cfDNA Key genomic markers in HCV-Induced hepatocellular carcinoma in Egyptian patients.
1/5 보강
[BACKGROUND] Malignant liver disease is among the highest in the world, with hepatocellular carcinoma (HCC) accounting for up to 90 % of all cases.
APA
Khalifa M, Hmed AA, et al. (2025). cfDNA Key genomic markers in HCV-Induced hepatocellular carcinoma in Egyptian patients.. Journal, genetic engineering & biotechnology, 23(3), 100533. https://doi.org/10.1016/j.jgeb.2025.100533
MLA
Khalifa M, et al.. "cfDNA Key genomic markers in HCV-Induced hepatocellular carcinoma in Egyptian patients.." Journal, genetic engineering & biotechnology, vol. 23, no. 3, 2025, pp. 100533.
PMID
40854652 ↗
Abstract 한글 요약
[BACKGROUND] Malignant liver disease is among the highest in the world, with hepatocellular carcinoma (HCC) accounting for up to 90 % of all cases. In Egypt, HCC poses a significant public-health concern, representing 47.17 % of cancer cases. The high incidence of hepatitis C virus (HCV) in the Egypt was a major predisposing factor for HCC.
[MATERIAL] This study included 63 Egyptian HCC patients, 55 % of whom had a history of HCV infection.
[METHODS] Using a paired sampling strategy, approximately 2800 COSMIC mutations from 50 oncogenes and tumor-suppressor genes were NGS sequenced.
[RESULTS] Total of 381 somatic mutations were identified, 91 mutations detected in the HCC group and 291 in the HCV-related HCC group. The top 10 mutated genes in the non-HCV group were TP53, ATM, EGFR, CDH1, FGFR1, MET, SMAD4, ERBB2, FLT3, and FBXW7, while in the HCV-related HCC group, genes were KIT, ATM, TP53, APC, FBXW7, KDR, RB1, SMAD4, EGFR, and PIK3CA.
[CONCLUSION] The present study represents the first comprehensive somatic mutation profile in HCC Egyptian patients. This finding suggests that HCV viral infection played a direct and indirect role in increasing the somatic mutation burden in HCV-related HCC patients and opens new promises of targeted therapies for those patients.
[MATERIAL] This study included 63 Egyptian HCC patients, 55 % of whom had a history of HCV infection.
[METHODS] Using a paired sampling strategy, approximately 2800 COSMIC mutations from 50 oncogenes and tumor-suppressor genes were NGS sequenced.
[RESULTS] Total of 381 somatic mutations were identified, 91 mutations detected in the HCC group and 291 in the HCV-related HCC group. The top 10 mutated genes in the non-HCV group were TP53, ATM, EGFR, CDH1, FGFR1, MET, SMAD4, ERBB2, FLT3, and FBXW7, while in the HCV-related HCC group, genes were KIT, ATM, TP53, APC, FBXW7, KDR, RB1, SMAD4, EGFR, and PIK3CA.
[CONCLUSION] The present study represents the first comprehensive somatic mutation profile in HCC Egyptian patients. This finding suggests that HCV viral infection played a direct and indirect role in increasing the somatic mutation burden in HCV-related HCC patients and opens new promises of targeted therapies for those patients.
