Impact of tumor mutation burden on the prognosis of patients with unresectable hepatocellular carcinoma undergoing transcatheter arterial chemoembolization combined with immunotherapy and anti-angiogenic drugs

Introduction

The management of hepatocellular carcinoma (HCC), one of the most prevalent and lethal forms of liver cancer, remains a significant challenge in oncology (1). HCC is the fourth leading cause of cancer-related deaths worldwide, characterized by late-stage diagnosis and a limited array of effective therapeutic options for advanced disease states. Advanced or unresectable HCC necessitates treatments that not only target the tumor but also modulate the host immune response, as traditional therapies alone often lead to suboptimal outcomes (2,3).

Transcatheter arterial chemoembolization (TACE) has long been the standard of care for intermediate-stage unresectable HCC. TACE works by occluding the blood supply to the tumor while delivering high doses of chemotherapy directly to the tumor site, thereby minimizing systemic exposure and enhancing local drug concentration (4,5). However, its efficacy is often hampered by the development of intra-tumoral hypoxia, which can foster an immune-suppressive microenvironment conducive to tumor progression and resistance. This necessitates the integration of additional therapeutic modalities to improve patient outcomes (6).

In recent years, immunotherapy has emerged as a promising avenue for cancer treatment, revolutionizing the management of various malignancies, including HCC (7). Immune checkpoint inhibitors, such as those targeting the programmed cell death protein 1 (PD-1) pathway, have demonstrated efficacy by enhancing T-cell mediated immune responses against tumors. Camrelizumab, a PD-1 inhibitor, has shown potential in reactivating cytotoxic T-cells and mediating anti-tumor effects, especially in tumors with higher immunogenicity. However, not all patients benefit uniformly from such therapies, highlighting the need to identify biomarkers that predict responsiveness (8).

Tumor mutation burden (TMB), a measure of the total number of mutations per megabase in a tumor genome, has surfaced as a potential biomarker for predicting response to immunotherapy (9). The rationale is that a higher TMB can lead to the generation of more neoantigens, which in turn might enhance tumor immunogenicity and improve the efficacy of immune checkpoint blockade. This association has been supported by studies across various cancer types, yet, its application in HCC remains under-explored (10).

The interplay between TMB and the tumor microenvironment presents a unique opportunity to tailor treatment strategies in unresectable HCC. When combined with TACE, immunotherapy can enhance anti-tumor immunity by counteracting the TACE-induced immune suppression. Additionally, anti-angiogenic drugs like lenvatinib or apatinib complement these effects by normalizing tumor vasculature, thereby facilitating immune cell infiltration and reducing immunosuppressive signals within the tumor microenvironment. The integration of these therapeutic modalities promises a synergistic approach, potentially improving the prognosis for patients with unresectable HCC (11).

While emerging evidence underlines the potential role of TMB in optimizing treatment strategies, there remains a significant gap in understanding its clinical implications in HCC specifically undergoing combined modality treatment. Our research seeks to address this gap by evaluating the prognostic significance of TMB in patients with unresectable HCC who were undergoing TACE combined with immunotherapy and anti-angiogenic therapy. We present this article in accordance with the REMARK reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-aw-930/rc).

Methods

Study design and patient selection

This study retrospectively analyzed 160 patients diagnosed with unresectable HCC, who received treatment through transarterial chemoembolization (TACE) combined with immunotherapy and anti-angiogenic drugs at The Affiliated Cangnan Hospital of Wenzhou Medical University between January 1, 2021, and January 1, 2025. Patients were initially stratified into two groups based on their clinical outcome at 12 months after the initiation of combination therapy, prior to any TMB analysis. The “good prognosis” group (n=89) was defined as patients who were alive without radiological disease progression (according to RECIST 1.1) at the 12-month timepoint. The “poor prognosis” group (n=71) included patients who had either died or exhibited radiological disease progression within 12 months of treatment initiation. This clinical endpoint-based stratification was used solely for the preliminary exploration of potential prognostic biomarkers, including TMB. Subsequently, the optimal tumor mutational burden (TMB) threshold was identified using ROC curve analysis, determined to be 10.025 mutations per megabase. Using this threshold, patients were further subdivided into a low TMB group (≤10.025 mutations per megabase, n=65) and a high TMB group (>10.025 mutations per megabase, n=95). A flowchart of patient selection is provided as Figure 1.

