Intratumor heterogeneity in hepatocellular carcinoma

Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma

Objectives

Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders.

Materials & methods

This was a retrospective analysis involving 120 patients with unresectable HCC. They were divided into training (n = 72) and validation (n = 48) cohorts. We developed an interpretable deep learning model using multiphase computed tomography (CT) images to predict whether patients will respond or not to CLICI treatment, based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). We evaluated the models' performance and analyzed the impact of each CT phase. Critical regions influencing predictions were identified and visualized through heatmaps.

Results

The multiphase model outperformed the best biphase and uniphase models, achieving an area under the curve (AUC) of 0.802 (95% CI = 0.780-0.824). The portal phase images were found to significantly enhance the model's predictive accuracy. Heatmaps identified six critical features influencing treatment response, offering valuable insights to clinicians. Additionally, we have made this model accessible via a web server at http://uhccnet.com/ for ease of use.

Conclusions

The integration of multiphase CT images with deep learning-generated heatmaps for predicting treatment response provides a robust and practical tool for guiding CLICI therapy in patients with unresectable HCC.

Indolent cancer and pattern of progression: Two missing parameters in trial design for hepatology

The indolent and aggressive behaviors of HCC might have a role in clinical trial (CT) results; however, the indolent HCC is less analyzed compared to others cancer. Indolent profile could be characterized as follows: (1) patients with low risk of progression itself due to the HCC molecular profile and/or due to the interaction between cancer cell their microenvironment; (2) patients who achieve objective response or present spontaneous regression; and (3) patients who develop radiological progression with no consequence on either the liver function or general status, and without trigger a change in the tumor stage. Patients with "indolent HCC" generally never develop cancer-related symptoms neither die for HCC-related causes. Thus, we hypothesize that the imbalance in the proportion of "indolent" versus "aggressive HCC" between arms or the underestimation/overestimation of HCC behavior at baseline in single-arm CT could be associated with CT failure or under-overestimation of trial results. The "indolent progression" may also explain the discrepancy between radiological progression-based end points and survival. Moreover, we discuss the related causes that explain the indolent profile of HCC and propose (1) refining the progression-related end point by the pattern of progression to minimize the limitations of the current end points; (2) considering alternative statistical tools for survival analysis such as milestone survival, or restricted mean survival time to capture the value of indolent HCC. According to these considerations, we propose incorporating novel end points into the single arm of phase I/II CT as exploratory analysis or as a secondary end point in phase III CT.

The association between tumour heterogeneity and immune evasion mechanisms in hepatocellular carcinoma and its clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. The emergence of combination therapy, atezolizumab (anti-PDL1, immune checkpoint inhibitor) and bevacizumab (anti-VEGF) has revolutionised the management of HCC. Despite this breakthrough, the best overall response rate with first-line systemic therapy is only about 30%, owing to intra-tumoural heterogeneity, complex tumour microenvironment and the lack of predictive biomarkers. Many groups have attempted to classify HCC based on the immune microenvironment and have consistently observed better outcomes in immunologically "hot" HCC. We summarised possible mechanisms of tumour immune evasion based on the latest literature and the rationale for combination/sequential therapy to improve treatment response. Lastly, we proposed future strategies and therapies to overcome HCC immune evasion to further improve treatment outcomes of HCC.

Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

Multi-b-value DWI to evaluate the synergistic antiproliferation and anti-heterogeneity effects of bufalin plus sorafenib in an orthotopic HCC model

BACKGROUND

Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed synergistic effects of bufalin+sorafenib in orthotopic HCC-LM3 xenograft nude mice by using intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), a stretched exponential model (SEM), and a fractional-order calculus (FROC) model.

METHODS

Twenty-four orthotopic HCC-LM3 xenograft mice were divided into bufalin+sorafenib, bufalin, sorafenib treatment groups, and a control group. Multi-b-value DWI was performed using a 3-T scanner after 3 weeks' treatment to obtain true diffusion coefficient Dt, pseudo-diffusion coefficient Dp, perfusion fraction f, mean diffusivity (MD), mean kurtosis (MK), distributed diffusion coefficient (DDC), heterogeneity index α, diffusion coefficient D, fractional order parameter β, and microstructural quantity μ. Necrotic fraction (NF), standard deviation (SD) of hematoxylin-eosin staining, and microvessel density (MVD) of anti-CD31 staining were evaluated. Correlations of DWI parameters with histopathological results were analyzed, and measurements were compared among four groups.

RESULTS

In the final 22 mice, f positively correlated with MVD (r = 0.679, p = 0.001). Significantly good correlations of MK (r = 0.677), α (r = -0.696), and β (r= -0.639) with SD were observed (all p < 0.010). f, MK, MVD, and SD were much lower, while MD, α, β, and NF were higher in bufalin plus sorafenib group than control group (all p < 0.050).

CONCLUSION

Evaluated by IVIM, DKI, SEM, and FROC, bufalin+sorafenib was found to inhibit tumor proliferation and angiogenesis and reduce spatial heterogeneity in HCC-LM3 models.

RELEVANCE STATEMENT

Multi-b-value DWI provides potential metrics for evaluating the efficacy of treatment in HCC.

KEY POINTS

• Bufalin plus sorafenib combination may increase the effectiveness of HCC therapy. • Multi-b-value DWI depicted HCC proliferation, angiogenesis, and spatial heterogeneity. • Multi-b-value DWI may be a noninvasive method to assess HCC therapeutic efficacy.

Decoding the basis of histological variation in human cancer

Molecular abnormalities that shape human neoplasms dissociate their phenotypic landscape from that of the healthy counterpart. Through the lens of a microscope, tumour pathology optically captures such aberrations projected onto a tissue slide and has categorized human epithelial neoplasms into distinct histological subtypes based on the diverse morphogenetic and molecular programmes that they manifest. Tumour histology often reflects tumour aggressiveness, patient prognosis and therapeutic vulnerability, and thus has been used as a de facto diagnostic tool and for making clinical decisions. However, it remains elusive how the diverse histological subtypes arise and translate into pleiotropic biological phenotypes. Molecular analysis of clinical tumour tissues and their culture, including patient-derived organoids, and add-back genetic reconstruction of tumorigenic pathways using gene engineering in culture models and rodents further elucidated molecular mechanisms that underlie morphological variations. Such mechanisms include genetic mutations and epigenetic alterations in cellular identity codes that erode hard-wired morphological programmes and histologically digress tumours from the native tissues. Interestingly, tumours acquire the ability to grow independently of the niche-driven stem cell ecosystem along with these morphological alterations, providing a biological rationale for histological diversification during tumorigenesis. This Review comprehensively summarizes our current understanding of such plasticity in the histological and lineage commitment fostered cooperatively by molecular alterations and the tumour environment, and describes basic and clinical implications for future cancer therapy.

Adjuvant and neoadjuvant therapies for hepatocellular carcinoma

Immune-oncology-based regimens have shown efficacy in advanced HCC and have been implemented as standard of care as first-line therapy. Their efficacy, including high response rates, and safety justify their evaluation in earlier disease stages. Following negative results for adjuvant sorafenib in the global STORM trial in 2015, 4 global phase 3 trials, featuring different immune checkpoint inhibitor combinations, entered in parallel the race in the adjuvant setting. The IMbrave050 trial, comparing adjuvant atezolizumab in combination with bevacizumab to active surveillance following curative-intent resection or ablation, was the first to report, fast-tracking the results of the first interim analysis and demonstrating an improvement in recurrence-free survival. The trial has provoked a discussion on the horizon of expectations from adjuvant treatment and the clinical relevance of efficacy endpoints. Moreover, major pathological responses reported from early phase 2 data in the neoadjuvant setting provide a strong rationale for the evaluation of these concepts in phase 3 trials. In this review, we summarize current evidence and outline future directions for systemic therapies in early-stage HCC.

