Biomarkers for immunotherapy of hepatocellular carcinoma

A novel liver-function-indicators-based prognosis signature for patients with hepatocellular carcinoma treated with anti-programmed cell death-1 therapy

BACKGROUND

The liver function reserve has a significant impact on the therapeutic effects of anti-programmed cell death-1 (PD-1) for hepatocellular carcinoma (HCC). This study aimed to comprehensively evaluate the ability of liver-function-based indicators to predict prognosis and construct a novel prognostic score for HCC patients with anti-PD-1 immunotherapy.

METHODS

Between July 2018 and January 2020, patients diagnosed with HCC who received anti-PD-1 treatment were screened for inclusion in the study. The valuable prognostic liver-function-based indicators were selected using Cox proportional hazards regression analysis to build a novel liver-function-indicators-based signature (LFIS). Concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and Kaplan-Meier survival curves were utilized to access the predictive performance of LFIS.

RESULTS

A total of 434 HCC patients who received anti-PD-1 treatment were included in the study. The LFIS, based on alkaline phosphatase-to-albumin ratio index, Child-Pugh score, platelet-albumin score, aspartate aminotransferase-to-lymphocyte ratio index, and gamma-glutamyl transpeptidase-to-lymphocyte ratio index, was constructed and identified as an independent risk factor for patient survival. The C-index of LFIS for overall survival (OS) was 0.692, which was higher than the other single liver-function-based indicator. The AUC of LFIS at 6-, 12-, 18-, and 24-month were 0.74, 0.714, 0.747, and 0.865 for OS, respectively. Patients in the higher-risk LFIS group were associated with both worse OS and PFS. An online and easy-to-use calculator was further constructed for better application of the LFIS signature.

CONCLUSION

The LFIS score had an excellent prognosis prediction ability superior to every single liver-function-based indicator for anti-PD-1 treatment in HCC patients. It is a reliable, easy-to-use tool to stratify risk for OS and PFS in HCC patients who received anti-PD-1 treatment.

Antiangiogenic-immune-checkpoint inhibitor combinations: lessons from phase III clinical trials

Antiangiogenic agents, generally antibodies or tyrosine-kinase inhibitors that target the VEGF-VEGFR pathway, are currently among the few combination partners clinically proven to improve the efficacy of immune-checkpoint inhibitors (ICIs). This benefit has been demonstrated in pivotal phase III trials across different cancer types, some with practice-changing results; however, numerous phase III trials have also had negative results. The rationale for using antiangiogenic drugs as partners for ICIs relies primarily on blocking the multiple immunosuppressive effects of VEGF and inducing several different vascular-modulating effects that can stimulate immunity, such as vascular normalization leading to increased intratumoural blood perfusion and flow, and inhibition of pro-apoptotic effects of endothelial cells on T cells, among others. Conversely, VEGF blockade can also cause changes that suppress antitumour immunity, such as increased tumour hypoxia, and reduced intratumoural ingress of co-administered ICIs. As a result, the net clinical benefits from antiangiogenic-ICI combinations will be determined by the balance between the opposing effects of VEGF signalling and its inhibition on the antitumour immune response. In this Perspective, we summarize the results from the currently completed phase III trials evaluating antiangiogenic agent-ICI combinations. We also discuss strategies to improve the efficacy of these combinations, focusing on aspects that include the deleterious functions of VEGF-VEGFR inhibition on antitumour immunity, vessel co-option as a driver of non-angiogenic tumour growth, clinical trial design, or the rationale for drug selection, dosing and scheduling.

Heterogeneity in Liver Cancer Immune Microenvironment: Emerging Single-Cell and Spatial Perspectives

Primary liver cancer is a solid malignancy with a high mortality rate. The success of immunotherapy has shown great promise in improving patient care and highlights a crucial need to understand the complexity of the liver tumor immune microenvironment (TIME). Recent advances in single-cell and spatial omics technologies, coupled with the development of systems biology approaches, are rapidly transforming the landscape of tumor immunology. Here we review the cellular landscape of liver TIME from single-cell and spatial perspectives. We also discuss the cellular interaction networks within the tumor cell community in regulating immune responses. We further highlight the challenges and opportunities with implications for biomarker discovery, patient stratification, and combination immunotherapies.