Figure 1 Patient selection flowchart. ECOG, Eastern Cooperative Oncology Group; HCC, hepatocellular carcinoma; TACE, transcatheter arterial chemoembolization; TMB, tumor mutation burden.

The study protocol received approval from the Institutional Review Board (IRB) of The Affiliated Cangnan Hospital of Wenzhou Medical University, under approval number: 2025055. Given its retrospective design, informed consent was waived due to the anonymized nature of the data. All patient records were treated with strict confidentiality, ensuring that no personally identifiable information was disclosed throughout the study. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Inclusion and exclusion criteria

Inclusion criteria

The study included patients diagnosed with unresectable HCC (12) who were treated with TACE in conjunction with immunotherapy and anti-angiogenic medications. Eligible participants were required to be 18 years of age or older and exhibit liver function classified as Child-Pugh A or B (13). Additionally, an Eastern Cooperative Oncology Group (ECOG) performance status score between 0 and 1 was necessary (14). Each participant had to have at least one measurable target lesion identified through imaging, and their clinical data needed to be comprehensive.

Exclusion criteria

Patients were excluded if they presented with diffuse tumor involvement or severe dysfunction in critical organs such as the heart, brain, lungs, or kidneys. The presence of coagulation abnormalities, concurrent malignancies other than HCC, severe portal hypertension, or decompensated cirrhosis was also criteria for exclusion. Complications related to decompensated cirrhosis, such as ascites, jaundice, hepatic encephalopathy, and esophageal and gastric variceal bleeding, further warranted exclusion from the study.

Treatment protocol

All patients were treated with a combination of TACE, immunotherapy, and anti-angiogenic drugs. The TACE procedure was conducted using the Seldinger technique, which involved puncturing the femoral artery and catheterizing the hepatic artery. Tumor-feeding arteries were identified through angiography, followed by superselective catheterization to reach the tumor vessels. The chemotherapy regimen included epirubicin (administered at 50 mg/m²), combined with lipiodol (5–20 mL, depending on the tumor’s size and vascularity), which was infused into the tumor vessels. This was succeeded by embolization with gelatin sponge particles. TACE sessions occurred every 6 to 8 weeks until either radiological evidence of progression or intolerable toxicity was observed.

Immunotherapy commenced within seven days following the initial TACE procedure, with camrelizumab being administered intravenously at a dose of 200 mg per infusion every three weeks, continuing until disease progression or unacceptable toxicity was reached. Anti-angiogenic therapy was also implemented, utilizing lenvatinib (dosed based on body weight at 8–12 mg/day orally) or apatinib (500 mg/day orally). This treatment started concurrently with immunotherapy and persisted until disease progression or the occurrence of severe adverse events.

Follow-up

Follow-up evaluations commenced 4 to 10 weeks following the completion of the final treatment and were then conducted every three months. The median follow-up period in this study was 30 months. These evaluations encompassed clinical assessments, laboratory tests, imaging studies, and quality-of-life assessments, with thorough documentation of any adverse events. Data were collected through outpatient and inpatient systems, records from external hospitals, and scheduled follow-up visits, ensuring comprehensive monitoring of patients’ survival status, disease progression, and response to treatment. The cutoff date for follow-up was January 1, 2025.

Data collection

Demographic and clinical data

Clinical data were gathered from electronic medical records and included demographic details [age, gender, and body mass index (BMI)], medical history (including smoking and alcohol use habits, etiology of HCC such as hepatitis B or C, and family history of the disease), as well as laboratory results, imaging reports, and treatment specifics.