Deep Learning for the Pathologic Diagnosis of Hepatocellular Carcinoma, Cholangiocarcinoma, and Metastatic Colorectal Cancer

Diagnosing primary liver cancers, particularly hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC), is a challenging and labor-intensive process, even for experts, and secondary liver cancers further complicate the diagnosis. Artificial intelligence (AI) offers promising solutions to these diagnostic challenges by facilitating the histopathological classification of tumors using digital whole slide images (WSIs). This study aimed to develop a deep learning model for distinguishing HCC, CC, and metastatic colorectal cancer (mCRC) using histopathological images and to discuss its clinical implications. The WSIs from HCC, CC, and mCRC were used to train the classifiers. For normal/tumor classification, the areas under the curve (AUCs) were 0.989, 0.988, and 0.991 for HCC, CC, and mCRC, respectively. Using proper tumor tissues, the HCC/other cancer type classifier was trained to effectively distinguish HCC from CC and mCRC, with a concatenated AUC of 0.998. Subsequently, the CC/mCRC classifier differentiated CC from mCRC with a concatenated AUC of 0.995. However, testing on an external dataset revealed that the HCC/other cancer type classifier underperformed with an AUC of 0.745. After combining the original training datasets with external datasets and retraining, the classification drastically improved, all achieving AUCs of 1.000. Although these results are promising and offer crucial insights into liver cancer, further research is required for model refinement and validation.

Metabolic reprogramming and its clinical implication for liver cancer

Cancer cells often encounter hypoxic and hypo-nutrient conditions, which force them to make adaptive changes to meet their high demands for energy and various biomaterials for biomass synthesis. As a result, enhanced catabolism (breakdown of macromolecules for energy production) and anabolism (macromolecule synthesis from bio-precursors) are induced in cancer. This phenomenon is called "metabolic reprogramming," a cancer hallmark contributing to cancer development, metastasis, and drug resistance. HCC and cholangiocarcinoma (CCA) are 2 different liver cancers with high intertumoral heterogeneity in terms of etiologies, mutational landscapes, transcriptomes, and histological representations. In agreement, metabolism in HCC or CCA is remarkably heterogeneous, although changes in the glycolytic pathways and an increase in the generation of lactate (the Warburg effect) have been frequently detected in those tumors. For example, HCC tumors with activated β-catenin are addicted to fatty acid catabolism, whereas HCC tumors derived from fatty liver avoid using fatty acids. In this review, we describe common metabolic alterations in HCC and CCA as well as metabolic features unique for their subsets. We discuss metabolism of NAFLD as well, because NAFLD will likely become a leading etiology of liver cancer in the coming years due to the obesity epidemic in the Western world. Furthermore, we outline the clinical implication of liver cancer metabolism and highlight the computation and systems biology approaches, such as genome-wide metabolic models, as a valuable tool allowing us to identify therapeutic targets and develop personalized treatments for liver cancer patients.

[18F] AlF-NOTA-FAPI-04 PET/CT can predict treatment response and survival in patients receiving chemotherapy for inoperable pancreatic ductal adenocarcinoma

PURPOSE

We investigated whether uptake of [18F] AlF-NOTA-FAPI-04 on positron emission tomography/computed tomography (PET/CT) could predict treatment response and survival in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

We prospectively evaluated 47 patients with histopathologically confirmed primary PDAC who provided pretreatment [18F] AlF-NOTA-FAPI-04 scans to detect fibroblast activation protein (FAP) on the tumor surface by uptake of [18F] AlF-NOTA-FAPI-04. PDAC specimens were immunohistochemically stained with cancer-associated fibroblast (CAF) markers. We obtained a second PET scan after one cycle of chemotherapy to study changes in FAPI uptake variables from before to during treatment. Correlations between baseline PET variables and CAF-related immunohistochemical markers were assessed with Spearman's rank test. Cox regression and Kaplan-Meier methods were used to assess relationships between disease progression and potential predictors. Receiver operating characteristic (ROC) curve analysis was used to define the optimal cut-off points for distinguishing patients according to good response vs. poor response per RECIST v.1.1.

RESULTS

The FAPI PET variables maximum and mean standardized uptake values (SUVmax, SUVmean), metabolic tumor volume (MTV), and total lesion FAP expression (TLF) were positively correlated with CAF markers (FAP, α-smooth muscle actin, vimentin, S100A4, and platelet-derived growth factor receptor α/β, all P < 0.05). MTV was associated with survival in patients with inoperable PDAC (all P < 0.05). Cox multivariate regression showed that MTV was associated with overall survival (MTV hazard ratio [HR] = 1.016, P = 0.016). Greater changes from before to during chemotherapy in SUVmax, MTV, and TLF were associated with good treatment response (all P < 0.05). ΔMTV, ΔTLF, and ΔSUVmax had larger areas under the curve than ΔCA19-9 for predicting treatment response. Kaplan-Meier analysis showed that the extent of change in MTV and TLF from before to after treatment predicted progression-free survival, with cut-off values (based on medians) of - 4.95 for ΔMTV (HR = 8.09, P = 0.013) and - 77.83 for ΔTLF (HR = 4.62, P = 0.012).

CONCLUSIONS

A higher baseline MTV on [18F] AlF-NOTA-FAPI-04 scans was associated with poorer survival in patients with inoperable PDAC. ΔMTV was more sensitive for predicting response than ΔCA19-9. These results are clinically meaningful for identifying patients with PDAC who are at high risk of disease progression.

Targeted Molecular Profiling of Circulating Cell-Free DNA in Patients With Advanced Hepatocellular Carcinoma

PURPOSE

Next-generation sequencing (NGS) of tumor-derived, circulating cell-free DNA (cfDNA) may aid in diagnosis, prognostication, and treatment of patients with hepatocellular carcinoma (HCC). The operating characteristics of cfDNA mutational profiling must be determined before routine clinical implementation.

METHODS

This was a single-center, retrospective study with the primary objective of defining genomic alterations in circulating cfDNA along with plasma-tissue genotype agreement between NGS of matched tumor samples in patients with advanced HCC. cfDNA was analyzed using a clinically validated 129-gene NGS assay; matched tissue-based NGS was analyzed with a US Food and Drug Administration-authorized NGS tumor assay.

RESULTS

Fifty-three plasma samples from 51 patients with histologically confirmed HCC underwent NGS-based cfDNA analysis. Genomic alterations were detected in 92.2% of patients, with the most commonly mutated genes including TERT promoter (57%), TP53 (47%), CTNNB1 (37%), ARID1A (18%), and TSC2 (14%). In total, 37 (73%) patients underwent paired tumor NGS, and concordance was high for mutations observed in patient-matched plasma samples: TERT (83%), TP53 (94%), CTNNB1 (92%), ARID1A (100%), and TSC2 (71%). In 10 (27%) of 37 tumor-plasma samples, alterations were detected by cfDNA analysis that were not detected in the patient-matched tumors. Potentially actionable mutations were identified in 37% of all cases including oncogenic/likely oncogenic alterations in TSC1/2 (18%), BRCA1/2 (8%), and PIK3CA (8%). Higher average variant allele fraction was associated with elevated alpha-fetoprotein, increased tumor volume, and no previous systemic therapy, but did not correlate with overall survival in treatment-naïve patients.

CONCLUSION

Tumor mutation profiling of cfDNA in HCC represents an alternative to tissue-based genomic profiling, given the high degree of tumor-plasma NGS concordance; however, genotyping of both blood and tumor may be required to detect all clinically actionable genomic alterations.

Combined radiotherapy and immune checkpoint inhibition for the treatment of advanced hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is one of the most common cancers and a leading cause of cancer related death worldwide. Until recently, systemic therapy for advanced HCC, defined as Barcelona Clinic Liver Cancer (BCLC) stage B or C, was limited and ineffective in terms of long-term survival. However, over the past decade, immune check point inhibitors (ICI) combinations have emerged as a potential therapeutic option for patients with nonresectable disease. ICI modulate the tumor microenvironment to prevent progression of the tumor. Radiotherapy is a crucial tool in treating unresectable HCC and may enhance the efficacy of ICI by manipulating the tumor microenvironment and decreasing tumor resistance to certain therapies. We herein review developments in the field of ICI combined with radiotherapy for the treatment of HCC, as well as look at challenges associated with these treatment modalities, and review future directions of combination therapy.

Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy

OBJECTIVES

The accurate prediction of post-hepatectomy early recurrence in patients with hepatocellular carcinoma (HCC) is crucial for decision-making regarding postoperative adjuvant treatment and monitoring. We aimed to explore the feasibility of deep learning (DL) features derived from gadoxetate disodium (Gd-EOB-DTPA) MRI, qualitative features, and clinical variables for predicting early recurrence.

