Hepatocellular carcinoma, or HCC, is the most common primary cancer arising in the liver. When tumors cannot be surgically removed, treatment becomes substantially more difficult because the disease may involve major blood vessels, occupy large portions of the liver or have spread beyond the organ. One approach is transarterial chemoembolization, known as TACE, in which physicians guide a catheter through the blood vessels to arteries feeding a tumor. Chemotherapy is delivered locally, while embolic material blocks the tumor’s blood supply. The procedure can expose cancer cells to high drug concentrations and deprive them of oxygen, but it does not always eliminate all malignant tissue.

The other components of the combination attack the disease through different biological pathways. Lenvatinib is a tyrosine kinase inhibitor that blocks signaling proteins involved in blood-vessel formation and tumor growth. HCC tumors often stimulate the development of new vessels to secure oxygen and nutrients; inhibiting pathways involving vascular endothelial growth factor receptors can restrict that support. PD-1 inhibitors work through the immune system. PD-1 is a checkpoint protein on immune cells that can be exploited by tumors to suppress T-cell activity. Blocking the PD-1 pathway may restore part of the immune response against cancer. In principle, TACE can release tumor antigens and alter the tumor environment, lenvatinib can restrain angiogenesis, and immunotherapy can mobilize immune cells against remaining cancer cells.

Although this three-part treatment, abbreviated T-L-P by the researchers, has shown encouraging activity, its effects vary considerably from one patient to another. Some patients experience substantial tumor shrinkage and prolonged disease control, while others progress despite treatment. Clinicians therefore need practical ways to identify likely responders and recognize patients whose disease or underlying liver dysfunction may limit the benefit. The research team, led by Pengpeng Zhu and Kaile Tian, examined medical records from patients who began T-L-P therapy between 2020 and 2022. The investigators randomly or administratively divided the study population into a training cohort of 90 patients, used to develop the model, and a validation cohort of 64 patients, used to test whether it retained its predictive value.

The researchers first assessed objective response rate, or ORR, which measures the proportion of patients whose tumors met predefined criteria for complete or partial shrinkage. They also examined disease control rate, which includes responses as well as stable disease. In the training cohort, 44 of 90 patients, or 48.9 percent, achieved an objective response, while 72 patients, or 80 percent, achieved disease control. In the validation cohort, the corresponding figures were 38 of 64 patients, or 59.4 percent, for objective response and 52 patients, or 81.3 percent, for disease control. These results describe outcomes in the selected study population and should not be interpreted as proof that the treatment will produce the same response rates in every clinical setting.

Statistical analysis identified three independent factors associated with objective response. The first was an alpha-fetoprotein concentration above 100 nanograms per milliliter. AFP is a protein produced during fetal development that can reappear at high levels in some people with HCC, although it is neither present in every case nor specific to this cancer. The second factor was a tumor burden score above 8. TBS combines tumor size and number into a single measure, generally increasing as tumors become larger or more numerous. The third was Child-Pugh class B liver function, a category indicating more substantial impairment than class A. The Child-Pugh system incorporates measures such as bilirubin, albumin, blood clotting, fluid accumulation and encephalopathy to estimate the liver’s functional reserve.

Each of these features was assigned one point in the ATC score, producing a range from zero to three. The name reflects the principal variables used in the model: AFP, tumor burden and Child-Pugh classification. Patients with no risk factors had a score of zero and were designated low risk; those with one factor had an intermediate-risk score of one; and those with two or three factors were placed in the high-risk group. The score is not a molecular test and does not directly measure immune activity, drug concentration or genetic mutations. Instead, it combines readily available indicators of tumor biology and the liver’s ability to withstand both cancer and treatment.

The differences between the groups were striking. In the training cohort, the estimated two-year overall survival rate was 83.57 percent for patients with an ATC score of zero, 64.13 percent for those scoring one and 20.69 percent for those scoring at least two. Two-year progression-free survival, which measures the length of time before the cancer worsens or the patient dies, was 66.48 percent, 46.55 percent and 9.33 percent in the same groups. The validation cohort showed a similar pattern: two-year overall survival was 94.12 percent for score zero, 64.71 percent for score one and 25.93 percent for scores of two or three. Two-year progression-free survival was 82.35 percent, 47.06 percent and 16.67 percent, respectively.

