Biomarkers for response to immunotherapy in hepatobiliary malignancies

Systemic chemotherapy improves outcome of hepatocellular carcinoma patients treated with transarterial chemoembolization

BACKGROUND

Transarterial chemoembolization (TACE) based neoadjuvant therapy was proven effective in hepatocellular carcinoma (HCC). Recently, tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) also showed promise in HCC treatment. However, the prognostic benefits associated with these treatments remain uncertain. This study aimed to explore the relationship between pathologic response and prognostic features in HCC patients who received neoadjuvant therapy.

METHODS

HCC patients who received TACE either with or without TKIs/ICIs as neoadjuvant therapy before liver resection were retrospectively collected from the First Affiliated Hospital, Zhejiang University School of Medicine in China. Pathologic response was determined by calculating the proportion of non-viable area within the tumor. Major pathologic response (MPR) was defined as the presence of non-viable tumor cells reaching a minimum of 90%. Complete pathologic response (CPR) was characterized by the absence of viable cells observed in the tumor.

RESULTS

A total of 481 patients meeting the inclusion criteria were enrolled, with 76 patients (15.8%) achieving CPR and 179 (37.2%) reaching MPR. The median recurrence-free survival (mRFS) in the CPR + MPR group was significantly higher than the non-MPR group (31.3 vs. 25.1 months). The difference in 3-year overall survival (OS) rate was not significant. Multivariate Cox regression analysis identified failure to achieve MPR (hazard ratio = 1.548, 95% confidence interval: 1.122-2.134; P = 0.008), HBsAg positivity (HR = 1.818, 95% CI: 1.062-3.115, P = 0.030), multiple lesions (HR = 2.278, 95% CI: 1.621-3.195, P < 0.001), and baseline tumor size > 5 cm (HR = 1.712, 95% CI: 1.031-2.849, P = 0.038) were independent risk factors for RFS. Subgroup analysis showed that 67 of 93 (72.0%) patients who received the combination of TACE, TKIs, and ICIs achieved MPR + CPR.

CONCLUSIONS

In individuals who received TACE-based neoadjuvant therapy for HCC, failure to achieve MPR emerges as an independent risk factor for RFS. Notably, the combination of TACE, TKIs, and ICIs demonstrated the highest rate of MPR.

Advances in the relationship of immune checkpoint inhibitors and DNA damage repair

Cancer immunotherapy, alongside surgery, radiation therapy, and chemotherapy, has emerged as a key treatment modality. Immune checkpoint inhibitors (ICIs) represent a promising immunotherapy that plays a critical role in the management of various solid tumors. However, the limited efficacy of ICI monotherapy and the development of primary or secondary resistance to combination therapy remain a challenge. Consequently, identifying molecular markers for predicting ICI efficacy has become an area of active clinical research. Notably, the correlation between DNA damage repair (DDR) mechanisms and the effectiveness of ICI treatment has been established. This review outlines the two primary pathways of DDR, namely, the homologous recombination repair pathway and the mismatch repair pathway. The relationship between these key genes and ICIs has been discussed and the potential of these genes as molecular markers for predicting ICI efficacy summarized.

Prognostic significance of postoperative serological incomplete conversion of AFP and PIVKA-II after hepatic resection for hepatocellular carcinoma: a multicenter analysis of 1755 patients

BACKGROUND

The value of serum biomarkers, particularly alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II), gains increasing attention in prognostic evaluation and recurrence monitoring for patients with hepatocellular carcinoma (HCC). This study investigated the implications of serological incomplete conversion (SIC) of these 2 biomarkers as prognostic indicators for long-term outcomes after HCC resection.

METHODS

A multicenter observational study was conducted on a cohort of HCC patients presenting with AFP (>20 ng/mL) or PIVKA-II (>40 mAU/mL) positivity who underwent curative-intent resection. Based on their postoperative AFP and PIVKA-II levels at first postoperative follow-up (4~8 weeks after surgery), these patients were stratified into the serological incomplete conversion (SIC) and serological complete conversion (SCC) groups. The study endpoints were recurrence and overall survival (OS).

RESULTS

Among 1755 patients, 379 and 1376 were categorized as having SIC and SCC, respectively. The SIC group exhibited 1- and 5-year OS rates of 67.5% and 26.3%, with the corresponding recurrence rates of 53.2% and 79.0%, respectively; while the SCC group displayed 1- and 5-year OS rates of 95.8% and 62.5%, with the corresponding recurrence rates of 16.8% and 48.8%, respectively (both P < .001). Multivariate Cox regression analysis demonstrated that postoperative SIC was an independent risk factor for both increased recurrence (HR: 2.40, 95% CI, 2.04-2.81, P < .001) and decreased OS (HR: 2.69, 95% CI, 2.24-3.24, P < .001).

