controls. Aberration burden increased progressively from stage I to stage IV, suggesting that cytogenetic instability parallels tumor progression and clonal expansion. These observations suggest that systemic CIN may represent an underlying genomic vulnerability predisposing to ESCC development. A higher frequency of chromosome loss as compared to gains was observed in patients with EC consistent with previous cytogenetic studies in patients with ESCC[16-19]. Polyploid metaphases were also observed in many of the patients in the present study, which was probably because more patients had presented at a later stage (II or III) of EC. Aneuploid cancers are reportedly susceptible to metastasis, resistant to therapy, and have a low survival rate[20-22]. Multiple chromosomal loci have been reported to be involved in the development and progression of EC in eleven studies[7,8,10,11,17,18,23-27].

In silico analysis

Integration of cytogenetic breakpoints with Reactome FI analysis identified linker genes including TP53, STAT3, AR, JUP, MAL, and GALNT3. Pathway enrichment demonstrated convergence on RNA polymerase II-mediated transcriptional regulation. Because cytogenetic G-band resolution encompasses multi-gene regions (approximately 5 Mb), additional filtering steps were applied to enhance biological specificity. Genes were prioritized based on (1) FI network connectivity in Reactome FI; (2) Pathway enrichment significance; and (3) Independent validation of genomic alterations in TCGA ESCC cohort.

The observed genes are frequently constitutively activated in many human cancers[28-31]. Tumorigenic STAT3 activation has been frequently linked to more malignant cancer behaviors, including growth, epithelial-mesenchymal transition, migration, invasion, and metastasis and also with tumor survival and therapeutic resistance[29]. TP53 mutations are among the most frequent in solid tumors including hematological malignancies, gastric, colorectal, and ovarian cancers, occurring at earlier ages than in the general population[32,33]. Importantly, enrichment was not interpreted in isolation; TCGA validation demonstrated copy number–associated gene-dosage effects in STAT3 and MAPK3 and coordinated expression between GATA2 and MAPK3, anchoring pathway enrichment within tumor-specific transcriptional dysregulation. While TCGA dataset provides a robust framework for large-scale genomic correlation, we acknowledge its inherent limitations. These include potential selection biases in the patient cohorts and the cross-sectional nature of the data, which reflects a single time point in tumor evolution. Furthermore, as TCGA data primarily focuses on the tumor genomic architecture, interpreting its relationship with peripheral cytogenetic markers requires caution. By acknowledging these interpretational constraints, we aim to provide a more grounded basis for our claims regarding the link between peripheral instability and tumor biology.

RNA polymerase II transcription pathway has been explored in different studies and found to be involved in different cancers[34]. The Paf1 complex also plays a role in mRNA processing and maturation, being responsible for maintaining proper poly(A) tail length[35]. Regulators of post-initiation stages of transcription, particularly components of RNA polymerase II super elongation complexes, are recurrently mutated in cancer, particularly in hematological malignancies through translocation with the mixed lineage leukemia family of transcription factors[36]. Down regulation of WWOX expression in several cancer cell lines has been found, including tumors of the pancreas, prostrate[37], breast, lung, and bladder[38,39]. While our network analysis identified hub genes such as STAT3 and TP53 based on high connectivity, it is important to note that network centrality alone does not definitively confirm biological dependency. These results provide a computational framework identifying candidate nodes that warrant future functional validation through targeted perturbation studies, such as CRISPR-based interference, to confirm their role in driving ESCC network behavior.

Taken together, these observations suggest that cytogenetically derived loci may converge on transcriptional regulatory programs relevant to ESCC biology. Several of the identified genes, including STAT3, MAPK3, and GATA2, participate in signaling pathways that ultimately regulate RNA polymerase II-mediated transcription. Amplification of STAT3 and MAPK3 observed in TCGA datasets may therefore contribute to enhanced transcriptional activation of oncogenic programs, while coordinated expression between GATA2 and MAPK3 suggests regulatory interaction within transcriptional networks. These findings provide a plausible mechanistic link between systemic CIN and dysregulated transcriptional programs observed in ESCC. Enrichment analysis suggested an association with RNA polymerase II regulation; however, this remains an in-silico prediction. Future orthogonal validation, such as assessing RNA polymerase II phosphorylation status (e.g., Ser2/Ser5) in patient-derived models, would be required to confirm this mechanistic axis. Similarly, the observed co-expression between GATA2 and MAPK3 suggests coordinated expression rather than a confirmed regulatory linkage, as direct interaction would require further validation through chromatin immunoprecipitation or similar assays.

Independent validation using TCGA ESCC cohort (Firehose Legacy dataset) revealed genomic alterations affecting 93% of ESCC tumors, supporting concordance between systemic cytogenetic instability and tumor genomic architecture. TP53 was altered in 84% of cases. Copy number gains in STAT3 and MAPK3 demonstrated gene-dosage effects, while WWOX showed recurrent deletions. Co-expression analysis revealed significant correlation between GATA2 and MAPK3 (Spearman ρ = 0.41, P < 0.001). These findings demonstrate concordance between peripheral CIN and tumor genomic architecture, positioning cytogenetic instability as a potential early biomarker signal requiring prospective validation. From a translational perspective, cytogenetic instability may represent an upstream biomarker signal within the cancer biomarker discovery sequence. As conceptualized in “Bridging discovery and treatment: Cancer biomarker,” candidate markers require sequential validation across discovery, analytical validation, clinical validation, and clinical utility phases. The present study contributes to the discovery phase by linking systemic CIN with tumor genomic alterations in ESCC. Looking forward, the translation of these specific gene aberrations into non-invasive diagnostic tools, such as liquid biopsies, holds significant promise. Emerging strategies provide a technical template for how the ESCC-related mutations identified[40] could be adapted into highly sensitive circulating tumor DNA-based detection assays for early diagnosis or monitoring.

CONCLUSION

This study demonstrates that peripheral CIN in patients with ESCC identifies recurrent cytogenetic regions harboring biologically relevant genes. Independent validation using TCGA ESCC datasets revealed genomic alterations and gene-dosage effects affecting 93% of tumors, supporting concordance between systemic cytogenetic instability and tumor-specific genomic architecture.

While these findings originate from peripheral cytogenetic signals, they represent an important early step in the biomarker discovery continuum. By linking recurrent chromosomal aberrations with tumor genomic alterations and coordinated transcriptional programs, our study bridges the gap between cytogenetic observation and translational relevance. These recurrent genomic regions may therefore represent candidate systemic markers for ESCC risk stratification.

Despite the significant correlations observed in this study, several limitations remain. Our reliance on TCGA datasets introduces inherent selection biases and interpretational constraints common to large-scale genomic repositories. Furthermore, the prognostic utility of these alterations requires validation in independent prospective cohorts. The rigorous standard for such clinical links is exemplified by the study[41] on how mutations can influence clinical outcome which demonstrates the complexity of moving from genomic discovery to clinical prognosis.

Future investigations should focus on prospective validation and standardized assay development to determine whether peripheral CIN signatures could serve as non-invasive predictive markers, potentially identifying individuals with heightened genomic vulnerability prior to overt disease manifestation.

ACKNOWLEDGEMENTS

The authors would like to thank all study participants.