Present and future of new systemic therapies for early and intermediate stages of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a high mortality neoplasm which usually appears on a cirrhotic liver. The therapeutic arsenal and subsequent prognostic outlook are intrinsically linked to the HCC stage at diagnosis. Notwithstanding the current deployment of treatments with curative intent (liver resection/local ablation and liver transplantation) in early and intermediate stages, a high rate of HCC recurrence persists, underscoring a pivotal clinical challenge. Emergent systemic therapies (ST), particularly immunotherapy, have demonstrate promising outcomes in terms of increase overall survival, but they are currently bound to the advanced stage of HCC. This review provides a comprehensive analysis of the literature, encompassing studies up to March 10, 2024, evaluating the impact of novel ST in the early and intermediate HCC stages, specially focusing on the findings of neoadjuvant and adjuvant regimens, aimed at increasing significantly overall survival and recurrence-free survival after a treatment with curative intent. We also investigate the potential role of ST in enhancing the downstaging rate for the intermediate-stage HCC initially deemed ineligible for treatment with curative intent. Finally, we critically discuss about the current relevance of the results of these studies and the encouraging future implications of ST in the treatment schedules of early and intermediate HCC stages.

Role of peritumoral tissue analysis in predicting characteristics of hepatocellular carcinoma using ultrasound-based radiomics

Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for personalized treatment. This study explored the role of ultrasound-based radiomics of peritumoral tissues for predicting HCC features, focusing on differentiation, cytokeratin 7 (CK7) and Ki67 expression, and p53 mutation status. A cohort of 153 patients with HCC underwent ultrasound examinations and radiomics features were extracted from peritumoral tissues. Subgroups were formed based on HCC characteristics. Predictive modeling was carried out using the XGBOOST algorithm in the differentiation subgroup, logistic regression in the CK7 and Ki67 expression subgroups, and support vector machine learning in the p53 mutation status subgroups. The predictive models demonstrated robust performance, with areas under the curves of 0.815 (0.683-0.948) in the differentiation subgroup, 0.922 (0.785-1) in the CK7 subgroup, 0.762 (0.618-0.906) in the Ki67 subgroup, and 0.849 (0.667-1) in the p53 mutation status subgroup. Confusion matrices and waterfall plots highlighted the good performance of the models. Comprehensive evaluation was carried out using SHapley Additive exPlanations plots, which revealed notable contributions from wavelet filter features. This study highlights the potential of ultrasound-based radiomics, specifically the importance of peritumoral tissue analysis, for predicting HCC characteristics. The results warrant further validation of peritumoral tissue radiomics in larger, multicenter studies.

Bevacizumab induces ferroptosis and enhances CD8+ T cell immune activity in liver cancer via modulating HAT1 and increasing IL-9

Bevacizumab is a recombinant humanized monoclonal immunoglobulin (Ig) G1 antibody of VEGF, and inhibits angiogenesis and tumor growth in hepatocellular carcinoma (HCC). Ferroptosis, a new form of regulated cell death function independently of the apoptotic machinery, has been accepted as an attractive target for pharmacological intervention; the ferroptosis pathway can enhance cell immune activity of anti-PD1 immunotherapy in HCC. In this study we investigated whether and how bevacizumab regulated ferroptosis and immune activity in liver cancer. Firstly, we performed RNA-sequencing in bevacizumab-treated human liver cancer cell line HepG2 cells, and found that bevacizumab significantly altered the expression of a number of genes including VEGF, PI3K, HAT1, SLC7A11 and IL-9 in liver cancer, bevacizumab upregulated 37 ferroptosis-related drivers, and downregulated 17 ferroptosis-related suppressors in particular. We demonstrated that bevacizumab triggered ferroptosis in liver cancer cells by driving VEGF/PI3K/HAT1/SLC7A11 axis. Clinical data confirmed that the expression levels of VEGF were positively associated with those of PI3K, HAT1 and SLC7A11 in HCC tissues. Meanwhile, we found that bevacizumab enhanced immune cell activity in tumor immune-microenvironment. We identified that HAT1 up-regulated miR-143 targeting IL-9 mRNA 3'UTR in liver cancer cells; bevacizumab treatment resulted in the increase of IL-9 levels and its secretion via VEGF/PI3K/HAT1/miR-143/IL-9 axis, which led to the inhibition of tumor growth in vivo through increasing the release of IL-2 and Granzyme B from activated CD8+ T cells. We conclude that in addition to inhibiting angiogenesis, bevacizumab induces ferroptosis and enhances CD8+ T cell immune activity in liver cancer. This study provides new insight into the mechanisms by which bevacizumab synergistically modulates ferroptosis and CD8+ T cell immune activity in liver cancer.