CONCLUSION

The results emphasize that postoperative incomplete conversion of either AFP or PIVKA-II is a significant prognostic marker, indicating a higher risk for adverse oncologic outcomes following HCC resection. This revelation has crucial implications for refining postoperative adjuvant therapy and surveillance strategies for HCC patients.

Hepatocellular Carcinoma Immunotherapy: Predictors of Response, Issues, and Challenges

Immune checkpoint inhibitors (ICIs), such as durvalumab, tremelimumab, and atezolizumab, have emerged as a significant therapeutic option for the treatment of hepatocellular carcinoma (HCC). In fact, the efficacy of ICIs as single agents or as part of combination therapies has been demonstrated in practice-changing phase III clinical trials. However, ICIs confront several difficulties, including the lack of predictive biomarkers, primary and secondary drug resistance, and treatment-related side effects. Herein, we provide an overview of current issues and future challenges in this setting.

CT radiomics-based biomarkers can predict response to immunotherapy in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) remains a leading cause of cancer deaths. Despite the rise of immunotherapies, many HCC patients don't benefit. There's a clear need for biomarkers to guide treatment decisions. This research aims to identify such biomarkers by combining radiological data and machine learning. We analyzed clinical and CT imaging data of 54 HCC patients undergoing immunotherapy. Radiologic features were examined to develop a model predicting short-term immunotherapy effects. We utilized 9 machine learning and 2 ensemble learning techniques using RapidMiner for model construction. We conducted the validation of the above feature combination using 29 HCC patients who received immunotherapy from another hospital, and tested and validated it using XGBoost combined with a genetic algorithm. In 54 HCC patients, radiomics features varied significantly between those with partial response (PR) and stable disease (SD). Key features in Gray Level Run Length Matrix (GLRLM) and in adjacent tissues' Intensity Direct, Neighborhood Gray Tone Difference Matrix (NGTDM), and Shape correlated with short-term immunotherapy efficacy. Selected feature combinations of 15, 19, and 8/15 features yielded better outcomes. Deep learning, random forest, and naive bayes outperformed other methods, with Bagging being more reliable than Adaboost. In the validation set of 29 HCC patients, the mentioned feature combination also demonstrated favorable performance. Furthermore, we achieved improved results when employing XGBoost in conjunction with a genetic algorithm for testing and validation. The machine learning model built with CT image features derived from GLCM, GLRLM, IntensityDirect, NGTDM, and Shape can accurately forecast the short-term efficacy of immunotherapy for HCC.

PAK1 inhibition increases TRIM21-induced PD-L1 degradation and enhances responses to anti-PD-1 therapy in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDA) is a common malignancy with a 5-year survival <10 %. Immunosuppressive tumor microenvironment (TME) plays a critical role in the progression of PDA. In recent years, programmed death-ligand 1 (PD-L1)/programmed cell death protein-1 (PD-1) blockade has emerged as a potent anti-tumor immunotherapy, while is yet to achieve significant clinical benefits for PDA patients. P21-Activated kinase 1 (PAK1) is highly upregulated in PDA and has been reported to be involved in the regulation of anti-tumor immunity. This study aims to investigate the combined effect of PAK1 inhibition and anti-PD-1 therapy on PDA and the underlying mechanisms. We have shown that PAK1 expression positively correlated with PD-L1 in PDA patients, and that inhibition of PAK1 downregulated PD-L1 expression of PDA cells. More importantly, we have demonstrated that PAK1 competed with PD-L1 in binding to tripartite motif-containing protein 21 (TRIM21), a ubiquitin E3 ligase, resulting in less ubiquitination and degradation of PD-L1. Moreover, PAK1 inhibition promoted CD8+ T cells activation and infiltration. In a murine PDA model, the combination of PAK1 inhibition and anti-PD-1 therapy showed significant anti-tumor effects compared with the control or monotherapy. Our results indicated that the combination of PAK1 inhibition and anti-PD-1 therapy would be a more effective treatment for PDA patients.

The interaction between intratumoral bacteria and metabolic distortion in hepatocellular carcinoma

BACKGROUND

Intratumoral bacteria might play essential roles in tumorigenesis in different cancer types. However, its features and potential roles in hepatocellular carcinoma (HCC) are largely unknown.