METHODS

In this bicentric study, 285 patients with HCC who underwent Gd-EOB-DTPA MRI before resection were divided into training (n = 195) and validation (n = 90) sets. DL features were extracted from contrast-enhanced MRI images using VGGNet-19. Three feature selection methods and five classification methods were combined for DL signature construction. Subsequently, an mp-MR DL signature fused with multiphase DL signatures of contrast-enhanced images was constructed. Univariate and multivariate logistic regression analyses were used to identify early recurrence risk factors including mp-MR DL signature, microvascular invasion (MVI), and tumor number. A DL nomogram was built by incorporating deep features and significant clinical variables to achieve early recurrence prediction.

RESULTS

MVI (p = 0.039), tumor number (p = 0.001), and mp-MR DL signature (p < 0.001) were independent risk factors for early recurrence. The DL nomogram outperformed the clinical nomogram in the training set (AUC: 0.949 vs. 0.751; p < 0.001) and validation set (AUC: 0.909 vs. 0.715; p = 0.002). Excellent DL nomogram calibration was achieved in both training and validation sets. Decision curve analysis confirmed the clinical usefulness of DL nomogram.

CONCLUSION

The proposed DL nomogram was superior to the clinical nomogram in predicting early recurrence for HCC patients after hepatectomy.

KEY POINTS

• Deep learning signature based on Gd-EOB-DTPA MRI was the predominant independent predictor of early recurrence for hepatocellular carcinoma (HCC) after hepatectomy. • Deep learning nomogram based on clinical factors and Gd-EOB-DTPA MRI features is promising for predicting early recurrence of HCC. • Deep learning nomogram outperformed the conventional clinical nomogram in predicting early recurrence.

Liquid Biopsy in Hepatocellular Carcinoma: The Significance of Circulating Tumor Cells in Diagnosis, Prognosis, and Treatment Monitoring

Hepatocellular carcinoma (HCC) is an aggressive malignancy with poor outcomes when diagnosed at an advanced stage. Current curative treatments are most effective in early-stage HCC, highlighting the importance of early diagnosis and intervention. However, existing diagnostic methods, such as radiological imaging, alpha-fetoprotein (AFP) testing, and biopsy, have limitations that hinder early diagnosis. AFP elevation is absent in a significant portion of tumors, and imaging may have low sensitivity for smaller tumors or in the presence of cirrhosis. Additionally, as our understanding of the molecular pathogenesis of HCC grows, there is an increasing need for molecular information about the tumors. Biopsy, although informative, is invasive and may not always be feasible depending on tumor location. In this context, liquid biopsy technology has emerged as a promising approach for early diagnosis, enabling molecular characterization and genetic profiling of tumors. This technique involves analyzing circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), or tumor-derived exosomes. CTCs are cancer cells shed from the primary tumor or metastatic sites and circulate in the bloodstream. Their presence not only allows for early detection but also provides insights into tumor metastasis and recurrence. By detecting CTCs in peripheral blood, real-time tumor-related information at the DNA, RNA, and protein levels can be obtained. This article provides an overview of CTCs and explores their clinical significance for early detection, prognosis, treatment selection, and monitoring treatment response in HCC, citing relevant literature.

Systemic administration of mesenchymal stem cells loaded with a novel oncolytic adenovirus carrying a bispecific T cell engager against hepatocellular carcinoma

We previously established a hepatocellular carcinoma (HCC) targeting system of conditionally replicative adenovirus (CRAd) delivered by human umbilical cord-derived mesenchymal stem cells (HUMSCs). However, this system needed to be developed further to enhance the antitumor effect and overcome the limitations caused by the alpha-fetoprotein (AFP) heterogeneity of HCC. In this study, a bispecific T cell engager (BiTE) targeting programmed death ligand 1 controlled by the human telomerase reverse transcriptase promoter was armed on the CRAd of the old system. It was demonstrated on orthotopic transplantation model mice that the new system had a better anti-tumor effect with no more damage to extrahepatic organs and less liver injury, and the infiltration and activation of T cells were significantly enhanced in the tumor tissues of the model mice treated with the new system. Importantly, we confirmed that the new system eliminated the AFP-negative cells on AFP heterogeneous tumor models efficiently. Conclusion: Compared with the old system, the new system provided a more effective and safer strategy against HCC.

Prognostic Value of Erythroblastic Leukemia Viral Oncogene Homolog 2 and Neuregulin 4 in Hepatocellular Carcinoma

Although the roles of erythroblastic leukemia viral oncogene homolog 2 (ERBB2), neuregulin 4 (NRG4), and mitogen-inducible gene 6 (MIG6) in epidermal growth factor receptor signaling in hepatocellular carcinoma (HCC) and other malignancies have been previously investigated, the prognostic value of their serum levels in HCC remains undetermined. In the present study, correlations between serum levels and tumor characteristics, overall survival, and tumor recurrence were analyzed. Furthermore, the prognostic potential of the serum levels of these biomarkers was evaluated relative to that of alpha-fetoprotein. Both ERBB2 and NRG4 correlated with the Barcelona Clinic Liver Cancer stage, ERBB2 correlated with the tumor-maximal diameter, and NRG4 correlated with a tumor number. Cox proportional hazards regression analysis revealed that ERBB2 (hazard ratio [HR], 2.719; p = 0.007) was an independent prognostic factor for overall survival. Furthermore, ERBB2 (HR, 2.338; p = 0.002) and NRG4 (HR, 431.763; p = 0.001) were independent prognostic factors for tumor recurrence. The products of ERBB2 and NRG4 had a better area under the curve than alpha-fetoprotein for predicting 6-month, 1-year, 3-year, and 5-year mortality. Therefore, these factors could be used to evaluate prognosis and monitor treatment response in patients with HCC.

Radiomics, a Promising New Discipline: Example of Hepatocellular Carcinoma

Radiomics is a discipline that involves studying medical images through their digital data. Using “artificial intelligence” algorithms, radiomics utilizes quantitative and high-throughput analysis of an image’s textural richness to obtain relevant information for clinicians, from diagnosis assistance to therapeutic guidance. Exploitation of these data could allow for a more detailed characterization of each phenotype, for each patient, making radiomics a new biomarker of interest, highly promising in the era of precision medicine. Moreover, radiomics is non-invasive, cost-effective, and easily reproducible in time. In the field of oncology, it performs an analysis of the entire tumor, which is impossible with a single biopsy but is essential for understanding the tumor’s heterogeneity and is known to be closely related to prognosis. However, current results are sometimes less accurate than expected and often require the addition of non-radiomics data to create a performing model. To highlight the strengths and weaknesses of this new technology, we take the example of hepatocellular carcinoma and show how radiomics could facilitate its diagnosis in difficult cases, predict certain histological features, and estimate treatment response, whether medical or surgical.

Prediction of therapeutic response of advanced hepatocellular carcinoma to combined targeted immunotherapy by MRI

PURPOSE

To assess the value of pre-treatment MRI in predicting treatment response to combined targeted immunotherapy in advanced hepatocellular carcinoma (HCC).

METHODS

Totally 35 HCC participants who underwent pre-treatment contrast-enhanced MRI and received combined tyrosine kinase inhibitor (TKI) and anti-PD-1 antibody treatment were enrolled. Univariable and multivariable logistic regression analyses were carried out for comparing clinical and MRI characteristics between patients with therapeutic response and those without. A predictive model based on MRI data and the corresponding nomogram were developed using data generated by multivariate analysis, and the diagnostic performance was evaluated. A cutoff for the combined index was measured by receiver operating characteristic curve analysis, and progression-free survival (PFS) rates were compared between cases with high and low combined index values.

RESULTS

Fifteen (42.86%) cases achieved overall response during treatment. Multivariable analysis revealed that homogeneous signal (odds ratio [OR] = 13.51, P = 0.010) and no arterial peritumoral enhancement (APE; OR = 10.29, P = 0.024) independently predicted treatment response. The combined model including both significant MRI parameters showed a satisfactory predictive performance with the largest area under the curve of 0.837 (95%CI 0.673-0.939), and both sensitivity and specificity of 80.0%. HCCs with high-combined index had higher PFS rate compared with those showing a low value (P = 0.034).

CONCLUSION

The combination of pre-treatment MRI features of homogeneous signal and no APE could be used for predicting treatment response to combined targeted immunotherapy in advanced HCC.