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Introduction
1
Introduction
Hepatocellular carcinoma (HCC) is a common and deadly cancer worldwide, ranking sixth in incidence and fourth in mortality.1 Hepatocellular carcinoma can develop in a number of preexisting conditions, such as cirrhosis, whether alcoholic or nonalcoholic, and hepatitis B and C. HCC usually develops in the context of preexisting conditions such as hepatitis B and C, as well as cirrhosis caused by alcohol and nonalcohol. Sadly, the outlook for HCC patients is usually bleak because the illness is frequently diagnosed at a later stage. This is especially true in places like Egypt, which has the highest rate of hepatitis C virus (HCV) in the world due to a severe epidemic that has impacted 10–15 % of its population over the past thirty years. Approximately 70 % of patients with hepatitis C virus (HCV) go on to develop chronic hepatitis, with 15–30 % of these patients developing cirrhosis within 20 years.2 The yearly incidence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis from HCV is reported to be between 1 % and 4 %. However, this rate increases to between 3 % and 8 % in patients with cirrhosis related to HCV, which is frequently associated with nonalcoholic fatty liver disease (NASH).3 In cirrhosis patients without HCV, the rate of HCC is significantly lower, at 1–2 %. However, recent developments in antiviral treatment, especially direct-acting antivirals (DAAs), have resulted in a sustained viral response (SVR) in the majority of HCV patients, raising the possibility of better results going forward. It is generally accepted that the removal of HCV significantly affects the development of HCC. However, it is important to recognize that some patients may still experience a recurrence of HCC even after attaining a sustained virologic response.[4], [5] The hepatitis C virus (HCV) is an RNA virus that belongs to the Flaviviridae family. It consists of a single-stranded RNA that encodes a 3,000-amino-acid protein. This protein is proteolyzed to produce both structural and nonstructural proteins. The core, envelope E1, and E2 proteins are structural proteins that are essential for shaping the virus and for the host cell entry processes.6 Nonstructural proteins, specifically P1, NS2, NS3, NS4A, NS4B, NS5A, and NS5B, are involved in the mechanism of viral replication and subsequent liver damage.7 HCV's genome is highly variable, with at least seven genotypes and a large number of subtypes discovered to date. Genotypes 1, 3, and 6 have been seen to be linked to an increased prevalence of cirrhosis or HCC, as well as poorer clinical outcomes compared to other genotypes, among these.[8], [9] Chronic HCV infection causes hepatocarcinogenesis, which is a complicated and multifactorial process. The interaction of direct and indirect mechanisms leads to oncogenic microenvironments characterized by cirrhosis. Within these microenvironments, viral protein structures function as promoters of malignant degeneration.10 The development of hepatocellular carcinoma (HCC) caused by hepatitis C virus (HCV) infection has been a gradual process over 20–40 years.11 Virus-induced factors mediate HCV carcinogenesis, while post-HCV tumor necrosis factor, interferon, and chronic inflammation mediate the host immunological response.12 Mutations that transform hepatocytes into malignant cells are linked to the cell cycle. The genes that are most commonly mutated in HCC are telomerase reverse transcriptase, tumor protein 53, and β-catenin. The minimally invasive examination of circulating cancer-associated biomarkers, such as circulating nucleic acids, circulating tumor cells, miRNAs, and exosomes—often known as liquid biopsy—has a variety of potential clinical uses.13 Among these, the evaluation of cfDNA shows the most promise in HCC at the moment. Circulating cfDNA refers to fragments of DNA found in both healthy people and cancer patients.14 The majority of cell-free DNA (cfDNA) is made up of DNA that has been released by normal lymphoid and myeloid cells. Less than 1 % of the total cfDNA in cancer patients is made up of tumor-derived cfDNA (cftDNA). Circulating cfDNA fragments are mostly found in plasma or serum as double-stranded molecules. In addition, these pieces are often more than 167 base pairs long.15 This dimension's magnitude is similar to the amount of cooling that occurs around a single nucleosome, which protects against DNA degradation by blood nucleases.16 In contrast, circulating tumor DNA (ctDNA) fragments, which are released by necrotic or apoptotic tumor cells, are typically less than 150 base pairs long. Tumor-specific sequences can be identified using these differences in size, together with changes in sequence or epigenetic changes.14 In fact, next-generation sequencing (NGS) and targeted PCR-based methods can detect cancer-specific alterations in cftDNA.17 Circulating free tumor DNA (cftDNA) has been shown in prior research to have molecular characteristics that are typical of the genomic DNA of malignant cells, such as point mutations and changes in methylation patterns. These features suggest the molecular diversity that can occur within a cancer, which may be made up of different tumor clones and metastases.18 The noninvasive technique that involves cftDNA sampling in liquid biopsy is particularly intriguing because it can overcome the limitations of traditional tissue biopsy and offer a real-time temporal representation of clonal evolution.19 The potential clinical use of cftDNA for HCC detection, disease monitoring, and prognosis has been studied.20
In the present investigation, a comparison was made between the somatic mutation signature derived from circulating free tumor DNA (cftDNA) of hepatocellular carcinoma (HCC) patients with no prior history of hepatitis C virus (HCV) and that of HCV-related HCC patients. The aim was to discern the dissimilarities between the two cohorts and to identify the most significantly altered gene pathways in each group.