METHODS

In this study, we assessed bacterial RNA by 16S rRNA fluorescence in situ hybridization and detected bacterial lipopolysaccharide (LPS) via immunohistochemistry. Hepa1-6 cells were used to establish orthotopic HCC models in mice. 2bRAD sequencing for microbiome was performed to determine the intratumoral bacterial characteristics, and liquid chromatography-mass spectrometry was conducted to explore the metabolic profile. The potential association between different intratumoral microbiota and metabolites were evaluated.

RESULTS

We detected bacterial 16S rRNA and LPS in HCC tissues from the patients with HCC. In HCC mouse model, we found that the intratumor bacteria in HCC tissues were significantly different to adjacent nontumor tissues. Furthermore, we observed different metabolites in HCC tissues and adjacent nontumor tissues, such as N-acetyl-D-glucosamine and a-lactose. Our results showed that several bacteria were significantly associated with metabolites, such as Pseudomonas koreensis, which was positively correlated with N-acetyl-D-glucosamine and negatively correlated with citrulline.

CONCLUSIONS

This study confirmed the close association between different bacteria and metabolites, which might provide novel opportunities for developing new biomarkers and therapeutic targets for HCC.

Systemic therapies in hepatocellular carcinoma: A revolution?

The evolution in systemic therapies in hepatocellular carcinoma (HCC) signifies a strategy of high-cost, high-gain innovation that originated with sorafenib, despite its limited impact on tumor response. This strategic approach paved the way for the emergence of a second wave of the short-lived competitive advantage, exemplified by the incorporation of atezolizumab plus bevacizumab and tremelimumab plus durvalumab. In the context of safety concerns within the liver cancer domain, the IMBRAVE150 and HIMALAYA trials boldly incorporated bevacizumab and tremelimumab, respectively, demonstrating the continuation of the high-risk, high-reward innovation paradigm. This review delves into the strengths, weaknesses, opportunities, and threats analysis of systemic therapies in the field of HCC.

Hepatocellular carcinoma immune prognosis score predicts the clinical outcomes of hepatocellular carcinoma patients receiving immune checkpoint inhibitors

OBJECTIVE

The predictive biomarkers of immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) still need to be further explored. This study aims to establish a new immune prognosis biomarker to predict the clinical outcomes of hepatocellular carcinoma patients receiving immune checkpoint inhibitors.

METHODS

The subjects of this study were 151 HCC patients receiving ICIs at Harbin Medical University Cancer Hospital from January 2018 to December 2021. This study collected a wide range of blood parameters from patients before treatment and used Cox's regression analysis to identify independent prognostic factors in blood parameters, as well as their β coefficient. The hepatocellular carcinoma immune prognosis score (HCIPS) was established through Lasso regression analysis and COX multivariate analysis. The cut-off value of HCIPS was calculated from the receiver operating characteristic (ROC) curve. Finally, the prognostic value of HCIPS was validated through survival analysis, stratified analyses, and nomograms.

RESULTS

HCIPS was composed of albumin (ALB) and thrombin time (TT), with a cut-off value of 0.64. There were 56 patients with HCIPS < 0.64 and 95 patients with HCIPS ≥ 0.64, patients with low HCIPS were significantly related to shorter progression-free survival (PFS) (13.10 months vs. 1.63 months, P < 0.001) and overall survival (OS) (14.83 months vs. 25.43 months, P < 0.001). HCIPS has also been found to be an independent prognostic factor in this study. In addition, the stratified analysis found a significant correlation between low HCIPS and shorter OS in patients with tumor size ≥ 5 cm (P of interaction = 0.032). The C-index and 95% CI of the nomograms for PFS and OS were 0.730 (0.680-0.779) and 0.758 (0.711-0.804), respectively.

CONCLUSIONS

As a new score established based on HCC patients receiving ICIs, HCIPS was significantly correlated with clinical outcomes in patients with ICIs and might serve as a new biomarker to predict HCC patients who cloud benefit from ICIs.

Biomarkers for immunotherapy of hepatocellular carcinoma

Immune-checkpoint inhibitors (ICIs) are now widely used for the treatment of patients with advanced-stage hepatocellular carcinoma (HCC). Two different ICI-containing regimens, atezolizumab plus bevacizumab and tremelimumab plus durvalumab, are now approved standard-of-care first-line therapies in this setting. However, and despite substantial improvements in survival outcomes relative to sorafenib, most patients with advanced-stage HCC do not derive durable benefit from these regimens. Advances in genome sequencing including the use of single-cell RNA sequencing (both of tumour material and blood samples), as well as immune cell identification strategies and other techniques such as radiomics and analysis of the microbiota, have created considerable potential for the identification of novel predictive biomarkers enabling the accurate selection of patients who are most likely to derive benefit from ICIs. In this Review, we summarize data on the immunology of HCC and the outcomes in patients receiving ICIs for the treatment of this disease. We then provide an overview of current biomarker use and developments in the past 5 years, including gene signatures, circulating tumour cells, high-dimensional flow cytometry, single-cell RNA sequencing as well as approaches involving the microbiome, radiomics and clinical markers. Novel concepts for further biomarker development in HCC are then discussed including biomarker-driven trials, spatial transcriptomics and integrated 'big data' analysis approaches. These concepts all have the potential to better identify patients who are most likely to benefit from ICIs and to promote the development of new treatment approaches.