To evaluate discrimination, the investigators used the area under the receiver operating characteristic curve, or AUC. This statistic summarizes how well a model distinguishes between patients who do and do not experience an outcome, with a value of 0.5 representing chance performance and values closer to 1 indicating stronger discrimination. The ATC score achieved an AUC of 0.826 in the training cohort and 0.811 in the validation cohort. According to the study, this performance was better than that of any individual component alone. The validation result is particularly important because a model can appear highly accurate in the same data used to build it but lose performance in a separate group.

The researchers say the score could support treatment planning by providing an early estimate of expected benefit from T-L-P therapy. A patient with a low score might be considered a strong candidate for continuing an intensive combination approach, assuming treatment is otherwise safe and appropriate. A high score could prompt closer monitoring, more detailed discussion of alternatives or consideration of clinical trials designed for patients with difficult-to-treat disease. The model might also help researchers balance participants across risk categories in future studies, making it easier to determine whether a new therapy helps patients with poor baseline prognoses rather than simply reflecting differences between trial populations.

The results nevertheless come with important limitations. The study was retrospective, meaning the investigators analyzed existing records rather than assigning treatment prospectively under a controlled protocol. All 154 patients received the same general treatment combination, but unmeasured differences in disease characteristics, supportive care or clinical decision-making could have influenced the outcomes. The sample was also relatively small and drawn from institutions in China, so the model requires testing in larger, geographically diverse populations before it can be considered broadly reliable. In addition, a score that predicts response at the group level cannot determine an individual patient’s fate. Some people with high scores may respond exceptionally well, while some with low scores may not benefit.

The findings add to a growing effort to make combination therapy for advanced liver cancer more precise. TACE, targeted therapy and immune checkpoint blockade each affect a different part of the tumor ecosystem, but the same complexity that creates therapeutic potential also makes outcomes difficult to anticipate. The ATC score offers a deliberately simple framework built from clinical information already collected in routine care. Its next test will be prospective validation: researchers will need to apply the score before treatment begins, follow patients under standardized conditions and determine whether it improves decisions rather than merely describing prognosis. Until then, the model is best viewed as a promising research tool—one that could help clinicians move closer to matching the right treatment intensity to the biology of an individual patient.

Hepatocellular carcinoma remains one of the most challenging cancers worldwide, with poor prognostic outcomes partly due to its immunosuppressive microenvironment and limited response to conventional treatments. Immunotherapies targeting immune checkpoints have revolutionized oncology but exhibit variable efficacy in HCC patients. The molecular underpinnings of this variability have been elusive. Lei and colleagues systematically investigated how the activation state of KRAS, a well-known oncogene commonly mutated in various cancers, influences the immune dynamics within HCC tumors, despite being in its wild-type form.

The study delineates a previously unappreciated role for wild-type KRAS, emphasizing that its activation—not mutation—is sufficient to elicit profound changes in the tumor immune milieu. By employing a combination of in vitro cell line models, patient-derived xenografts, and transcriptomic profiling, the researchers demonstrated that activated wild-type KRAS drives a robust suppression of interferon signaling pathways. The interferon pathway is crucial for eliciting an effective anti-tumor immune response, notably by promoting antigen presentation and the recruitment of cytotoxic immune cells.

Their analysis revealed that wild-type KRAS activation downregulates the expression of interferon-stimulated genes (ISGs), thereby blunting the tumor’s susceptibility to immune attack. This suppression extends to both type I and type II interferon responses, suggesting a broad-spectrum immune escapism strategy. The molecular crosstalk between KRAS signaling and interferon pathways was substantiated through phosphoproteomic analyses, which identified downstream signaling nodes potentially mediating this immune resistance phenomenon.

Beyond the molecular crosstalk, the study highlights the functional consequences of KRAS-induced immune evasion in the context of immunotherapy. When subjected to checkpoint blockade inhibitors targeting PD-1/PD-L1, models exhibiting wild-type KRAS activation demonstrated significantly impaired therapeutic responses. This finding suggests that KRAS activation status may serve as a predictive biomarker for resistance to immunotherapy, a revelation that demands clinical validation in patient cohorts.

The authors also explored therapeutic interventions that could potentially circumvent KRAS-driven immune evasion. Combining MEK inhibitors, which dampen KRAS downstream signaling, with immunotherapy restored interferon responsiveness and enhanced tumor control in experimental models. This combinatorial approach emphasizes the therapeutic synergy achievable through targeted molecular inhibition alongside immune checkpoint blockade.