Genetics of Hepatocellular Carcinoma: From Tumor to Circulating DNA

Hepatocellular carcinoma (HCC) accounts for 90% of primary hepatic malignancies and is one of the major causes of cancer-related death. Over the last 15 years, the molecular landscape of HCC has been deciphered, with the identification of the main driver genes of liver carcinogenesis that belong to six major biological pathways, such as telomere maintenance, Wnt/b-catenin, P53/cell cycle regulation, oxidative stress, epigenetic modifiers, AKT/mTOR and MAP kinase. The combination of genetic and transcriptomic data composed various HCC subclasses strongly related to risk factors, pathological features and prognosis. However, translation into clinical practice is not achieved, mainly because the most frequently mutated genes are undruggable. Moreover, the results derived from the analysis of a single tissue sample may not adequately catch the intra- and intertumor heterogeneity. The analysis of circulating tumor DNA (ctDNA) is broadly developed in other types of cancer for early diagnosis, prognosis and monitoring under systemic treatment in order to identify primary and secondary mechanisms of resistance. The aim of this review is to describe recent data about the HCC molecular landscape and to discuss how ctDNA could be used in the future for HCC detection and management.

Predicting histologic differentiation of solitary hepatocellular carcinoma up to 5 cm on gadoxetate disodium-enhanced MRI

BACKGROUND

To establish a preoperative score based on gadoxetate disodium-enhanced magnetic resonance imaging (EOB-MRI) and clinical indicators for predicting histologic differentiation of solitary HCC up to 5 cm.

METHODS

From July 2015 to January 2022, consecutive patients with surgically proven solitary HCC measuring ≤ 5 cm at preoperative EOB-MRI were retrospectively enrolled. All MR images were independently evaluated by two radiologists who were blinded to all clinical and pathologic information. Univariate and multivariate logistic regression analyses were performed to identify significant clinicoradiological features associated with poorly differentiated (PD) HCC, which were then incorporated into the predictive score. The predictive score was validated in an independent validation set by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.

RESULTS

A total of 182 patients were included, 42 (23%) with PD HCC. According to the multivariate analysis, marked hepatobiliary phase hypointensity (odds ratio [OR], 9.98), LR-M category (OR, 5.60), and serum alpha-fetoprotein (AFP) level > 400 ng/mL (OR, 3.58) were incorporated into the predictive model; the predictive score achieved an AUC of 0.802 and 0.830 on the training and validation sets, respectively. The sensitivity, specificity, and accuracy of the predictive score were 66.7%, 85.7%, and 81.3%, respectively, on the training set and 66.7%, 81.0%, and 77.8%, respectively, on the validation set.

CONCLUSION

The proposed score integrating two EOB-MRI features and AFP level can accurately predict PD HCC in the preoperative setting.

Single-cell resolved ploidy and chromosomal aberrations in nonalcoholic steatohepatitis-(NASH) induced hepatocellular carcinoma and its precursor lesions

Nonalcoholic steatohepatitis (NASH)-induced hepatocellular carcinoma (HCC) and its precursor, nonalcoholic fatty liver disease (NAFLD) are an unmet health issue due to widespread obesity. We assessed copy number changes of genes associated with hepatocarcinogenesis and oxidative pathways at a single-cell level. Eleven patients with NASH-HCC and 11 patients with NAFLD were included. Eight probes were analyzed using multiplex interphase fluorescence in situ hybridization (miFISH), single-cell imaging and phylogenetic tree modelling: Telomerase reverse transcriptase (TERT), C-Myc (MYC), hepatocyte growth factor receptor tyrosine kinase (MET), tumor protein 53 (TP53), cyclin D1 (CCND1), human epidermal growth factor receptor 2 (HER2), the fragile histidine triad gene (FHIT) and FRA16D oxidoreductase (WWOX). Each NASH-HCC tumor had up to 14 distinct clonal signal patterns indicating multiclonality, which correlated with high tumor grade. Changes frequently observed were TP53 losses, 45%; MYC gains, 36%; WWOX losses, 36%; and HER2 gains, 18%. Whole-genome duplications were frequent (82%) with aberrant tetraploid cells evolving from diploid ancestors. Non-tumorous NAFLD/NASH biopsies did not harbor clonal copy number changes. Fine mapping of NASH-HCC using single-cell multiplex FISH shows that branched tumor evolution involves genome duplication and that multiclonality increases with tumor grade. The loss of oxidoreductase WWOX and HER2 gains could be potentially associated with NASH-induced hepatocellular carcinoma.

Multi-region sequencing with spatial information enables accurate heterogeneity estimation and risk stratification in liver cancer

BACKGROUND

Numerous studies have used multi-region sampling approaches to characterize intra-tumor heterogeneity (ITH) in hepatocellular carcinoma (HCC). However, conventional multi-region sampling strategies do not preserve the spatial details of samples, and thus, the potential influences of spatial distribution on patient-wise ITH (represents the overall heterogeneity level of the tumor in a given patient) have long been overlooked. Furthermore, gene-wise transcriptional ITH (represents the expression pattern of genes across different intra-tumor regions) in HCC is also under-explored, highlighting the need for a comprehensive investigation.

METHODS

To address the problem of spatial information loss, we propose a simple and easy-to-implement strategy called spatial localization sampling (SLS). We performed multi-region sampling and sequencing on 14 patients with HCC, collecting a total of 75 tumor samples with spatial information and molecular data. Normalized diversity score and integrated heterogeneity score (IHS) were then developed to measure patient-wise and gene-wise ITH, respectively.

RESULTS

A significant correlation between spatial and molecular heterogeneity was uncovered, implying that spatial distribution of sampling sites did influence ITH estimation in HCC. We demonstrated that the normalized diversity score had the ability to overcome sampling location bias and provide a more accurate estimation of patient-wise ITH. According to this metric, HCC tumors could be divided into two classes (low-ITH and high-ITH tumors) with significant differences in multiple biological properties. Through IHS analysis, we revealed a highly heterogenous immune microenvironment in HCC and identified some low-ITH checkpoint genes with immunotherapeutic potential. We also constructed a low-heterogeneity risk stratification (LHRS) signature based on the IHS results which could accurately predict the survival outcome of patients with HCC on a single tumor biopsy sample.

CONCLUSIONS

This study provides new insights into the complex phenotypes of HCC and may serve as a guide for future studies in this field.

Multiregional single-cell dissection of tumor and immune cells reveals stable lock-and-key features in liver cancer

Intratumor heterogeneity may result from the evolution of tumor cells and their continuous interactions with the tumor microenvironment which collectively drives tumorigenesis. However, an appearance of cellular and molecular heterogeneity creates a challenge to define molecular features linked to tumor malignancy. Here we perform multiregional single-cell RNA sequencing (scRNA-seq) analysis of seven liver cancer patients (four hepatocellular carcinoma, HCC and three intrahepatic cholangiocarcinoma, iCCA). We identify cellular dynamics of malignant cells and their communication networks with tumor-associated immune cells, which are validated using additional scRNA-seq data of 25 HCC and 12 iCCA patients as a stable fingerprint embedded in a malignant ecosystem representing features of tumor aggressiveness. We further validate the top ligand-receptor interaction pairs (i.e., LGALS9-SLC1A5 and SPP1-PTGER4 between tumor cells and macrophages) associated with unique transcriptome in additional 542 HCC patients. Our study unveils stable molecular networks of malignant ecosystems, which may open a path for therapeutic exploration.

CTNNB1 polymorphism (rs121913407) in circulating tumor DNA (ctDNA) in Egyptian hepatocellular carcinoma patients

Background

Hepatocellular carcinoma (HCC) represents the sixth most common cancer worldwide and the fourth in Egypt. Persistent inflammation and specific somatic mutations in driving genes play a major role in the development of HCC. One of these somatic mutations is CTNNB1 mutations with subsequent activation of β-catenin in HCC, associated with a risk of malignant transformation. In this study, we investigate the clinical utility of peripheral blood circulating tumor DNA (ctDNA) CTNNB1 (rs121913407) in HCC patients compared to pathological chronic hepatitis C virus (HCV) patients and healthy controls.

Methods

Our study is a case-control study at the Ain Shams Centre for Organ Transplantation, Ain Shams University Hospitals, enrolling twenty-eight adult HCC patients (twelve early HCC patients and sixteen advanced HCC patients), ten patients with chronic hepatitis C as a disease control group, and ten healthy controls. We collected plasma and stored at −80 °C. We detected mutations in the gene locus CTNNB1 rs121913407 by real-time PCR.