Identification of a brand intratumor microbiome signature for predicting prognosis of hepatocellular carcinoma

PURPOSE

Given that prognosis of hepatocellular carcinoma (HCC) differs dramatically, it is imperative to uncover effective and available prognostic biomarker(s). The intratumor microbiome plays a significant role in the response to tumor microenvironment, we aimed to identify an intratumor microbiome signature for predicting the prognosis of HCC patients accurately and investigate its possible mechanisms subsequently.

METHODS

The TCGA HCC microbiome data (TCGA-LIHC-microbiome) was downloaded from cBioPortal. To create an intratumor microbiome-related prognostic signature, univariate and multivariate Cox regression analyses were used to quantify the association of microbial abundance and patients' overall survival (OS), as well as their diseases specific survival (DSS). The performance of the scoring model was evaluated by the area under the ROC curve (AUC). Based on the microbiome-related signature, clinical factors, and multi-omics molecular subtypes on the basis of "icluster" algorithm, nomograms were established to predict OS and DSS. Patients were further clustered into three subtypes based on their microbiome-related characteristics by consensus clustering. Moreover, deconvolution algorithm, weighted correlation network analysis (WGCNA) and gene set variation analysis (GSVA) were used to investigate the potential mechanisms.

RESULTS

In TCGA LIHC microbiome data, the abundances of 166 genera among the total 1406 genera were considerably associated with HCC patients' OS. From that filtered dataset we identified a 27-microbe prognostic signature and developed a microbiome-related score (MRS) model. Compared with those in the relatively low-risk group, patients in higher-risk group own a much worse OS (P < 0.0001). Besides, the time-dependent ROC curves with MRS showed excellent predictive efficacy both in OS and DSS. Moreover, MRS is an independent prognostic factor for OS and DSS over clinical factors and multi-omics-based molecular subtypes. The integration of MRS into nomograms significantly improved the efficacy of prognosis prediction (1-year AUC:0.849, 3-year AUC: 0.825, 5-year AUC: 0.822). The analysis of microbiome-based subtypes on their immune characteristics and specific gene modules inferred that the intratumor microbiome may affect the HCC patients' prognosis via modulating the cancer stemness and immune response.

CONCLUSION

MRS, a 27 intratumor microbiome-related prognostic model, was successfully established to predict HCC patients overall survive independently. And the possible underlying mechanisms were also investigated to provide a potential intervention strategy.

The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging

In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.

ATRA sensitized the response of hepatocellular carcinoma to Sorafenib by downregulation of p21-activated kinase 1

BACKGROUND

Sorafenib resistance greatly reduces the efficacy of treatments in advanced hepatocellular carcinoma (HCC) patients, but the underlying mechanisms are not thoroughly understood. All-trans retinoic acid (ATRA), an anti-leukaemia agent, has attracted considerable attention due to its role in sensitizing cells to other anticancer treatments. We aimed to investigate the combined effect of ATRA and Sorafenib on HCC and the underlying mechanisms.

METHODS

CCK-8, cell sphere formation, trans-well migration, and wound-healing assays were used to analyse the biological behaviours of HCC cells in vitro. Western blotting and qRT-PCR analysis were conducted to measure the expression of p21 activated kinase 1 (PAK1) and phospho-p21 activated kinase 1 (pPAK1). Xenograft models were established to confirm the synergistic effects of ATRA and Sorafenib in vivo. TUNEL assays and immunohistochemistry were utilized to determine apoptosis, proliferation, PAK1 and pPAK1 levels in tumour tissues.

RESULTS

We observed that PAK1 was overexpressed in HCC, and its expression was negatively correlated with the survival of patients. PAK1 promoted the proliferation, self-renewal and epithelial-mesenchymal transition of HCC cells. Correlation analysis indicated that the IC50 of Sorafenib was positively correlated with the level of pPAK1 in HCC cell lines. ATRA inhibited the progression of HCC and sensitized HCC response to Sorafenib by downregulation of PAK1, as shown by the calculated coefficient of drug interaction and the data obtained from xenograft models.