A Novel Nomogram to Predict Prognosis in Elderly Early-Stage Hepatocellular Carcinoma Patients After Ablation Therapy

Purpose

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer. Early diagnosis is crucial for improving prognosis. Elderly HCC patients often have underlying liver diseases such as chronic hepatitis and cirrhosis, leading to impaired liver function and suboptimal liver reserve. Radiofrequency ablation (RFA) has rapidly become one of the most important methods for treating early-stage hepatocellular carcinoma (EHCC) due to its advantages, including minimal trauma, short operation time, less intraoperative bleeding, quick postoperative recovery, cost-effectiveness, and few postoperative-complications. However, the prognostic model for early recurrence after local ablation in elderly EHCC patients has not been widely evaluated. We have developed a prognostic model for the recurrence of local RFA in elderly EHCC patients. This is expected to provide a new early warning system for preventing early recurrence in elderly EHCC patients, prolonging patient's life, and improving overall quality of life.

Methods

In this study, we included 661 EHCC patients who underwent local ablation, dividing them into a Primary cohort and a Validation cohort in a 7:3 ratio. We characterized the cohorts and utilized the primary cohort to develop a prognostic nomogram model for recurrence after local ablation in elderly EHCC patients. Additionally, the validation cohort was used to assess the potential of the nomogram as a non-invasive biomarker for post-ablation recurrence in EHCC.

Results

The user-friendly nomogram incorporates common clinical variables including gender, BCLC stage, tumor number, tumor size, red blood cell (RBC), gamma-glutamyl transferase (GGT), and prothrombin time activity (PTA). The nomogram constructed using the identified seven variables exhibits robust discriminatory capabilities, favorable predictive performance, and noteworthy clinical utility.

Conclusion

We developed a user-friendly nomogram based on the BCLC stage classification, which may provide prognostic assessments for elderly EHCC patients at 1, 3, and 5 years post-RFA.

Dihydroartemisinin breaks the positive feedback loop of YAP1 and GLUT1-mediated aerobic glycolysis to boost the CD8+ effector T cells in hepatocellular carcinoma

Aerobic glycolysis is a hallmark of hepatocellular carcinoma (HCC). Dihydroartemisinin (DHA) exhibits antitumor activity towards liver cancer. Our previous studies have shown that DHA inhibits the Warburg effect in HCC cells. However, the mechanism still needs to be clarified. Our study aimed to elucidate the interaction between YAP1 and GLUT1-mediated aerobic glycolysis in HCC cells and focused on the underlying mechanisms of DHA inhibiting aerobic glycolysis in HCC cells. In this study, we confirmed that inhibition of YAP1 expression lowers GLUT1-mediated aerobic glycolysis in HCC cells and enhances the activity of CD8+T cells in the tumor niche. Then, we found that DHA was bound to cellular YAP1 in HCC cells. YAP1 knockdown inhibited GLUT1-mediated aerobic glycolysis, whereas YAP1 overexpression promoted GLUT1-mediated aerobic glycolysis in HCC cells. Notably, liver-specific Yap1 knockout by AAV8-TBG-Cre suppressed HIF-1α and GLUT1 expression in tumors but not para-tumors in DEN/TCPOBOP-induced HCC mice. Even more crucial is that YAP1 forms a positive feedback loop with GLUT1-mediated aerobic glycolysis, which is associated with HIF-1α in HCC cells. Finally, DHA reduced GLUT1-aerobic glycolysis in HCC cells through YAP1 and prevented the binding of YAP1 and HIF-1α. Collectively, our study revealed the mechanism of DHA inhibiting glycolysis in HCC cells from a perspective of a positive feedback loop involving YAP1 and GLUT1 mediated-aerobic glycolysis and provided a feasible therapeutic strategy for targeting enhanced aerobic glycolysis in HCC.