Introduction
Hepatocellular carcinoma (HCC) is a common and deadly cancer worldwide, ranking sixth in incidence and fourth in mortality.1 Hepatocellular carcinoma can develop in a number of preexisting conditions, such as cirrhosis, whether alcoholic or nonalcoholic, and hepatitis B and C. HCC usually develops in the context of preexisting conditions such as hepatitis B and C, as well as cirrhosis caused by alcohol and nonalcohol. Sadly, the outlook for HCC patients is usually bleak because the illness is frequently diagnosed at a later stage. This is especially true in places like Egypt, which has the highest rate of hepatitis C virus (HCV) in the world due to a severe epidemic that has impacted 10–15 % of its population over the past thirty years. Approximately 70 % of patients with hepatitis C virus (HCV) go on to develop chronic hepatitis, with 15–30 % of these patients developing cirrhosis within 20 years.2 The yearly incidence of hepatocellular carcinoma (HCC) in patients with chronic hepatitis from HCV is reported to be between 1 % and 4 %. However, this rate increases to between 3 % and 8 % in patients with cirrhosis related to HCV, which is frequently associated with nonalcoholic fatty liver disease (NASH).3 In cirrhosis patients without HCV, the rate of HCC is significantly lower, at 1–2 %. However, recent developments in antiviral treatment, especially direct-acting antivirals (DAAs), have resulted in a sustained viral response (SVR) in the majority of HCV patients, raising the possibility of better results going forward. It is generally accepted that the removal of HCV significantly affects the development of HCC. However, it is important to recognize that some patients may still experience a recurrence of HCC even after attaining a sustained virologic response.[4], [5] The hepatitis C virus (HCV) is an RNA virus that belongs to the Flaviviridae family. It consists of a single-stranded RNA that encodes a 3,000-amino-acid protein. This protein is proteolyzed to produce both structural and nonstructural proteins. The core, envelope E1, and E2 proteins are structural proteins that are essential for shaping the virus and for the host cell entry processes.6 Nonstructural proteins, specifically P1, NS2, NS3, NS4A, NS4B, NS5A, and NS5B, are involved in the mechanism of viral replication and subsequent liver damage.7 HCV's genome is highly variable, with at least seven genotypes and a large number of subtypes discovered to date. Genotypes 1, 3, and 6 have been seen to be linked to an increased prevalence of cirrhosis or HCC, as well as poorer clinical outcomes compared to other genotypes, among these.[8], [9] Chronic HCV infection causes hepatocarcinogenesis, which is a complicated and multifactorial process. The interaction of direct and indirect mechanisms leads to oncogenic microenvironments characterized by cirrhosis. Within these microenvironments, viral protein structures function as promoters of malignant degeneration.10 The development of hepatocellular carcinoma (HCC) caused by hepatitis C virus (HCV) infection has been a gradual process over 20–40 years.11 Virus-induced factors mediate HCV carcinogenesis, while post-HCV tumor necrosis factor, interferon, and chronic inflammation mediate the host immunological response.12 Mutations that transform hepatocytes into malignant cells are linked to the cell cycle. The genes that are most commonly mutated in HCC are telomerase reverse transcriptase, tumor protein 53, and β-catenin. The minimally invasive examination of circulating cancer-associated biomarkers, such as circulating nucleic acids, circulating tumor cells, miRNAs, and exosomes—often known as liquid biopsy—has a variety of potential clinical uses.13 Among these, the evaluation of cfDNA shows the most promise in HCC at the moment. Circulating cfDNA refers to fragments of DNA found in both healthy people and cancer patients.14 The majority of cell-free DNA (cfDNA) is made up of DNA that has been released by normal lymphoid and myeloid cells. Less than 1 % of the total cfDNA in cancer patients is made up of tumor-derived cfDNA (cftDNA). Circulating cfDNA fragments are mostly found in plasma or serum as double-stranded molecules. In addition, these pieces are often more than 167 base pairs long.15 This dimension's magnitude is similar to the amount of cooling that occurs around a single nucleosome, which protects against DNA degradation by