CONCLUSIONS

Our findings indicated that instead of treatment with Sorafenib alone, the combination of ATRA and Sorafenib provides a more effective treatment for HCC patients. Video Abstract.

Association of the pretreatment lung immune prognostic index with immune checkpoint inhibitor outcomes in patients with advanced hepatocellular carcinoma

OBJECTIVE

To evaluate whether the pretreatment Lung Immune Prognostic Index (LIPI) is associated with outcomes in advanced hepatocellular carcinoma (HCC) patients under ICI.

METHODS

A two-center retrospective study of patients with HCC treated with immune checkpoint inhibitors (ICIs) between January 2018 and January 2021 was performed. Based on pretreatment derived neutrophils/ (leukocytes minus neutrophils) ratio (dNLR) greater than 3 and a lactate dehydrogenase (LDH) level greater than the normal value, patients were stratified into three groups (good LIPI:0 risk factor, intermediate LIPI: 1 risk factor, and poor LIPI: 2 risk factors). The primary endpoints were overall survival (OS) and progression-free survival (PFS). The second endpoints were disease control rate (DCR) and objective response rate (ORR).

RESULTS

In the pooled cohort (n = 224), 80 (35.7%) had a good LIPI (zero factor), 91 (40.6%) had intermediate LIPI (one factor), and 53 (23.7%) had poor LIPI (two factors). The median follow-up was 25.1 months. Median OS was 16.8 months, 12.5 months, and 9.5 months for the good, intermediate, and poor LIPI groups, respectively (P < 0.0001). Median PFS was 11.8 months, 7.8 months, and 4.0 months for the good, intermediate, and poor LIPI groups, respectively (P < 0.0001). Multivariate analysis indicated that the intermediate LIPI and poor LIPI both were independently associated with OS, PFS, and ORR, DCR (P < 0.05), as risk factors.

CONCLUSION

Pretreatment LIPI was correlated with worse outcomes for ICIs suggesting that LIPI could be promising biomarker for advanced HCC patients under ICIs.

Immuno-genomic-radiomics to predict response of biliary tract cancer to camrelizumab plus GEMOX in a single-arm phase II trial

Background & Aims

Immunotherapy is an option for the treatment of advanced biliary tract cancer (BTC), although it has a low response rate. In this post hoc analysis, we investigated the predictive value of an immuno-genomic-radiomics (IGR) analysis for patients with BTC treated with camrelizumab plus gemcitabine and oxaliplatin (GEMOX) therapy.

Methods

Thirty-two patients with BTC treated with camrelizumab plus GEMOX were prospectively enrolled. The relationship between high-throughput computed tomography (CT) radiomics features with immuno-genomic expression was tested and scaled with a full correlation matrix analysis. Odds ratio (OR) of IGR expression for objective response to camrelizumab plus GEMOX was tested with logistic regression analysis. Association of IGR expression with progression-free survival (PFS) and overall survival (OS) was analysed with a Cox proportional hazard regression.

Results

CT radiomics correlated with CD8⁺ T cells (r = -0.72-0.71, p = 0.004-0.047), tumour mutation burden (TMB) (r = 0.59, p = 0.039), and ARID1A mutation (r = -0.58-0.57, p = 0.020-0.034). There was no significant correlation between radiomics and programmed cell death protein ligand 1 expression (p >0.96). Among all IGR biomarkers, only four radiomics features were independent predictors of objective response (OR = 0.09-3.81; p = 0.011-0.044). Combining independent radiomics features into an objective response prediction model achieved an area under the curve of 0.869. In a Cox analysis, radiomics signature [hazard ratio (HR) = 6.90, p <0.001], ARID1A (HR = 3.31, p = 0.013), and blood TMB (HR = 1.13, p = 0.023) were independent predictors of PFS. Radiomics signature (HR = 6.58, p <0.001) and CD8⁺ T cells (HR = 0.22, p = 0.004) were independent predictors of OS. Prognostic models integrating these features achieved concordance indexes of 0.677 and 0.681 for PFS and OS, respectively.

Conclusions

Radiomics could act as a non-invasive immuno-genomic surrogate of BTC, which could further aid in response prediction for patients with BTC treated with immunotherapy. However, multicenter and larger sample studies are required to validate these results.

Impact and implications

Immunotherapy is an alternative for the treatment of advanced BTC, whereas tumour response is heterogeneous. In a post hoc analysis of the single-arm phase II clinical trial (NCT03486678), we found that CT radiomics features were associated with the tumour microenvironment and that IGR expression was a promising marker for tumour response and long-term survival.

Clinical trial number

Post hoc analysis of NCT03486678.