Laboratory testing

The laboratory tests conducted included liver function tests [alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, albumin], coagulation parameters [international normalized ratio (INR)], renal function tests [blood urea nitrogen (BUN); serum creatinine], and tumor markers [alpha-fetoprotein (AFP)]. Specifically, ALT, AST, total bilirubin, and albumin levels were measured using the Roche Cobas c702 automated analyzer (Roche Diagnostics, Basel, Switzerland). The INR was determined by the STA-R MAX coagulation analyzer (Diagnostica Stago, Asnières-sur-Seine, France). Blood urea nitrogen and serum creatinine levels were assessed using the Siemens Dimension EXL 200 integrated chemistry system (Siemens Healthineers, Erlangen, Germany), while AFP levels were quantified with the Abbott Architect i2000SR immunoassay system (Abbott Laboratories, Abbott Park, IL, USA).

Imaging assessments

Imaging studies to evaluate tumor size, distribution, and response to treatment included CT scans and MRI. CT scans were conducted with a Siemens SOMATOM Definition Flash CT scanner (Siemens Healthineers, Germany), while MRI scans were performed using a GE Signa HDxt 1.5T MRI system (GE Healthcare, Chicago, IL, USA).

TMB analysis

TMB was evaluated using next-generation sequencing (NGS) methods on biopsy samples collected before treatment began. The Illumina NovaSeq 6000 system (Illumina, San Diego, CA, USA) was used for sequencing, with DNA extracted using the QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany). Libraries were prepared using the TruSeq DNA PCR-Free Library Prep Kit (Illumina, USA). Sequencing reads were aligned to the human reference genome (GRCh38) using the BWA-MEM algorithm, and variants were detected following the GATK Best Practices pipeline.

Documentation of adverse events

The incidence of adverse events was evaluated according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 (15). The primary endpoints monitored in this study included fever, abdominal pain, nausea and vomiting, hand-foot syndrome, fatigue, and rash.

Outcome measures

The primary outcomes of this study were progression-free survival (PFS) and overall survival (OS). Secondary outcomes encompassed the objective response rate (ORR), which includes complete response (CR) and partial response (PR), as well as any adverse events. PFS was defined as the duration from the initiation of treatment to disease progression or death from any cause. OS was measured as the duration from the start of treatment to death from any cause. The ORR was determined by the combined rates of CR and PR (16).

Statistical analysis

Statistical analyses were conducted using SPSS software version 29.0 (IBM Corp., USA). Continuous variables were reported as mean ± standard deviation (SD) and compared using independent samples t-tests. Categorical variables were presented as frequencies and percentages, with comparisons made via Chi-squared tests. Receiver operating characteristic (ROC) curve analysis was utilized to determine the optimal threshold for TMB. Survival outcomes, including OS and PFS, were estimated using Kaplan-Meier curves. Cox proportional hazards regression models were employed to identify independent predictors of PFS and OS. A two-sided P value of less than 0.05 was considered statistically significant. The outcome measures in this study had complete data with no missing values.