blood nucleases.16 In contrast, circulating tumor DNA (ctDNA) fragments, which are released by necrotic or apoptotic tumor cells, are typically less than 150 base pairs long. Tumor-specific sequences can be identified using these differences in size, together with changes in sequence or epigenetic changes.14 In fact, next-generation sequencing (NGS) and targeted PCR-based methods can detect cancer-specific alterations in cftDNA.17 Circulating free tumor DNA (cftDNA) has been shown in prior research to have molecular characteristics that are typical of the genomic DNA of malignant cells, such as point mutations and changes in methylation patterns. These features suggest the molecular diversity that can occur within a cancer, which may be made up of different tumor clones and metastases.18 The noninvasive technique that involves cftDNA sampling in liquid biopsy is particularly intriguing because it can overcome the limitations of traditional tissue biopsy and offer a real-time temporal representation of clonal evolution.19 The potential clinical use of cftDNA for HCC detection, disease monitoring, and prognosis has been studied.20
In the present investigation, a comparison was made between the somatic mutation signature derived from circulating free tumor DNA (cftDNA) of hepatocellular carcinoma (HCC) patients with no prior history of hepatitis C virus (HCV) and that of HCV-related HCC patients. The aim was to discern the dissimilarities between the two cohorts and to identify the most significantly altered gene pathways in each group.
Materials and methods
2
Materials and methods
2.1
Patients
A total of 35 (55 %) patients with HCV-related HCC and 28 (45 %) patients with non-HCV-related HCC were included in this study. The Barcelona Clinic Liver Cancer (BCLC) staging system was used to evaluate the included HCC patients. Both groups were age- and sex-matched. Samples were collected from national liver institutes in the Cairo and Menoufia governorates from Jan 2021 until February 2022. Ethical approval was obtained from the National Liver Institute Board (NLI IRB No. 232/2020).
2.2
Sample collection
After providing informed consent, a total volume of 9 ml of EDTA blood was collected in three 3 ml tubes from each patient. The samples were separated immediately into plasma and buffy coats. The plasma was stored at −80 °C for further cftDNA isolation, and the buffy coat was stored at −20 °C for genomic DNA isolation.
2.3
DNA extraction
2.3.1
Genomic DNA isolation
Genomic DNA was extracted from isolated buffy coats using a Thermo Fisher GeneJET Genomic DNA Purification Kit (CatNo. K0721, USA) according to the manufacturer’s guidelines. The isolated DNA was then quantified and quantified by a Qubit-3 fluorometer using a Qubit dsDNA BR (Broad Range) Assay Kit (CatNo. Q32850, USA).
2.3.2
cftDNA isolation
cftDNA was isolated from plasma samples using a QIAamp Circulating Nucleic Acid Kit (Cat. No./ID: 55114, Germany) according to the manufacturer’s protocol. The isolated cftDNA was then quantified and quantified by a Qubit-3 fluorometer using high-sensitivity dsDNA quantitation (CatNo. Q32851, USA).
2.4
NGS library preparation
AmpliSeq for Illumina Cancer HotSpot Panel v2 along with the AmpliSeq Library PLUS kit were used for library generation according to the manufacturer’s instructions. Two libraries were prepared per patient, one for the genomic DNA and the other for the cftDNA sample. Amplified libraries were indexed and then quantified and qualified using an Agilent High Sensitivity DNA Kit on an Agilent Bioanalyzer 2100.
2.5
Sequencing
Libraries were pooled according to their molar ratios where the cftDNA was 5 times the genomic DNA library to yield at least 60X and 500X depth of coverage for genomic DNA and cftDNA, respectively. Then, the final library pool was diluted according to the manufacturer’s instructions for MiSeq sequencing. The library pools were loaded into flow cells, and paired-end sequencing was started using 2 × 75 for the cftDNA samples and 2 × 151 for the genomic DNA samples.
2.6
Bioinformatics analysis
The resulting fastq files were filtered and aligned to the human genome reference hg19 using BWA-MEM, and the resulting BAM files were subsequently used to generate VCF files via the Strelka2 germline and somatic small variant caller. The resulting VCFs were then annotated, filtered and enriched using the locally installed OpenCRAVAT server.