Notably, the study’s implications extend to the broader understanding of oncogenic signaling pathways co-opting immune escape mechanisms. While mutant KRAS has been extensively studied for its oncogenic capacity, this research underscores that even the wild-type protein, when aberrantly activated, can reprogram the tumor microenvironment to its advantage. This paradigm shift challenges existing dogma and calls for a reassessment of KRAS’s role across different cancer types and treatment contexts.

From a translational perspective, the insights provided by Lei and colleagues could catalyze the development of precision immuno-oncology strategies tailored to the signaling landscape of tumors. Diagnostic assays assessing KRAS activation alongside interferon pathway status may help stratify patients for personalized interventions, optimizing clinical outcomes. Furthermore, targeting wild-type KRAS-induced immune modulation could help overcome one of the major barriers to effective immunotherapy in HCC.

Given the complexity of tumor-immune interactions, the elucidation of KRAS’s immunomodulatory function enriches our comprehension of tumor biology and reveals new therapeutic vulnerabilities. Importantly, the correlation between KRAS activation and immune suppression is likely influenced by a constellation of other factors, including tumor heterogeneity and microenvironmental cues, warranting deeper mechanistic explorations in future studies.

This seminal work adds a crucial layer to the fundamental narrative of cancer immune evasion and resistance mechanisms. It invites oncologists and researchers alike to consider the non-mutational activation of oncogenes as a critical determinant of tumor immune phenotypes. Consequently, therapeutic regimens that concurrently target oncogenic signaling and restore interferon responsiveness could become the cornerstone of next-generation immunotherapies.

In conclusion, the discovery that wild-type KRAS activation subverts interferon-mediated immunity marks a significant milestone in hepatocellular carcinoma research. It not only deepens our understanding of the molecular interplay between oncogenic drivers and immune escape but also highlights actionable targets to augment immunotherapeutic efficacy. As immunotherapy continues to reshape the cancer treatment paradigm, integrating such molecular insights will be paramount in overcoming resistance and improving patient survival.

This research opens the door to a new chapter where the nuanced roles of canonical oncogenes are revisited in the context of immune regulation. The potential to revert immune suppression by intercepting wild-type KRAS signaling offers hope for more effective treatments against a notably refractory cancer type. Ultimately, these findings underscore the intricate dance between tumor genetics and immune surveillance that defines therapeutic success.

Future research directions inspired by this work will likely focus on validating these findings in large clinical cohorts and expanding the therapeutic arsenal against KRAS-driven immune evasion. Investigations into whether similar mechanisms operate in other cancers or involve additional oncogenes could further revolutionize the field of cancer immunotherapy. The promise of converting immunologically “cold” tumors into “hot” ones by targeting wild-type KRAS activation is an exciting prospect that holds considerable translational promise.

As the oncology community grapples with the challenges of resistance to immunotherapies, studies like this exemplify the power of molecular biology to unravel hidden resistance pathways. By bridging oncogenic signaling with immune regulation, the scientific and medical communities are better equipped to devise integrated treatment strategies that anticipate and overcome tumor defenses.

Lei et al.’s landmark study is a testament to the critical importance of dissecting tumor biology at a granular level to unlock new avenues for effective cancer treatment. Harnessing this knowledge to inform clinical practice will be a pivotal step toward achieving durable remissions and ultimately cures for hepatocellular carcinoma patients worldwide.

Subject of Research: Mechanisms of immune evasion and therapeutic resistance in hepatocellular carcinoma mediated by wild-type KRAS activation.

Article Title: Wild-type KRAS activation drives evasion of interferon-mediated immunity and resistance to immunotherapy in hepatocellular carcinoma.

Article References:
Lei, M.M.L., Leung, C.O.N., Leung, R.W.H. et al. Wild-type KRAS activation drives evasion of interferon-mediated immunity and resistance to immunotherapy in hepatocellular carcinoma. Nat Commun 16, 9913 (2025). https://doi.org/10.1038/s41467-025-64860-7

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41467-025-64860-7

Alpha-fetoprotein has long been utilized as a clinical biomarker in liver cancer diagnosis and surveillance. However, its dynamic changes over the course of systemic therapy remained underexplored until this latest retrospective, multicenter cohort study involving 553 uHCC patients treated with lenvatinib. Lenvatinib, a tyrosine kinase inhibitor with potent antiangiogenic properties, has gained approval as a first-line systemic agent for advanced HCC, but predicting which patients derive the greatest benefit has been elusive. This study uniquely applies advanced statistical modeling to AFP trajectories, offering nuanced insights beyond static measurement.