Results

All of our studied cases (early and advanced HCC) in addition to HCV and healthy control groups were CTNNB1 wild (TT) genotype. There was statistical significant difference between early and late cases of HCC as regards AFP and AST.

Conclusions

None of our recruited subjects showed CTNNB1 rs121913407 gene mutation. Further studies on larger number of patients are needed to clarify and confirm the clinical utility of CTNNB1 single-nucleotide polymorphism in the pathogenesis of HCC related to HCV in Egyptian population.

CTNNB1 mutations, TERT polymorphism and CD8+ cell densities in resected hepatocellular carcinoma are associated with longer time to recurrence

Background

Hepatocellular carcinoma (HCC) is a fatal disease characterized by early genetic alterations in telomerase reverse transcriptase promoter (TERTp) and β-catenin (CTNNB1) genes and immune cell activation in the tumor microenvironment. As a novel approach, we wanted to assess patient survival influenced by combined presence of mutations and densities of CD8+ cytotoxic T cells.

Methods

Tissue samples were obtained from 67 HCC patients who had undergone resection. We analysed CD8+ T cells density, TERTp mutations, rs2853669 polymorphism, and CTNNB1 mutations. These variables were evaluated for time to recurrence (TTR) and disease free survival (DFS).

Results

TERTp mutations were found in 75.8% and CTNNB1 mutations in 35.6% of the patients. TERTp mutations were not associated with survival but polymorphism rs2853669 in TERTp was associated with improved TTR and DFS. CTNNB1 mutations were associated with improving TTR. High density of CD8+ T-lymphocytes in tumor center and invasive margin correlated with longer TTR and DFS. Combined genetic and immune factors further improved survival showing higher predictive values. E.g., combining CTNNB1 mutations and high density of CD8+ T-lymphocytes in tumor center yielded HRs of 0.12 (0.03–0.52), p = 0.005 for TTR and 0.25 (0.09–0.74), p = 0.01 for DFS.

Conclusion

The results outline a novel integrative approach for prognostication through combining independent predictive factors from genetic and immune cell profiles. However, larger studies are needed to explore multiple cell types in the tumor microenvironment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09989-0.

Priming of Sorafenib Prior to Radiofrequency Ablation Does Not Increase Treatment Effect in Hepatocellular Carcinoma

BACKGROUND

Preclinical studies have shown that modulation of the tumor microvasculature with anti-angiogenic agents decreases tumor perfusion and may increase the efficacy of radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC). Retrospective studies suggest that sorafenib given prior to RFA promotes an increase in the ablation zone, but prospective randomized data are lacking.

AIMS

We conducted a randomized, double-blind, placebo-controlled phase II trial to evaluate the efficacy of a short-course of sorafenib prior to RFA for HCC tumors sized 3.5-7 cm (NCT00813293).

METHODS

Treatment consisted of sorafenib 400 mg twice daily for 10 days or matching placebo, followed by RFA on day 10. The primary objectives were to assess if priming with sorafenib increased the volume and diameter of the RFA coagulation zone and to evaluate its impact on RFA thermal parameters. Secondary objectives included feasibility, safety and to explore the relationship between tumor blood flow on MRI and RFA effectiveness.

RESULTS

Twenty patients were randomized 1:1. Priming with sorafenib did not increase the size of ablation zone achieved with RFA and did not promote significant changes in thermal parameters, although it significantly decreased blood perfusion to the tumor by 27.9% (p = 0.01) as analyzed by DCE-MRI. No subject discontinued treatment owing to adverse events and no grade 4 toxicity was observed.

CONCLUSION

Priming of sorafenib did not enhance the effect of RFA in intermediate sized HCC. Future studies should investigate whether longer duration of treatment or a different antiangiogenic strategy in the post-procedure setting would be more effective in impairing tumor perfusion and increasing RFA efficacy.

Dietary folate drives methionine metabolism to promote cancer development by stabilizing MAT IIA

Folic acid, served as dietary supplement, is closely linked to one-carbon metabolism and methionine metabolism. Previous clinical evidence indicated that folic acid supplementation displays dual effect on cancer development, promoting or suppressing tumor formation and progression. However, the underlying mechanism remains to be uncovered. Here, we report that high-folate diet significantly promotes cancer development in mice with hepatocellular carcinoma (HCC) induced by DEN/high-fat diet (HFD), simultaneously with increased expression of methionine adenosyltransferase 2A (gene name, MAT2A; protein name, MATIIα), the key enzyme in methionine metabolism, and acceleration of methionine cycle in cancer tissues. In contrast, folate-free diet reduces MATIIα expression and impedes HFD-induced HCC development. Notably, methionine metabolism is dynamically reprogrammed with valosin-containing protein p97/p47 complex-interacting protein (VCIP135) which functions as a deubiquitylating enzyme to bind and stabilize MATIIα in response to folic acid signal. Consistently, upregulation of MATIIα expression is positively correlated with increased VCIP135 protein level in human HCC tissues compared to adjacent tissues. Furthermore, liver-specific knockout of Mat2a remarkably abolishes the advocating effect of folic acid on HFD-induced HCC, demonstrating that the effect of high or free folate-diet on HFD-induced HCC relies on Mat2a. Moreover, folate and multiple intermediate metabolites in one-carbon metabolism are significantly decreased in vivo and in vitro upon Mat2a deletion. Together, folate promotes the integration of methionine and one-carbon metabolism, contributing to HCC development via hijacking MATIIα metabolic pathway. This study provides insight into folate-promoted cancer development, strongly recommending the tailor-made folate supplement guideline for both sub-healthy populations and patients with cancer expressing high level of MATIIα expression.

Preoperative gadoxetic acid-enhanced MRI predicts aggressive pathological features in LI-RADS category 5 hepatocellular carcinoma

AIM

To investigate whether Liver Imaging Reporting and Data System (LI-RADS) imaging features and non-LI-RADS imaging features can predict aggressive pathological features in adult patients with hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

From February 2018 to September 2021, 236 adult patients with cirrhosis or hepatitis B virus infection in which liver cancer was suspected underwent MRI within 1 month before surgery. Significant MRI findings and alpha-fetoprotein (AFP) level predicted high-grade HCC and microvascular invasion (MVI) by univariate and multivariate logistic regression models.

RESULTS

The study included 112 patients with histopathologically confirmed liver cancer (≤5 cm), 35 of whom (31.3%) high-grade HCC and 42 of 112 (37.5%) patients had MVI. Mosaic architecture (odds ratio [OR] = 6.031; 95% confidence interval [CI]: 1.366, 26.626; p=0.018), coronal enhancement (OR=5.878; 95% CI: 1.471, 23.489; p=0.012), and intratumoural vessels (OR=5.278; 95% CI: 1.325, 21.020; p=0.018) were significant independent predictors of high-grade HCC. A non-smooth tumour margin (OR=10.237; 95% CI: 1.547, 67.760; p=0.016), coronal enhancement (OR=3.800; 95% CI: 1.152, 12.531; p=0.028), and peritumoural hypointensity on the hepatobiliary phase (HBP; OR=10.322; 95% CI: 2.733, 38.986; p=0.001) were significant independent predictors of MVI.

CONCLUSION

In high-risk adult patients with single LR-5 HCC (≤5 cm), mosaic architecture, coronal enhancement, and intratumoural vessels are independent predictors of high-grade HCC. Non-smooth tumour margin, coronal enhancement, and peritumoural hypointensity on HBP independently predicted MVI.

MRI-based Nomogram Predicts the Risk of Progression of Unresectable Hepatocellular Carcinoma After Combined Lenvatinib and anti-PD-1 Antibody Therapy

RATIONALE AND OBJECTIVES

Combined immune and anti-angiogenic treatment has shown promising results for unresectable hepatocellular carcinoma (HCC), but with a high risk of early progression. In this study, we aimed to investigate whether pre-treatment magnetic resonance imaging (MRI) features and MRI-based nomogram could predict the risk of disease progression of unresectable HCC after first-line lenvatinib/anti-PD-1 antibody therapy.