Results

Demographic and basic data

Patients in the good prognosis group exhibited higher TMB, with a mean of 11.16 mutations/Mb compared to 8.52 mutations/Mb in the poor prognosis group (P<0.001) (Table 1). Maximum tumor diameter also differed significantly, being smaller in the good prognosis group (8.24±2.09 cm) than in the poor prognosis group (9.30±2.13 cm, P=0.002). The AFP levels were significantly lower in the good prognosis group (760.90±119.60 ng/mL) compared to the poor prognosis group (822.40±105.30 ng/mL, P<0.001). Furthermore, the distribution of Barcelona Clinic Liver Cancer (BCLC) stages differed significantly, with a higher percentage of patients in the B stage in the good prognosis group (88.76%) compared to the poor prognosis group (74.65%, P=0.02). ECOG performance status scores showed a similar distribution with significance (P=0.04). The INR was significantly reduced in the good prognosis group (mean 1.07±0.12) compared to the poor prognosis group (mean 1.16±0.27, P=0.01). Additionally, blood urea nitrogen levels were lower in the good prognosis group (4.63±1.05 mmol/L) than in the poor prognosis group (5.04±1.28 mmol/L, P=0.046). Although the gender, age, BMI, history of smoking, alcohol consumption, etiology, disease duration, tumor distribution, number of tumors, Child-Pugh score, and most laboratory parameters, including ALT, AST, total bilirubin, albumin, and serum creatinine, showed no statistically significant differences across the two groups, these findings underscore the importance of TMB, tumor characteristics, AFP levels, and biochemical markers in prognosis (Figure 2).

Figure 2 Comparison of laboratory data among patients with different prognostic status. (A) AFP; (B) ALT; (C) AST; (D) total bilirubin; (E) albumin (g/L); (F) international normalized ratio; (G) blood urea nitrogen; (H) serum creatinine. ns, no significant difference; *, P<0.05; ***, P<0.001. AFP, alpha-fetoprotein; ALT, alanine aminotransferase; AST, aspartate aminotransferase.

ROC analysis

In the ROC analysis of factors affecting prognosis in patients with unresectable HCC, TMB demonstrated the highest area under the curve (AUC) at 0.83, with an optimal threshold of 10.025 mutations/Mb, yielding sensitivities of 0.803 and specificities of 0.742 (Table 2, Figure 3). This suggests TMB as a strong prognostic indicator. The maximum tumor diameter also showed notable predictive efficacy with an AUC of 0.626 at a threshold of 7.12 cm, providing sensitivities of 0.887 and specificities of 0.315. AFP levels had a moderate prediction ability for prognosis at a threshold of 730.84 ng/mL, corresponding to an AUC of 0.638, sensitivities of 0.845, and specificities of 0.404. In contrast, the BCLC stage and ECOG score had lower predictive values, each with an AUC of approximately 0.570, indicating limited prognostic power despite high sensitivities (0.887 for BCLC and 0.873 for ECOG) but low specificities (0.258). The INR showed an AUC of 0.622, with a threshold of 1.225, sensitivities of 0.944, and specificities of 0.371. Blood urea nitrogen levels, with an AUC of 0.598, had lower prognostic relevance, although it showed high specificities of 0.798 at a threshold of 5.5 mmol/L, combined with sensitivities of 0.437. These findings reinforce TMB as a key independent prognostic factor in this patient population.

Figure 3 TMB ROC curve. AUC, area under the curve; ROC, receiver operating characteristic; TMB, tumor mutation burden.

Baseline characteristics by TMB levels

In the analysis of baseline characteristics of patients with unresectable HCC stratified by TMB levels, the high TMB group exhibited a significantly smaller maximum tumor diameter (8.33±2.07 cm) compared to the low TMB group (9.24±2.15 cm, P=0.008) (Tables 3,4). Additionally, the high TMB group had significantly lower AFP levels (752.93±107.65 ng/mL) than the low TMB group (817.49±114.38 ng/mL, P<0.001). INR was lower among patients in the high TMB group (1.03±0.24) compared to those in the low TMB group (1.16±0.18, P<0.001). Blood urea nitrogen levels were also lower in the high TMB group (4.70±1.11 mmol/L) relative to the low TMB group (5.08±1.09 mmol/L, P=0.03). There was a statistically significant difference in the distribution of the BCLC stage and ECOG score between the groups, with the high TMB group having more patients in stage B of BCLC (85.26% vs. 70.77%, P=0.03) and a higher proportion of patients with an ECOG score of 0 (85.26% vs. 70.77%, P=0.03). The remaining variables, including gender, age, BMI, history of smoking, alcohol use, etiology, disease duration, tumor distribution, number of tumors, Child-Pugh classification, and most laboratory values such as ALT, AST, total bilirubin, and serum creatinine showed no statistically significant differences between the low and high TMB groups. This data highlights the relevance of TMB in relation to distinct clinical and biochemical profiles in these patients.