Utilizing a latent class linear mixed model—a sophisticated technique to capture underlying patterns within longitudinal data—the investigators classified AFP changes into four distinct trajectories: High-stable, High-rising, Sharp-falling, and Low-stable. Each trajectory represents a unique biological and clinical response pattern during lenvatinib treatment. This classification was grounded in analyzing serial AFP levels collected from patients across four oncology centers over three years, enhancing the robustness and generalizability of findings.

Notably, the study revealed that patients exhibiting the Sharp-falling and Low-stable AFP trajectories experienced significantly improved overall survival (OS) and progression-free survival (PFS) compared to those with High-stable trajectories. Specifically, hazard ratios for mortality indicated a 72% and 58% reduction in risk for the Sharp-falling and Low-stable groups, respectively, marking a profound difference in prognosis associated with AFP dynamics. Similarly, the risk of disease progression diminished markedly within these groups, highlighting the AFP trajectory’s potential utility as a predictive biomarker.

Conversely, patients categorized under the High-rising trajectory did not demonstrate statistically significant survival benefits relative to the High-stable group, underscoring the importance of not only absolute AFP levels but their temporal patterns. These distinctions emphasize that a simple binary of high versus low AFP may insufficiently capture the biological complexity underlying treatment response, advocating for dynamic biomarker monitoring in clinical practice.

The clinical implications of these findings are manifold. First, encouraging longitudinal AFP monitoring could allow oncologists to stratify patients more effectively according to their anticipated response to lenvatinib. This stratification can inform adaptive treatment modifications, such as dose adjustments or the integration of complementary therapies in patients unlikely to respond favorably. Moreover, AFP trajectory analysis provides a non-invasive, cost-effective biomarker strategy, circumventing the need for more invasive or expensive modalities in routine follow-ups.

Beyond immediate clinical application, this research exemplifies the power of integrating advanced biostatistical methodologies into oncology studies. The latent class linear mixed model facilitated uncovering heterogeneity in treatment response hidden beneath aggregate data, pointing to the future of personalized medicine that utilizes computational techniques to identify subpopulations within heterogeneous diseases like HCC. This approach may be extended to other cancer biomarkers and therapeutic contexts, magnifying its translational potential.

Furthermore, the utilization of retrospective multicenter data spanning multiple years fortifies the reliability and clinical relevance of the study’s conclusions. Such collaboration across centers mitigates biases that might arise from smaller single-center cohorts and captures real-world patient diversity, which is critical for the applicability of predictive models in heterogeneous clinical settings. The study design also reflects the increasing embrace of big data analytics within oncology, a trend expected to accelerate in the coming years.

Despite these promising advancements, challenges remain in fully integrating AFP trajectory monitoring into routine clinical workflows. Standardization of AFP measurement intervals, inter-laboratory assay variability, and the need for real-time data analytics infrastructure are practical hurdles to be addressed. Nonetheless, the demonstrated prognostic power of AFP trajectories sets a compelling rationale for further prospective validation and health system integration.

Importantly, lenvatinib’s mechanism as a multikinase inhibitor, targeting VEGFR, FGFR, PDGFR, and others, intersects with tumor angiogenesis and cell proliferation pathways. The association between AFP dynamics and survival outcomes might reflect underlying tumor biology modulated by lenvatinib’s molecular effects. Future mechanistic studies could elucidate how AFP production correlates with tumor microenvironment alterations under systemic treatment, deepening understanding and enhancing biomarker-driven therapy.

Additionally, the absence of significant differences in outcomes for the High-rising group compared to the High-stable cohort suggests a potential resistance phenotype or aggressive tumor biology that does not respond to AFP decline, underscoring the need for alternative therapeutic strategies or combination regimens in this subgroup. This insight advocates for biomarker-informed clinical trials tailored to trajectory-defined patient subsets.

In the evolving landscape of hepatocellular carcinoma management, where immunotherapies and novel targeted agents are emerging, the integration of AFP trajectory monitoring could prove invaluable for treatment sequencing and personalized care. As therapeutic options diversify, robust biomarkers enabling early detection of resistance or response will become critical to optimize outcomes and resource allocation.