Intertumoral Heterogeneity Based on MRI Radiomic Features Estimates Recurrence in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) heterogeneity impacts prognosis, and imaging is a potential indicator.

PURPOSE

To characterize HCC image subtypes in MRI and correlate subtypes with recurrence.

STUDY TYPE

Retrospective.

POPULATION

A total of 440 patients (training cohort = 213, internal test cohort = 140, external test cohort = 87) from three centers.

FIELD STRENGTH/SEQUENCE

1.5-T/3.0-T, fast/turbo spin-echo T2-weighted, spin-echo echo-planar diffusion-weighted, contrast-enhanced three-dimensional gradient-recalled-echo T1-weighted with extracellular agents (Gd-DTPA, Gd-DTPA-BMA, and Gd-BOPTA).

ASSESSMENT

Three-dimensional volume-of-interest of HCC was contoured on portal venous phase, then coregistered with precontrast and late arterial phases. Subtypes were identified using non-negative matrix factorization by analyzing radiomics features from volume-of-interests, and correlated with recurrence. Clinical (demographic and laboratory data), pathological, and radiologic features were compared across subtypes. Among clinical, radiologic features and subtypes, variables with variance inflation factor above 10 were excluded. Variables (P < 0.10) in univariate Cox regression were included in stepwise multivariate analysis. Three recurrence estimation models were built: clinical-radiologic model, subtype model, hybrid model integrating clinical-radiologic characteristics, and subtypes.

STATISTICAL TESTS

Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, Fisher's exact test, Kaplan-Meier curves, log-rank test, concordance index (C-index). Significance level: P < 0.05.

RESULTS

Two subtypes were identified across three cohorts (subtype 1:subtype 2 of 86:127, 60:80, and 36:51, respectively). Subtype 1 showed higher microvascular invasion (MVI)-positive rates (53%-57% vs. 26%-31%), and worse recurrence-free survival. Hazard ratio (HR) for the subtype is 6.10 in subtype model. Clinical-radiologic model included alpha-fetoprotein (HR: 3.01), macrovascular invasion (HR: 2.32), nonsmooth tumor margin (HR: 1.81), rim enhancement (HR: 3.13), and intratumoral artery (HR: 2.21). Hybrid model included alpha-fetoprotein (HR: 2.70), nonsmooth tumor margin (HR: 1.51), rim enhancement (HR: 3.25), and subtypes (HR: 5.34). Subtype model was comparable to clinical-radiologic model (C-index: 0.71-0.73 vs. 0.71-0.73), but hybrid model outperformed both (C-index: 0.77-0.79).

CONCLUSION

MRI radiomics-based clustering identified two HCC subtypes with distinct MVI status and recurrence-free survival. Hybrid model showed superior capability to estimate recurrence.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Programmed Death Ligand 1 Expression in Circulating Tumor Cells as a Predictor and Monitor of Response to Atezolizumab plus Bevacizumab Treatment in Patients with Hepatocellular Carcinoma

There remains no reliable biomarker of therapeutic efficacy in hepatocellular carcinoma (HCC) for the PD-L1 inhibitor atezolizumab and bevacizumab (Atezo/Bev). Circulating tumor cells (CTCs) enable the serial collection of living tumor cells. Pre-treatment and serial CTC gene expression changes and tumor histology were evaluated to identify predictors of response to Atezo/Bev. Peripheral blood from 22 patients with HCC treated with Atezo/Bev and 24 patients treated with lenvatinib was serially collected. The RNA expression in CTCs was analyzed using qRT-PCR. Higher PD-L1 expression in pre-treatment CTCs was associated with response and improved prognosis with Atezo/Bev treatment, but not with lenvatinib. There was no correlation between PD-L1 expression in CTCs and that in liver tumor biopsy specimens scored using imaging software. Furthermore, PD-L1 RNA expression in CTCs was dynamically altered by Atezo/Bev, decreasing during effective response and increasing upon progression. CTC-derived RNA collected during Atezo/Bev indicates that patients with higher PD-L1 expression in CTCs at baseline were 3.9 times more responsive to treatment. Therefore, PD-L1 RNA levels in CTCs are an accurate response predictor and may be a monitorable biomarker that changes dynamically to reflect the response during Atezo/Bev treatment.