Clinical efficacy

In the assessment of clinical efficacy between patients with low and high TMB levels, the ORR was significantly higher in the high TMB group (39.99%) compared to the low TMB group (18.46%), with a χ² value of 7.623 and P=0.006, indicating a notable improvement in clinical outcomes among those with higher TMB (Table 5). Although the CR rate demonstrated a trend towards higher outcomes in the high TMB group (22.10% vs. 10.77%), this was not statistically significant (P=0.06). Similarly, the PR rate was higher in the high TMB group (17.89% vs. 7.69%) but did not reach statistical significance (P=0.07). These results underscore the potential role of TMB as a biomarker for predicting better therapeutic responses in patients undergoing TACE combined with immunotherapy and anti-angiogenic drugs.

Survival outcome analysis

The median PFS was substantially extended in the high TMB group, averaging 8.98±3.46 months, vs. 6.25±2.33 months in the low TMB group, with a χ² value of 5.976 and P<0.001 (Figures 4,5). Similarly, OS was notably longer for the high TMB group, with a mean of 20.57±5.92 months, compared to 13.82±4.27 months for the low TMB group (χ²=8.381, P<0.001). These findings highlight the significant prognostic value of TMB in predicting both PFS and OS in patients with unresectable HCC undergoing TACE combined with immunotherapy and anti-angiogenic agents.

Figure 4 PFS curves. PFS, progression-free survival; TMB, tumor mutation burden.

Figure 5 OS curves. OS, overall survival; TMB, tumor mutation burden.

Cox regression analysis of the impact on PFS

In the Cox regression analysis assessing the impact of TMB and other variables on PFS in patients with unresectable HCC, both univariate and multivariate analyses highlighted the prognostic significance of TMB (Table 6). High TMB levels were associated with a reduced hazard for disease progression, with a hazard ratio (HR) of 0.67 [95% confidence interval (CI): 0.51–0.88; P<0.001] in univariate analysis and 0.72 (95% CI: 0.54–0.96; P=0.02) in multivariate analysis. Maximum tumor diameter also emerged as a significant predictor, presenting an HR of 1.34 (95% CI: 1.12–1.61; P<0.001) in univariate analysis and 1.28 (95% CI: 1.06–1.55; P=0.01) in multivariate analysis, suggesting increased tumor size was associated with shorter PFS. Similarly, advanced BCLC stage, ECOG performance status, and INR were independently associated with poorer PFS, with multivariate HRs of 1.75 (95% CI: 1.34–2.29; P<0.001), 1.55 (95% CI: 1.18–2.04; P=0.002), and 1.18 (95% CI: 1.03–1.35; P=0.02), respectively. Furthermore, a higher AFP level and elevated blood urea nitrogen were linked with decreased PFS, presenting multivariate HRs of 1.001 (95% CI: 1.000–1.002; P=0.04) and 1.06 (95% CI: 1.00–1.12; P=0.048), respectively. These findings underscore the strong association between high TMB and improved PFS, emphasizing the potential of TMB as a valuable prognostic factor in this patient cohort.