Materials and methods
2.1
Patients
A total of 35 (55 %) patients with HCV-related HCC and 28 (45 %) patients with non-HCV-related HCC were included in this study. The Barcelona Clinic Liver Cancer (BCLC) staging system was used to evaluate the included HCC patients. Both groups were age- and sex-matched. Samples were collected from national liver institutes in the Cairo and Menoufia governorates from Jan 2021 until February 2022. Ethical approval was obtained from the National Liver Institute Board (NLI IRB No. 232/2020).
2.2
Sample collection
After providing informed consent, a total volume of 9 ml of EDTA blood was collected in three 3 ml tubes from each patient. The samples were separated immediately into plasma and buffy coats. The plasma was stored at −80 °C for further cftDNA isolation, and the buffy coat was stored at −20 °C for genomic DNA isolation.
2.3
DNA extraction
2.3.1
Genomic DNA isolation
Genomic DNA was extracted from isolated buffy coats using a Thermo Fisher GeneJET Genomic DNA Purification Kit (CatNo. K0721, USA) according to the manufacturer’s guidelines. The isolated DNA was then quantified and quantified by a Qubit-3 fluorometer using a Qubit dsDNA BR (Broad Range) Assay Kit (CatNo. Q32850, USA).
2.3.2
cftDNA isolation
cftDNA was isolated from plasma samples using a QIAamp Circulating Nucleic Acid Kit (Cat. No./ID: 55114, Germany) according to the manufacturer’s protocol. The isolated cftDNA was then quantified and quantified by a Qubit-3 fluorometer using high-sensitivity dsDNA quantitation (CatNo. Q32851, USA).
2.4
NGS library preparation
AmpliSeq for Illumina Cancer HotSpot Panel v2 along with the AmpliSeq Library PLUS kit were used for library generation according to the manufacturer’s instructions. Two libraries were prepared per patient, one for the genomic DNA and the other for the cftDNA sample. Amplified libraries were indexed and then quantified and qualified using an Agilent High Sensitivity DNA Kit on an Agilent Bioanalyzer 2100.
2.5
Sequencing
Libraries were pooled according to their molar ratios where the cftDNA was 5 times the genomic DNA library to yield at least 60X and 500X depth of coverage for genomic DNA and cftDNA, respectively. Then, the final library pool was diluted according to the manufacturer’s instructions for MiSeq sequencing. The library pools were loaded into flow cells, and paired-end sequencing was started using 2 × 75 for the cftDNA samples and 2 × 151 for the genomic DNA samples.
2.6
Bioinformatics analysis
The resulting fastq files were filtered and aligned to the human genome reference hg19 using BWA-MEM, and the resulting BAM files were subsequently used to generate VCF files via the Strelka2 germline and somatic small variant caller. The resulting VCFs were then annotated, filtered and enriched using the locally installed OpenCRAVAT server.
Results
3
Results
AmpliSeq for Illumina Cancer HotSpot Panel v2 was used to enrich 2800 COSMIC mutations from 50 oncogenes and tumor suppressor genes in all patient samples using a paired (normal/tumor) sampling strategy to determine the somatic origin of the detected mutations. Among those 50 genes, 45 had somatic mutation events. A total of 381 somatic mutations were detected, 91 of which were detected in the non-HCV-related HCC group and 291 of which were detected in the HCV-related HCC group. The top 10 mutated genes in the non-HCV-related HCC group were TP53, ATM, EGFR, CDH1, FGFR1, MET, SMAD4, ERBB2, FLT3 and FBXW7, while in the HCV-related HCC group, the top 10 genes were KIT, ATM, TP53, APC, FBXW7, KDR, RB1, SMAD4, EGFR and PIK3CA, as shown in Fig. 1.
The majority of those mutations were missense variants with a frequency of 95 %, followed by stop gain mutations at 0.024 %, frameshift insertions at 0.008 %, splice site variants, inframe deletions at 0.003 % and start loss at 0.003 %, as shown in Fig. 2.