Moreover, these findings resonate amid global increases in liver cancer incidence associated with metabolic syndrome, viral hepatitis, and cirrhosis, particularly in regions with limited access to advanced imaging or biopsy capabilities. Serum biomarkers such as AFP, when leveraged with trajectory analysis, could democratize prognosis estimation and prompt timely therapeutic interventions across diverse healthcare settings.

The study by Zheng et al. thus provides a paradigm-shifting framework, transitioning AFP from a static diagnostic marker to a dynamic predictive tool capable of guiding individualized therapy in unresectable hepatocellular carcinoma. This advancement aligns with precision oncology’s goals: tailoring treatments based on patient-specific tumor biology, optimizing clinical outcomes, and minimizing unnecessary toxicity.

In sum, the identification of four distinct AFP trajectories with divergent survival outcomes under lenvatinib therapy heralds a new chapter in liver cancer management. By harnessing longitudinal biomarker data through advanced modeling techniques, oncology is poised to enhance prognostication and personalize systemic therapy in uHCC, transforming a grim prognosis into a more manageable condition.

Future prospective studies and clinical trials integrating AFP trajectory monitoring with molecular and imaging biomarkers could further refine and validate this approach. Ultimately, such multidisciplinary biomarker strategies will catalyze the evolution of hepatocellular carcinoma into a precisely targeted and adaptable clinical challenge, improving survival and quality of life for patients worldwide.

Subject of Research: Alpha-fetoprotein trajectories as predictive biomarkers in unresectable hepatocellular carcinoma patients receiving lenvatinib treatment.

Article Title: Trajectories of α-fetoprotein and unresectable hepatocellular carcinoma outcomes receiving lenvatinib: a retrospective, multicenter cohort study

Article References: Zheng, Y., Hu, J., Mei, Y. et al. Trajectories of α-fetoprotein and unresectable hepatocellular carcinoma outcomes receiving lenvatinib: a retrospective, multicenter cohort study. BMC Cancer 25, 1137 (2025). https://doi.org/10.1186/s12885-025-14516-y

Image Credits: Scienmag.com

DOI: https://doi.org/10.1186/s12885-025-14516-y

HCC, the predominant form of primary liver cancer, often presents in advanced stages where curative options such as surgical resection or liver transplantation are no longer viable. The dismal prognosis associated with advanced HCC has propelled extensive research into immunotherapeutic strategies aimed at harnessing the patient’s immune system to combat the malignancy more effectively. Llovet’s exposition provides a comprehensive synthesis of recent clinical breakthroughs, molecular rationale, and translational research that collectively underscore the clinical efficacy and mechanistic underpinnings of combination immunotherapies in HCC.

At the core of these innovative treatments lies the intricate interaction between tumor cells and the immune microenvironment within the liver. The liver’s inherent immune-tolerant milieu, designed to mitigate excessive inflammatory responses to constant antigenic exposure from the gut, paradoxically fosters an immunosuppressive niche favoring tumor progression. Therapeutic modalities that disrupt this tolerant landscape, while simultaneously reinvigorating tumor-directed immunity, represent the crux of the novel immunotherapy paradigm. Llovet meticulously elucidates how combinations of immune checkpoint inhibitors—targeting PD-1/PD-L1 and CTLA-4 pathways—can synergistically reverse T-cell exhaustion and unleash a potent anti-tumor immune response.

Single-agent immune checkpoint blockade had previously shown limited efficacy in HCC due to diverse resistance mechanisms. By contrast, combined checkpoint blockade has demonstrated enhanced clinical outcomes, including improved objective response rates and survival benefits. Llovet highlights clinical trials that illustrate the improved potency of combining anti-PD-1 antibodies with anti-CTLA-4, highlighting the dual reactivation of effector T-cells alongside suppression of regulatory T-cell populations. These findings underscore the necessity of targeting multiple immune regulatory axes concurrently to overcome the multifaceted immune evasion tactics employed by HCC.