A prognostic and immune related risk model based on zinc homeostasis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The dysfunction of zinc homeostasis participates in the early and advancing malignancy of HCC. However, the prognostic ability of zinc homeostasis in HCC has not been clarified yet. Here, we showed a zinc-homeostasis related risk model in HCC. Five signature genes including ADAMTS5, PLOD2, PTDSS2, KLRB1, and UCK2 were screened out via survival analyses and regression algorithms to construct the nomogram with clinical characteristics. Experimental researches indicated that UCK2 participated in the progression of HCC. Patients with higher risk scores always had worse outcomes and were more associated with immune suppression according to the analyses of immune related-pathway activation, cell infiltration, and gene expression. Moreover, these patients were likely to exhibit more sensitivity to sorafenib and other antitumor drugs. This study highlights the significant prognostic role of zinc homeostasis and suggests potential treatment strategies in HCC.

Identification of Two Distinct Immune Subtypes in Hepatitis B Virus (HBV)-Associated Hepatocellular Carcinoma (HCC)

HBV is the most common risk factor for HCC development, accounting for almost 50% of cases worldwide. Despite significant advances in immunotherapy, there is limited information on the HBV-HCC tumor microenvironment (TME), which may influence the response to checkpoint inhibitors. Here, we characterize the TME in a unique series of liver specimens from HBV-HCC patients to identify who might benefit from immunotherapy. By combining an extensive immunohistochemistry analysis with the transcriptomic profile of paired liver samples (tumor vs. nontumorous tissue) from 12 well-characterized Caucasian patients with HBV-HCC, we identified two distinct tumor subtypes that we defined immune-high and immune-low. The immune-high subtype, seen in half of the patients, is characterized by a high number of infiltrating B and T cells in association with stromal activation and a transcriptomic profile featuring inhibition of antigen presentation and CTL activation. All the immune-high tumors expressed high levels of CTLA-4 and low levels of PD-1, while PD-L1 was present only in four of six cases. In contrast, the immune-low subtype shows significantly lower lymphocyte infiltration and stromal activation. By whole exome sequencing, we documented that four out of six individuals with the immune-low subtype had missense mutations in the CTNNB1 gene, while only one patient had mutations in this gene in the immune-high subtype. Outside the tumor, there were no differences between the two subtypes. This study identifies two distinctive immune subtypes in HBV-associated HCC, regardless of the microenvironment observed in the surrounding nontumorous tissue, providing new insights into pathogenesis. These findings may be instrumental in the identification of patients who might benefit from immunotherapy.

Intercellular crosstalk between cancer cells and cancer-associated fibroblasts via exosomes in gastrointestinal tumors

Gastrointestinal (GI) tumors are a significant global health threat, with high rates of morbidity and mortality. Exosomes contain various biologically active molecules like nucleic acids, proteins, and lipids and can serve as messengers for intercellular communication. They play critical roles in the exchange of information between tumor cells and the tumor microenvironment (TME). The TME consists of mesenchymal cells and components of the extracellular matrix (ECM), with fibroblasts being the most abundant cell type in the tumor mesenchyme. Cancer-associated fibroblasts (CAFs) are derived from normal fibroblasts and mesenchymal stem cells that are activated in the TME. CAFs can secrete exosomes to modulate cell proliferation, invasion, migration, drug resistance, and other biological processes in tumors. Additionally, tumor cells can manipulate the function and behavior of fibroblasts through direct cell-cell interactions. This review provides a summary of the intercellular crosstalk between GI tumor cells and CAFs through exosomes, along with potential underlying mechanisms.