MATERIALS AND METHODS

Thirty-seven HCC participants with qualified pre-treatment contrast-enhanced MRI were enrolled. All patients received combined lenvatinib and anti-PD-1 antibody treatment. Progression free survival rate was analyzed using the Kaplan-Meier method. Potential clinical-radiological risk factors for progression were analyzed using the log-rank tests and Cox regression model. The performance of MRI-based nomogram was evaluated based on C-index, calibration, and decision curve analyses.

RESULTS

The 6-month and 12-month cumulative progression free survival rates were 59.5% (95% confidence interval (CI), 43.6%-75.4%) and 48.0% (95% CI, 31.7%-64.3%). On multivariate analysis, no or incomplete tumor capsule (hazard ratio (HR) = 15.215 [95% CI 2.707-85.529], p = 0.002), heterogeneous signal on T2-weighted imaging (HR = 28.179 [95% CI 2.437-325.838]; p = 0.008) and arterial contrast-to-noise ratio ≤95.45 (HR = 5.113 [95% CI 1.538-17.00]; p = 0.008) were independent risk factors for disease progression. Satisfactory predictive performance of the nomogram incorporating the three independent imaging features was obtained with a C-index value of 0.880 (95% CI 0.824-0.937), and the combined nomogram had more favorable clinical prediction performance than any single feature.

CONCLUSION

MRI features can be considered effective predictors of disease progression for unresectable HCC with first-line lenvatinib plus anti-PD-1 antibody therapy, and the combined MRI-based nomogram achieved a superior prognostic model, which may help to identify appropriate candidates for the therapy.

Systems analysis identifies endothelin 1 axis blockade for enhancing the anti-tumor effect of multikinase inhibitor

Multikinase inhibitors, such as sorafenib, are used for the treatment of advanced carcinomas but the response shows limited efficacy or varies a lot with patients. Here we adopted the systems approach combined with high-throughput data analysis to discover key mechanism embedded in the drug response. When analyzing the transcriptomic data from the Cancer Cell Line Encyclopedia (CCLE) database, endothelin 1 (EDN1) was enriched in cancer cells with low responsiveness to sorafenib. We found that the level of EDN1 is higher in the tissue and blood of hepatocellular carcinoma (HCC) patients showing poor response to sorafenib. In vitro experiment showed that EDN1 not only induces activation of angiogenic-promoting pathways in HCC cells but also stimulates proliferation and migration. Moreover, EDN1 is related with poor responsiveness to sorafenib by mitigating unfolded protein response (UPR), which was validated in both transcriptomic data analysis and in silico simulation. Finally, we found that endothelin receptor B (EDNRB) antagonists can enhance the efficacy of sorafenib in both HCC cells and xenograft mouse models. Our findings provide that EDN1 is a novel diagnostic marker for sorafenib responsiveness in HCC and a basis for testing macitentan, which is currently used for pulmonary artery hypertension, in combination with sorafenib in advanced HCC patients.

Radiomics for the detection of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, accounting for about 90% of liver cancer cases. It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality. Moreover, recurrence of HCC is common. Microvascular invasion (MVI) is a major factor associated with recurrence in postoperative HCC. It is difficult to evaluate MVI using traditional imaging modalities. Currently, MVI is assessed primarily through pathological and immunohistochemical analyses of postoperative tissue samples. Needle biopsy is the primary method used to confirm MVI diagnosis before surgery. As the puncture specimens represent just a small part of the tumor, and given the heterogeneity of HCC, biopsy samples may yield false-negative results. Radiomics, an emerging, powerful, and non-invasive tool based on various imaging modalities, such as computed tomography, magnetic resonance imaging, ultrasound, and positron emission tomography, can predict the HCC-MVI status preoperatively by delineating the tumor and/or the regions at a certain distance from the surface of the tumor to extract the image features. Although positive results have been reported for radiomics, its drawbacks have limited its clinical translation. This article reviews the application of radiomics, based on various imaging modalities, in preoperative evaluation of HCC-MVI and explores future research directions that facilitate its clinical translation.

Comparative subcellular localization of NRF2 and KEAP1 during the hepatocellular carcinoma development in vivo

The activation of Nuclear Factor, Erythroid 2 Like 2 - Kelch Like ECH Associated Protein 1 (NRF2-KEAP1) signaling pathway plays a critical dual role by either protecting or promoting the carcinogenesis process. However, its activation or nuclear translocation during hepatocellular carcinoma (HCC) progression has not been addressed yet. This study characterizes the subcellular localization of both NRF2 and KEAP1 during diethylnitrosamine-induced hepatocarcinogenesis in the rat. NRF2-KEAP1 pathway was continuously activated along with the increased expression of its target genes, namely Nqo1, Hmox1, Gclc, and Ptgr1. Similarly, the nuclear translocation of NRF2, MAF, and KEAP1 increased in HCC cells from weeks 12 to 22 during HCC progression. Likewise, colocalization of NRF2 with KEAP1 was higher in the cell nuclei of HCC neoplastic nodules than in surrounding cells. Moreover, immunofluorescence analyses revealed that the interaction of KEAP1 with filamentous Actin was disrupted in HCC cells. This disruption may be contributing to the release and nuclear translocation of NRF2 since the cortical actin cytoskeleton serves as anchoring of KEAP1. In conclusion, this evidence indicates that NRF2 is progressively activated and promotes the progression of experimental HCC.

Hepatocellular Carcinoma: The Role of MicroRNAs

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths worldwide. HCC is diagnosed in its advanced stage when limited treatment options are available. Substantial morphologic, genetic and epigenetic heterogeneity has been reported in HCC, which poses a challenge for the development of a targeted therapy. In this review, we discuss the role and involvement of several microRNAs (miRs) in the heterogeneity and metastasis of hepatocellular carcinoma with a special emphasis on their possible role as a diagnostic and prognostic tool in the risk prediction, early detection, and treatment of hepatocellular carcinoma.

Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma

PURPOSE

How to discriminate different risks of recurrent nasopharyngeal carcinoma (rNPC) patients and guide individual treatment has become of great importance. This study aimed to explore the associations between deep learning signatures and biological functions as well as survival in (rNPC) patients.

METHODS

A total of 420 rNPC patients with PET/CT imaging and follow-up of overall survival (OS) were retrospectively enrolled. All patients were randomly divided into a training set (n = 269) and test set (n = 151) with a 6:4 ratio. We constructed multi-modality deep learning signatures from PET and CT images with a light-weighted deep convolutional neural network EfficienetNet-lite0 and survival loss DeepSurvLoss. An integrated nomogram was constructed incorporating clinical factors and deep learning signatures from PET/CT. Clinical nomogram and single-modality deep learning nomograms were also built for comparison. Furthermore, the association between biological functions and survival risks generated from an integrated nomogram was analyzed by RNA sequencing (RNA-seq).

RESULTS

The C-index of the integrated nomogram incorporating age, rT-stage, and deep learning PET/CT signature was 0.741 (95% CI: 0.688-0.794) in the training set and 0.732 (95% CI: 0.679-0.785) in the test set. The nomogram stratified patients into two groups with high risk and low risk in both the training set and test set with hazard ratios (HR) of 4.56 (95% CI: 2.80-7.42, p < 0.001) and 4.05 (95% CI: 2.21-7.43, p < 0.001), respectively. The C-index of the integrated nomogram was significantly higher than the clinical nomogram and single-modality nomograms. When stratified by sex, N-stage, or EBV DNA, risk prediction of our integrated nomogram was valid in all patient subgroups. Further subgroup analysis showed that patients with a low-risk could benefit from surgery and re-irradiation, while there was no difference in survival rates between patients treated by chemotherapy in the high-risk and low-risk groups. RNA sequencing (RNA-seq) of data further explored the mechanism of high- and low-risk patients from the genetic and molecular level.

CONCLUSION

Our study demonstrated that PET/CT-based deep learning signatures showed satisfactory prognostic predictive performance in rNPC patients. The nomogram incorporating deep learning signatures successfully divided patients into different risks and had great potential to guide individual treatment: patients with a low-risk were supposed to be treated with surgery and re-irradiation, while for high-risk patients, the application of palliative chemotherapy may be sufficient.

Predictive value of collagen in cancer

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.

Circulating Cell-Free DNA Captures the Intratumor Heterogeneity in Multinodular Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, with more than 40% of patients initially diagnosed with multinodular HCCs. Although circulating cell-free DNA (cfDNA) has been shown to effectively detect somatic mutations, little is known about its utility to capture intratumor heterogeneity in patients with multinodular HCC undergoing systemic treatment.