Beyond checkpoint inhibition, the integration of immunotherapy with antiangiogenic agents emerges as a groundbreaking approach discussed extensively in the article. Angiogenesis inhibitors, which normalize aberrant tumor vasculature and modulate immune cell infiltration, complement immune checkpoint inhibitors by remodeling the tumor microenvironment into a more immunologically permissive state. Llovet’s discussion of pivotal trials combining VEGF-targeting agents with PD-1/PD-L1 inhibitors illuminates the mechanistic synergy that underlies enhanced therapeutic efficacy, with some combinations attaining regulatory approval based on robust survival gains.

The article also delves into the molecular heterogeneity of HCC, which is increasingly recognized as a critical determinant of immunotherapy responsiveness. Through integrative genomic and transcriptomic analyses, distinct immune phenotypes have been characterized, ranging from immune-inflamed tumors with high lymphocyte infiltration to immune-desert tumors marked by immunosuppression and exclusion. Llovet underscores that precision medicine approaches tailored to these immunological subtypes hold promise for optimizing patient selection and tailoring combination regimens to maximize benefit.

Another notable breakthrough in immunotherapy combinations explored in Llovet’s work is the incorporation of novel agents such as bispecific antibodies and cell-based therapies. Bispecific T-cell engagers (BiTEs) and chimeric antigen receptor (CAR) T-cell therapies are being engineered to specifically target HCC-associated antigens, effectively directing cytotoxic immunity while minimizing off-target effects. The article provides a nuanced discussion of preclinical data and early-phase clinical trials that demonstrate the feasibility and potential of these emerging modalities to complement existing checkpoint and antiangiogenic therapies.

Importantly, the article emphasizes the challenges associated with managing immune-related adverse events (irAEs) that often arise from intensified immunotherapeutic regimens. The liver’s unique immunobiology places patients at risk for severe hepatotoxicity, necessitating vigilant monitoring and innovative management strategies. Llovet highlights ongoing research efforts aimed at identifying biomarkers predictive of toxicity and response, as well as the development of prophylactic interventions to mitigate irAE severity without compromising anticancer efficacy.

Llovet further discusses the role of the gut-liver axis in modulating responses to immunotherapy. The hepatic immune environment is profoundly influenced by gut microbiota-derived metabolites and microbial antigens, which shape systemic and intrahepatic immunity. Recent findings suggest that targeting microbial dysbiosis or leveraging microbiome modulation could potentiate immunotherapeutic success in HCC, adding a new dimension to combination treatment strategies.

Furthermore, advancing imaging and biomarker technologies have facilitated dynamic monitoring of treatment response and immune activation in HCC patients undergoing immunotherapy. Liquid biopsy techniques analyzing circulating tumor DNA and immune cell profiling are uncovered in the article as promising tools to enable personalized adaptation of therapeutic regimens in real-time, enhancing clinical decision-making and potentially improving survival outcomes.

Llovet concludes with a visionary perspective on the future landscape of HCC treatment. He advocates for continued interdisciplinary research aimed at unraveling tumor-immune interactions, optimizing combination regimens, and expanding clinical trial designs to include diverse patient populations. The integration of artificial intelligence and machine learning to predict therapeutic responses and toxicity profiles is identified as an emergent frontier, poised to revolutionize individualized patient care.

In essence, this comprehensive review by J.M. Llovet encapsulates a transformative epoch in HCC management, wherein sophisticated immunotherapy combinations are redefining therapeutic possibilities for a historically refractory malignancy. Through meticulous synthesis of clinical data, mechanistic insights, and translational research, the article charts a compelling trajectory toward durable disease control and improved quality of life for patients battling advanced hepatocellular carcinoma.

The momentum generated by these novel immunotherapeutic strategies holds immense promise for reshaping HCC outcomes and offers a beacon of hope in the broader fight against liver cancer. As these combination therapies move from bench to bedside and beyond, the imperative to deepen our understanding of tumor immunobiology and refine treatment paradigms remains more critical than ever. Llovet’s authoritative contribution stands as a seminal reference point that will undoubtedly inspire and guide clinicians, researchers, and stakeholders invested in conquering advanced-stage hepatocellular carcinoma.

Subject of Research: Novel immunotherapy combinations in the management of advanced-stage hepatocellular carcinoma

Article Title: Role of novel immunotherapy combinations in the management of advanced-stage hepatocellular carcinoma

Article References:
Llovet, J.M. Role of novel immunotherapy combinations in the management of advanced-stage hepatocellular carcinoma. Nat Rev Clin Oncol (2025). https://doi.org/10.1038/s41571-025-01055-5

Image Credits: AI Generated