Cox regression analysis of the impact on OS

The Cox regression analysis evaluating the impact of TMB and other variables on OS in patients with unresectable HCC demonstrated that high TMB was associated with significantly improved survival (Table 7). High TMB levels were linked to a reduced risk of mortality, with a hazard ratio (HR) of 0.59 (95% CI: 0.45–0.78; P<0.001) in the univariate analysis and 0.64 (95% CI: 0.48–0.85; P=0.002) in the multivariate model, underscoring its prognostic significance. Additionally, maximum tumor diameter was a significant predictor of OS, with multivariate analysis yielding an HR of 1.35 (95% CI: 1.12–1.62; P=0.001), indicating that larger tumors were associated with poorer survival outcomes. Moreover, higher BCLC stage and ECOG scores were independent predictors of reduced OS, with multivariate HRs of 1.81 (95% CI: 1.38–2.37; P<0.001) and 1.59 (95% CI: 1.21–2.09; P=0.001), respectively. Similarly, elevated levels of AFP and blood urea nitrogen increased the hazard of mortality, with multivariate HRs of 1.002 (95% CI: 1.001–1.003; P=0.004) and 1.08 (95% CI: 1.02–1.14; P=0.01), respectively. Finally, the INR was also a significant negative predictor, with an HR of 1.20 (95% CI: 1.05–1.38; P=0.01). These findings highlight TMB as a crucial independent prognostic factor for OS among patients undergoing TACE combined with immunotherapy and anti-angiogenic treatments.

Incidence of adverse events

The incidence of fever was lower in the high TMB group (12.63%) compared to the low TMB group (26.15%), with a χ² value of 4.755 and P=0.03 (Table 8). Abdominal pain was also less frequent in the high TMB group (10.52% vs. 23.08%, χ²=4.611, P=0.03). Similarly, nausea and vomiting occurred less often in the high TMB group (7.37%) compared to the low TMB group (20.00%), with a χ² value of 5.630 and P=0.02. The incidence of hand-foot syndrome and rash followed this trend, with the high TMB group reporting lower frequencies (8.42% vs. 20.00%, χ²=4.538, P=0.03 for hand-foot syndrome; 7.37% vs. 18.46%, χ²=4.538, P=0.03 for rash). Notably, fatigue was significantly reduced in the high TMB group, affecting 16.84% of patients compared to 40.00% in the low TMB group, with a χ² value of 10.694 and P=0.001. These results suggest that a higher TMB was associated with a lower incidence of several common adverse events following treatment, potentially contributing to improved tolerability of the therapeutic regimen.

Discussion

The exploration of TMB as a biomarker in guiding treatment strategies for unresectable HCC represents a significant advancement in precision oncology.

The prognostic value of TMB can be attributed to its reflection of the tumor’s genomic complexity and immunogenicity. Tumors with higher TMB tend to generate more neoantigens, which may enhance their recognition by the immune system, thus potentiating the efficacy of immunotherapeutic interventions (17). Camrelizumab, an anti-PD-1 antibody used in our study, benefits from such enhanced immunogenicity by more effectively reactivating cytotoxic T cells. This aligns with previous research illustrating that high TMB correlates with improved responses to immunotherapy across various cancers (18). Consequently, HCC patients exhibiting high TMB levels demonstrate superior survival outcomes and treatment responses.

Furthermore, the integration of TACE with immunotherapy and anti-angiogenic treatment may create a synergistic effect, amplifying the benefits witnessed in high TMB patients. TACE, by selectively targeting and disrupting tumor blood supply, not only reduces tumor mass but may also promote the release of tumor antigens, thereby enhancing immune activation in the presence of PD-1 blockade (19). Concurrently, anti-angiogenic agents like lenvatinib or apatinib can modulate the tumor microenvironment, reducing immunosuppressive barriers and improving immune cell infiltration. This three-pronged strategy can significantly benefit patients with high TMB, where the immune system was more primed for tumor recognition and destruction (20).

Our study also highlights the role of TMB in prognosticating adverse events. Patients with higher TMB reported fewer adverse events, such as fatigue, nausea, and rash. This counterintuitive finding could be due to the nuanced interaction between the host immune system and tumor neoantigens (21). Higher TMB might indicate a more active immune environment that not only targets tumors more effectively but also better tolerates immunotherapy. Reduced systemic inflammation in high TMB patients might account for the lower incidence of treatment-related adverse effects, leading to improved tolerability and quality of life (22).