Correlation Between Contrast-Enhanced Ultrasound and Immune Response of Distant Hepatocellular Carcinoma After Radiofrequency Ablation in a Murine Model

OBJECTIVES

To investigate the relationships between contrast-enhanced ultrasound (CEUS) and the immune status of a distant tumor after radiofrequency ablation (RFA) in a mouse model of hepatocellular carcinoma (HCC).

METHODS

Twenty-four mice with two liver tumors were randomized into two groups. RFA was performed on the left tumor in the RFA group. Growth of the right tumors in both groups was monitored after RFA. According to tumor growth, two time points at which tumor growth was halted and restored were selected for study. Then, another 24 mice were randomized into RFA and non-RFA groups. The CEUS parameters, apoptosis, CD8+ T cell, and vasculogenic mimicry (VM) of the right tumors were analyzed on the two aforementioned time points in each group.

RESULTS

Days 3 and 6 were selected as the time points of tumor retardation and progressive growth, respectively. The different immune status of the distant tumors at the two time points after RFA was confirmed by CD8+ T cell and apoptosis (both P < 0.001). Peak intensity, time to peak, area wash-in, and area wash-out of the CEUS parameters increased significantly in the day-6 RFA group versus the day-3 RFA group (P < .001, P = .017, P = .005, P = .002, respectively). VM of the day-6 RFA group was higher than that of the day-3 RFA group (P = .003).

CONCLUSIONS

CEUS maybe a good method to follow the immune response after RFA in an advanced HCC mouse model.

Identification of Prognostic Genes in Hepatocellular Carcinoma

Background

Previous studies have demonstrated the important role of tumor stem cells (TSCs) in the development of hepatocellular carcinoma (HCC); however, TSC-related genetic markers have not been investigated.

Aim

The aim of the present study was to identify stem cell-related signature genes to predict the prognosis of HCC, using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.

Methods

In total, 423 liver HCC tissue samples, including 373 tumor and 50 adjacent normal tissue samples from TCGA, and 115 primary tumor and 52 adjacent non-tumor tissue samples from the GEO GSE76427 database, were used in the present study. The non-negative matrix factorization (NMF) algorithm, t-distributed stochastic neighbor embedding (t-SNE) algorithm and Cox regression analysis were combined for model construction and validation.

Results

Overall, six clusters were identified using the NMF and t-SNE algorithms with 470 stem cell-related genes. The results demonstrated that patients in cluster 5 had the worst prognosis. For multivariate Cox survival analysis, 15 genes with optimal lambda values were chosen and eight genes were incorporated into the final regression model using the optimal Akaike information criterion value. Validation of the risk model using the aforementioned eight signature genes demonstrated the models strong reliability and stable predictive performance.

Conclusion

The results of the present study indicated that the eight-gene (Hes family BHLH transcription factor 5, KIT ligand, methyltransferase-like 3, proteasome 26S subunit non-ATPase 1, Ras-related protein Rab-10, treacle ribosome biogenesis factor 1, YTH N6-methyladenosine RNA binding protein 2 and Zinc Finger CCCH-Type Containing 13) signature constructed by the model may be reliable in predicting the prognosis of patients with HCC.

The role of BCL9 genetic variation as a biomarker for hepatitis C-related hepatocellular carcinoma in Egyptian patients

BACKGROUND

Hepatocellular carcinoma (HCC) is considered one of the most common cancers related to mortality around the world, and susceptibility is related with genetic, lifestyle, and environmental factors. Copy number variation of the Bcell CLL/lymphoma 9 (BCL9) gene is a type of structural variation which can influence gene expression and can be related with specific phenotypes and diseases and has a role in hepatocarcinogenesis. Our aims were to assess the copy number variation (CNV) in the BCL9 gene and explore its role in HCV-related HCC Egyptian patients. A total of 50 HCV-related HCC patients were enrolled in the study (including 25 early HCC and 25 late HCC cases); the copy number of the BCL9 gene was detected using quantitative polymerase reaction.

RESULTS

There was a highly statistically significant difference between the two groups (early and late HCC patients) in gender, bilharziasis, performance status, child score class, child grade, focal lesion size, portal vein, and ascites. CNV was detected and represented by the gain in the BCL9 gene in 14% of patients, and all of them were males. Also, it was noticed that the ratio of gain in BCL9 copy number in late individuals was about 1.5 times than that in early HCC individuals. Moreover, our results showed that the distribution of performance status > 1, average and enlarged liver, focal lesion size, thrombosed portal vein, and AFP was higher in patients with BCL9 copy number gain.

CONCLUSION

We detected about 14% gain in BCL9 copy number in Egyptian HCC patients. But the variation in copy number of the BCL9 gene did not affect HCC development in our patients' cohort.

Predictive Role for Serum Aldo-Keto Reductase Family1 Member B10 for Early Detection of Hepatocellular Carcinoma in Egyptian Patients

Background: Most patients with hepatocellular carcinoma (HCC) are diagnosed at late stages despite of improvement screening programs and lack of effective diagnostic methods for cases with preclinical HCC leads to a low rate of early detection. Aldo-keto reductase family 1 member B10 (AKR1B10) is associated with several types of cancer. However, to our knowledge, the diagnostic significance of AKR1B10 measurement in early stage of HCC has poorly understood. Aim To evaluate the diagnostic performance of serum AKR1B10 in hepatitis C virus (HCV)-related liver disorders and its unique role in diagnosing HCC. Methods Serum AKR1B10 was detected by sandwich ELISA in 30 patients with HCV-related HCC, 30 patients with HCV related liver cirrhosis, and 20 healthy controls. Both Serum AKR1B10 and α-fetoprotein (AFP) levels were analyzed, evaluated and compared. Results Serum AKR1B10 was significantly elevated in patients with HCC compared with. The sensitivity (86.7.0%) and specificity (70%) for HCC diagnosis with AKR1B10 were high at a cutoff value of 0.945 ng/ml, while alpha fetoprotein had sensitivity 67% and specificity 88% in early detection of HCC among studied groups at cutoff point higher than 17.9. ng/ml. Furthermore, concurrent measurement of Alpha fetoprotein and AKR1B10 had increased sensitivity to 97.6% and specificity 100% in early detection of HCC among studied groups at cutoff point higher than ≥150 ng/ml. Furthermore, concurrent measurement of serum AKR1B10 and AFP significantly increased sensitivity and negative predictive value for HCC diagnosis. Conclusions we concluded in the current study that AKR1B10 has a unique role as a biomarker for early-stage HCV-related HCC. Compared with AFP alone, a combination of serum AKR1B10 and AFP had an increased the diagnostic performance in patients with HCC.

Morphological heterogeneity in beta-catenin-mutated hepatocellular carcinomas: implications for tumor molecular classification

Beta-catenin (CTNNB1) is commonly mutated in hepatocellular carcinoma (HCC). CTNNB1-mutated HCC has important clinical correlates, such as being immune cold and less likely to respond to immune checkpoint inhibitor therapies. It remains unclear, however, if they are a morphologically homogenous group of tumors. To better understand the association between the morphology, CTNNB1 mutations, and other molecular features, a detailed study of 338 The Cancer Genome Atlas cases was performed. A characteristic histological morphology was strongly associated with CTNNB1 mutations but was present in only 58% of CTNNB1-mutated HCCs. Tumors with APC mutations tended to have the classic morphology; those with AXIN mutations did not. Pseudoglands are a key feature of the classic morphology, and they were associated with CTNNB1 mutations, male gender, specific CTNNB1 mutation site, and lack of TP53 mutations. Differential gene expression analysis stratified by the presence/absence of pseudoglands identified 60 differentially expressed genes (FDR <5%); clustering according to these differentially expressed genes revealed three groups of tumors, one with pseudoglands and a strong association with genes regulated by Wnt signaling; within this group, TP53 mutations were associated with a loss of the typical morphology of CTNNB1-mutated HCCs. When stratified by gender, further differential gene expression showed Wnt-regulated genes were associated with pseudoglands in men but not women. These findings indicate HCC with CTNNB1 mutations are morphologically heterogeneous, with gene penetrance for morphology dependent in part on gender, specific CTNNB1 mutations, and co-occurring TP53 mutations. This heterogeneity has important implications for the classification of HCC.