Noncoding RNAs in Hepatocellular Carcinoma: Potential Applications in Combined Therapeutic Strategies and Promising Candidates of Treatment Response

The incidence of hepatocellular carcinoma (HCC) is increasing, and 40% of patients are diagnosed at advanced stages. Over the past 5 years, the number of clinically available treatments has dramatically increased for HCC, making patient management particularly complex. Immune checkpoint inhibitors (ICIs) have improved the overall survival of patients, showing a durable treatment benefit over time and a different response pattern with respect to tyrosine kinase inhibitors (TKIs). Although there is improved survival in responder cases, a sizeable group of patients are primary progressors or are ineligible for immunotherapy. Indeed, patients with nonviral etiologies, such as nonalcoholic steatohepatitis (NASH), and alterations in specific driver genes might be less responsive to immunotherapy. Therefore, improving the comprehension of mechanisms of drug resistance and identifying biomarkers that are informative of the best treatment approach are required actions to improve patient survival. Abundant evidence indicates that noncoding RNAs (ncRNAs) are pivotal players in cancer. Molecular mechanisms through which ncRNAs exert their effects in cancer progression and drug resistance have been widely investigated. Nevertheless, there are no studies summarizing the synergistic effect between ncRNA-based strategies and TKIs or ICIs in the preclinical setting. This review aims to provide up-to-date information regarding the possible use of ncRNAs as therapeutic targets in association with molecular-targeted agents and immunotherapies and as predictive tools for the selection of optimized treatment options in advanced HCCs.

Big data and artificial intelligence in cancer research

The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.

The Gut Microbiome Controls Liver Tumors via the Vagus Nerve

Liver cancer ranks amongst the deadliest cancers. Nerves have emerged as an understudied regulator of tumor progression. The parasympathetic vagus nerve influences systemic immunity via acetylcholine (ACh). Whether cholinergic neuroimmune interactions influence hepatocellular carcinoma (HCC) remains uncertain. Liver denervation via hepatic vagotomy (HV) significantly reduced liver tumor burden, while pharmacological enhancement of parasympathetic tone promoted tumor growth. Cholinergic disruption in Rag1KO mice revealed that cholinergic regulation requires adaptive immunity. Further scRNA-seq and in vitro studies indicated that vagal ACh dampens CD8+ T cell activity via muscarinic ACh receptor (AChR) CHRM3. Depletion of CD8+ T cells abrogated HV outcomes and selective deletion of Chrm3 on CD8 + T cells inhibited liver tumor growth. Beyond tumor-specific outcomes, vagotomy improved cancer-associated fatigue and anxiety-like behavior. As microbiota transplantation from HCC donors was sufficient to impair behavior, we investigated putative microbiota-neuroimmune crosstalk. Tumor, rather than vagotomy, robustly altered fecal bacterial composition, increasing Desulfovibrionales and Clostridial taxa. Strikingly, in tumor-free mice, vagotomy permitted HCC-associated microbiota to activate hepatic CD8+ T cells. These findings reveal that gut bacteria influence behavior and liver anti-tumor immunity via a dynamic and pharmaceutically targetable, vagus-liver axis.

Biomarkers predicting the efficacy of immune checkpoint inhibitors in hepatocellular carcinoma

In recent years, immune checkpoint inhibitors (ICIs) have emerged as a transformative approach in treating advanced hepatocellular carcinoma (HCC). Despite their success, challenges persist, including concerns about their effectiveness, treatment costs, frequent occurrence of treatment-related adverse events, and tumor hyperprogression. Therefore, it is imperative to identify indicators capable of predicting the efficacy of ICIs treatment, enabling optimal patient selection to maximize clinical benefits while minimizing unnecessary toxic side effects and economic losses. This review paper categorizes prognostic biomarkers of ICIs treatment into the following categories: biochemical and cytological indicators, tumor-related markers, imaging and personal features, etiology, gut microbiome, and immune-related adverse events (irAEs). By organizing these indicators systematically, we aim to guide biomarker exploration and inform clinical treatment decisions.