Interestingly, the distinct differences in clinical and biochemical profiles between low and high TMB groups underscore TMB’s role in delineating patient subgroups according to their biological response potential. For instance, higher AFP levels and tumor diameters, which typically indicate aggressive disease biology, were inversely correlated with favorable TMB-associated outcomes (23). This suggests that while high tumor aggression indicators conventionally predict poorer outcomes, the presence of high TMB might counterbalance this, delivering extended survival and response benefits. Such findings advocate for a deeper understanding of the interplay between TMB and other prognostic factors in enhancing personalized risk stratification and treatment planning (24).

The lower predictive capacity of standard parameters like the BCLC stage and ECOG score compared to TMB reinforces the notion that genomic evaluation provides a more nuanced understanding of tumor dynamics (25). The complexity captured by TMB transcends classical clinical staging and performance metrics by offering insights into tumor biology at the molecular level (26). This underscores the need for incorporating genomic markers into routine clinical decision-making processes, thus transitioning from conventional to more personalized paradigms in oncology (27).

While our study demonstrates statistically significant associations between high TMB and improved outcomes, the clinical meaningfulness of these differences warrants consideration. For instance, the median PFS difference of approximately 2.7 months and OS difference of nearly 7 months between high and low TMB groups may represent a meaningful gain for patients with unresectable HCC, where treatment options are limited. These findings suggest that TMB could potentially aid in identifying patients more likely to benefit from combination therapy, thereby informing personalized treatment strategies and improving resource allocation in clinical practice.

Mechanistically, TMB-rich environments potentially foster more potent anti-tumor immune responses through several pathways: the enhanced presentation of neoantigens to dendritic cells and T cells, increased chemotactic signals recruiting active effector cells, and reduced immunosuppressive mechanisms (28). Combining these processes with immunotherapy and anti-angiogenic strategies likely amplifies anti-tumor immunity, creating a feed-forward loop that perpetuates tumor regression in responsive subsets of patients. This interaction warrants further exploration into specific mutation types and their synergistic impact with immunotherapeutic regimens (29,30).

Reflecting on limitations, this study is retrospective in design, which may introduce selection bias and limit causal inference. Additionally, despite multivariable adjustment, residual confounding due to baseline differences between TMB groups cannot be entirely excluded. Future studies using propensity score methods may help further balance these characteristics. It should be noted that the TMB cutoff used in this study was derived from ROC analysis within the same cohort and may be influenced by factors such as sequencing platform, panel size, and patient characteristics. Therefore, this threshold should be considered specific to our study population and requires validation in external, prospective cohorts before it can be widely adopted in clinical practice. Further, while our study establishes the prognostic utility of TMB, the mechanisms proposed remain speculative and require validation through prospective trials and mechanistic studies. The heterogeneity in TMB cut-off thresholds also calls for standardized protocols across institutions to ensure uniform application and interpretation.

Future directions should concentrate on prospective validation of TMB as a predictive biomarker in HCC cohorts undergoing similar therapeutic regimens. Additionally, integrating multi-omic datasets, including proteomics and transcriptomics, might refine our understanding of TMB’s role alongside immune landscape characterization, enabling more precise patient stratification. It is also critical to investigate the interaction of TMB with other emerging biomarkers, such as PD-L1 expression and immune cell infiltration profiles, to develop comprehensive scoring systems predictive of immunotherapy outcomes.

Conclusions

In conclusion, our findings advocate for the integration of TMB assessments into the clinical management of HCC. Not only does TMB serve as a valuable prognostic tool, but its incorporation also enriches our understanding of patient susceptibility and treatment response, shaping a pathway towards more effective and personalized cancer care strategies.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-aw-930/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-aw-930/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-aw-930/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-aw-930/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol received approval from the Institutional Review Board (IRB) of The Affiliated Cangnan Hospital of Wenzhou Medical University, under approval number: 2025055. Given its retrospective design, informed consent was waived due to the anonymized nature of the data. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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