The number of detected mutations per gene varied from the non-HCV-related HCC group to the HCV-related HCC group, as shown in Fig. 3.
Results
AmpliSeq for Illumina Cancer HotSpot Panel v2 was used to enrich 2800 COSMIC mutations from 50 oncogenes and tumor suppressor genes in all patient samples using a paired (normal/tumor) sampling strategy to determine the somatic origin of the detected mutations. Among those 50 genes, 45 had somatic mutation events. A total of 381 somatic mutations were detected, 91 of which were detected in the non-HCV-related HCC group and 291 of which were detected in the HCV-related HCC group. The top 10 mutated genes in the non-HCV-related HCC group were TP53, ATM, EGFR, CDH1, FGFR1, MET, SMAD4, ERBB2, FLT3 and FBXW7, while in the HCV-related HCC group, the top 10 genes were KIT, ATM, TP53, APC, FBXW7, KDR, RB1, SMAD4, EGFR and PIK3CA, as shown in Fig. 1.
The majority of those mutations were missense variants with a frequency of 95 %, followed by stop gain mutations at 0.024 %, frameshift insertions at 0.008 %, splice site variants, inframe deletions at 0.003 % and start loss at 0.003 %, as shown in Fig. 2.
The number of detected mutations per gene varied from the non-HCV-related HCC group to the HCV-related HCC group, as shown in Fig. 3.
Discussion
4
Discussion
Hepatocellular carcinoma (HCC) is the leading cause of mortality associated with liver disease on a global scale. Infection with the hepatitis C virus (HCV) is a significant contributor to the development of severe hepatic fibrosis and cirrhosis, which greatly increases the likelihood of HCC onset. The incidence of HCV-related HCC morbidity and mortality has increased as the incidence of HCV-induced cirrhosis continues to increase.21 To date, there is no clear understanding of the disparities between HCV-related and non-HCV-related HCC, particularly at the molecular level. Profiling of somatic mutations may serve as a valid approach to determine the molecular differences between the two groups. The genomic landscape of HCC is influenced by HCV infection, leading to regional variation in mutation rates and alterations in chromatin organization. Understanding these molecular pathways and genomic alterations is crucial for identifying potential therapeutic targets for HCC associated with HCV infection.
Based on the results obtained, out of the top 10 somatically mutated genes in each group, five genes were commonly mutated in both groups (TP53, ATM, EGFR, SMAD4, and FBXW7), while five genes differed per group. For the HCV-related HCC group, these genes were KIT, APC, KDR, RB1, and PIK3CA, while for the non-HCV-related HCC group, they were CDH1, FGFR1, MET, ERBB2, and FLT3. This difference in the top mutated genes may account for differences in tumorigenesis pathways. Additionally, there was a 2.5- to 3-fold increase in the somatic mutational burden in the HCV-related group compared to that in the non-HCV-related HCC group, which may explain the high morbidity rate of this particular HCC group.
Discussion
Hepatocellular carcinoma (HCC) is the leading cause of mortality associated with liver disease on a global scale. Infection with the hepatitis C virus (HCV) is a significant contributor to the development of severe hepatic fibrosis and cirrhosis, which greatly increases the likelihood of HCC onset. The incidence of HCV-related HCC morbidity and mortality has increased as the incidence of HCV-induced cirrhosis continues to increase.21 To date, there is no clear understanding of the disparities between HCV-related and non-HCV-related HCC, particularly at the molecular level. Profiling of somatic mutations may serve as a valid approach to determine the molecular differences between the two groups. The genomic landscape of HCC is influenced by HCV infection, leading to regional variation in mutation rates and alterations in chromatin organization. Understanding these molecular pathways and genomic alterations is crucial for identifying potential therapeutic targets for HCC associated with HCV infection.
Based on the results obtained, out of the top 10 somatically mutated genes in each group, five genes were commonly mutated in both groups (TP53, ATM, EGFR, SMAD4, and FBXW7), while five genes differed per group. For the HCV-related HCC group, these genes were KIT, APC, KDR, RB1, and PIK3CA, while for the non-HCV-related HCC group, they were CDH1, FGFR1, MET, ERBB2, and FLT3. This difference in the top mutated genes may account for differences in tumorigenesis pathways. Additionally, there was a 2.5- to 3-fold increase in the somatic mutational burden in the HCV-related group compared to that in the non-HCV-related HCC group, which may explain the high morbidity rate of this particular HCC group.
Conclusion
5
Conclusion
Comprehending the molecular terrain of hepatocellular carcinoma (HCC) could facilitate the identification of more efficacious and individualized targeted therapies. The findings presented herein represent the initial all-encompassing somatic mutation profile in HCC patients from Egypt. The current results demonstrate that the somatic mutational load is greater in patients with HCV-associated HCC than in patients with HCC, implying that HCV viral infection exerts both direct and indirect influences on increasing the frequency of somatic mutations. This observation may suggest a threefold increase in the likelihood of developing HCC.
Conclusion
Comprehending the molecular terrain of hepatocellular carcinoma (HCC) could facilitate the identification of more efficacious and individualized targeted therapies. The findings presented herein represent the initial all-encompassing somatic mutation profile in HCC patients from Egypt. The current results demonstrate that the somatic mutational load is greater in patients with HCV-associated HCC than in patients with HCC, implying that HCV viral infection exerts both direct and indirect influences on increasing the frequency of somatic mutations. This observation may suggest a threefold increase in the likelihood of developing HCC.
Study limitations
6
Study limitations
This study has some limitations that warrant consideration. First, the relatively modest sample size may limit the generalizability of the findings to broader populations. Second, the analysis was confined to a targeted panel of 50 cancer-related genes, potentially overlooking mutations in other relevant genomic regions.
Study limitations
This study has some limitations that warrant consideration. First, the relatively modest sample size may limit the generalizability of the findings to broader populations. Second, the analysis was confined to a targeted panel of 50 cancer-related genes, potentially overlooking mutations in other relevant genomic regions.
Ethical approval declaration
Ethical approval declaration
Ethical approval was obtained from the IRB at National Liver Institute − Menoufia University, Egypt. (NLI IRB approval No. 232/2020)
Ethical approval was obtained from the IRB at National Liver Institute − Menoufia University, Egypt. (NLI IRB approval No. 232/2020)
Consent for publication’ section in the declarations
8
Consent for publication’ section in the declarations
Not applicable.
Consent for publication’ section in the declarations
Not applicable.
Availability of data and materials’/’data availability’
9
Availability of data and materials’/’data availability’
Data is not deposited because of a privacy/identification issue and the authors state that it’s available upon request submitted to Mohamed.khalifa@57357.org.
Availability of data and materials’/’data availability’
Data is not deposited because of a privacy/identification issue and the authors state that it’s available upon request submitted to Mohamed.khalifa@57357.org.
Human ethics and consent to participate declarations
10
Human ethics and consent to participate declarations
Full informed ethical consent was signed by each patient involved in this study after a detailed explanation about the study design and aims.
Human ethics and consent to participate declarations
Full informed ethical consent was signed by each patient involved in this study after a detailed explanation about the study design and aims.
Funding declaration
Funding declaration
This work was not received any funding and it’s fully self-funded.
This work was not received any funding and it’s fully self-funded.
CRediT authorship contribution statement
CRediT authorship contribution statement
Mohamed Khalifa: Writing – original draft, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation. Ahmed A. Hmed: Writing – review & editing. Khaled S. Elfeky: Writing – review & editing. Sayed Bakry: Writing – review & editing, Validation, Supervision, Methodology. Manal El Hamshary: Writing – review & editing, Supervision, Formal analysis, Conceptualization. Ahmed R. Sofy: Writing – review & editing, Supervision, Methodology, Data curation, Conceptualization.
Mohamed Khalifa: Writing – original draft, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation. Ahmed A. Hmed: Writing – review & editing. Khaled S. Elfeky: Writing – review & editing. Sayed Bakry: Writing – review & editing, Validation, Supervision, Methodology. Manal El Hamshary: Writing – review & editing, Supervision, Formal analysis, Conceptualization. Ahmed R. Sofy: Writing – review & editing, Supervision, Methodology, Data curation, Conceptualization.
Declaration of competing interest
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this manuscript.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this manuscript.
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