Liquid biopsy to identify biomarkers for immunotherapy in hepatocellular carcinoma

The past years have witnessed the vigorous development of immunotherapy, mainly immune checkpoint inhibitors (ICIs) targeting the programmed cell death-1 (PD-1) protein and its ligand, PD-L1, and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4). Indeed, ICIs have largely revolutionized the management and improved the prognosis of patients with intermediate and advanced hepatocellular carcinoma (HCC). However, biomarker-based stratification of HCC patients for optimal response to ICI treatment is still of unmet need and again, there exists the necessity to dynamically monitor treatment effect in real-time manner. The role of conventional biomarkers in immunotherapy surveillance is largely limited by spatial and temporal tumor heterogeneity whereas liquid biopsy seems to be promising to circumvent tumor heterogeneity to identify candidate patients who may response to immunotherapy, to dynamically monitor treatment effect and to unveil resistance mechanism. Herein, we provide a thorough review about the potential utility of liquid biopsy in immunotherapy for HCC and discuss its future perspectives.

Fidarestat induces glycolysis of NK cells through decreasing AKR1B10 expression to inhibit hepatocellular carcinoma

The aldose reductase inhibitor Fidarestat has been noted to have efficacy in treating a variety of tumors. To define its role in hepatocellular carcinoma (HCC), we induced a HCC xenograft model in mice, which were treated with different doses of Fidarestat. The amounts of natural killer (NK) cells and related inflammatory factors were detected in the serum of the mice. Fidarestat inhibited HCC tumor growth and lung metastasis in vivo and increased NK cell number as well as levels of NK cell-related inflammatory factors in mouse serum. NK cells were then co-cultured with the HCC cell line in vitro to detect effects on HCC cell progression after Fidarestat administration. The glycolysis activity of the NK cells was evaluated by extracellular acidification rate, while aldo-keto reductase family 1 member B10 (AKR1B10) expression was detected by western blot analysis. Administration of Fidarestat downregulated the expression of AKR1B10 in NK cells and promoted NK cell glycolysis to enhance their killing activity against HCC cells. However, depletion of NK cells or upregulation of AKR1B10 attenuated the anticancer activity of Fidarestat. Taken together, Fidarestat downregulated AKR1B10 expression in NK cells to promote NK cell glycolysis, thereby alleviating HCC progression.

Prediction of early recurrence and response to adjuvant Sorafenib for hepatocellular carcinoma after resection

Background

Early recurrence of hepatocellular carcinoma (HCC) is a major obstacle to improving the prognosis, and no widely accepted adjuvant therapy guideline for patients post-liver resection is available. Currently, all available methods and biomarkers are insufficient to accurately predict post-operation HCC patients’ risk of early recurrence and their response to adjuvant therapy.

Methods

In this study, we downloaded four gene expression datasets (GSE14520, GSE54236, GSE87630, and GSE109211) from the Gene Expression Omnibus database and identified 34 common differentially expressed genes associated with HCC dysregulation and response to adjuvant sorafenib. Then, we constructed a novel 11-messenger RNA predictive model by using ROC curves analysis, univariate Cox regression analysis, and LASSO Cox regression analysis. Furthermore, we validated the predictive values of the risk model in GSE14520 and TCGA-LIHC cohorts by using Kaplan–Meier survival analysis, multivariable Cox regression analysis, and decision curve analysis, respectively.

Results

The risk score model could identify patients with a high risk of HCC recurrence at the early stage and could predict the response of patients to adjuvant sorafenib. Patients with a high risk score had a worse recurrence rate in training cohorts (2-year: p < 0.0001, hazard ratio (HR): 4.658, confidence interval 95% CI [2.895–7.495]; 5-year: p < 0.0001, HR: 3.251, 95% CI [2.155–4.904]) and external validation cohorts (2-year: p < 0.001, HR: 3.65, 95% CI [2.001–6.658]; 5-year: p < 0.001, HR: 3.156, 95% CI [1.78–5.596]). The AUC values of the risk score model for predicting tumor early recurrence were 0.746 and 0.618, and that of the risk score model for predicting the response to adjuvant sorafenib were 0.722 and 0.708 in the different cohort, respectively. Multivariable Cox regression analysis and decision curve analysis also showed that the risk score model was superior to and independent of other clinicopathologic characteristics. Moreover, the risk score model had excellent abilities to predict the overall survival and HCC recurrence of patients with the same tumor stage category.

Conclusions

Our risk model is a reliable and superior predictive tool. With this model, we could optimize the risk stratification based on early tumor recurrence and could evaluate the response of patients to adjuvant sorafenib after liver resection.

The transcriptome of early GGT/KRT19-positive hepatocellular carcinoma reveals a downregulated gene expression profile associated with fatty acid metabolism

Hepatocellular carcinoma expressing hepatobiliary progenitor markers, is considered of poor prognosis. By using a hepatocarcinogenesis model, laser capture microdissection, and RNA-Sequencing analysis, we identified an expression profile in GGT/KRT19-positive experimental tumors; 438 differentially expressed genes were found in early and late nodules along with increased collagen deposition. Dysregulated genes were involved in Fatty Acid Metabolism, RXR function, and Hepatic Stellate Cells Activation. Downregulation of Slc27a5, Acsl1, and Cyp2e1, demonstrated that Retinoid X Receptor α (RXRα) function is compromised in GGT/KRT19-positive nodules. Since RXRα controls NRF2 pathway activation, we determined the expression of NRF2 targeted genes; Akr1b8, Akr7a3, Gstp1, Abcc3, Ptgr1, and Txnrd1 were upregulated, indicating NRF2 pathway activation. A comparative analysis in human HCC showed that SLC27A5, ACSL1, CYP2E1, and RXRα gene expression is mutually exclusive with KRT19 gene expression. Our results indicate that the downregulation of Slc27a5, Acsl1, Rxrα, and Cyp2e1 genes is an early event within GGT/KRT19-positive HCC.

Non-alcoholic steatohepatitis and risk of hepatocellular carcinoma

ABSTRACT

The emergence of non-alcoholic fatty liver disease (NAFLD) as the leading chronic liver disease worldwide raises some concerns. In particular, NAFLD is closely tied to sedentary lifestyle habits and associated with other metabolic diseases, such as obesity and diabetes. At the end of the disease spectrum, non-alcoholic steatohepatitis (NASH) may progress to cirrhosis and hepatocellular carcinoma (HCC), representing a serious health problem to modern society. Recently, an increasing number of HCC cases originating from this progressive disease spectrum have been identified, with different levels of severity and complications. Updating the current guidelines by placing a bigger focus on this emerging cause and highlighting some of its unique features is necessary. Since, the drivers of the disease are complex and multifactorial, in order to improve future outcomes, having a better understanding of NASH progression into HCC may be helpful. The risks that can promote disease progression and currently available management strategies employed to monitor and treat NASH-related HCC make up the bulk of this review.

Intratumor Heterogeneity in Hepatocellular Carcinoma: Challenges and Opportunities

Hepatocellular carcinoma (HCC) represents a leading cause of cancer-related death, but it remains difficult to treat. Intratumor genetic and phenotypic heterogeneity are inherent properties of breast, skin, lung, prostate, and brain tumors, and intratumor heterogeneity (ITH) helps define prognosis and therapeutic response in these cancers. Several recent studies estimate that ITH is inherent to HCC and attribute the clinical intractability of HCC to this heterogeneity. In this review, we examine the evidence for genomic, phenotypic, and tumor microenvironment ITH in HCC, with a focus on two of the top molecular drivers of HCC: β-catenin (CTNNB1) and Telomerase reverse transcriptase (TERT). We discuss the influence of ITH on HCC diagnosis, prognosis, and therapy, while highlighting the gaps in knowledge and possible future directions.

Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in hepatocellular carcinoma: the PLANET study

Intra-tumor heterogeneity (ITH) is a key challenge in cancer treatment, but previous studies have focused mainly on the genomic alterations without exploring phenotypic (transcriptomic and immune) heterogeneity. Using one of the largest prospective surgical cohorts for hepatocellular carcinoma (HCC) with multi-region sampling, we sequenced whole genomes and paired transcriptomes from 67 HCC patients (331 samples). We found that while genomic ITH was rather constant across stages, phenotypic ITH had a very different trajectory and quickly diversified in stage II patients. Most strikingly, 30% of patients were found to contain more than one transcriptomic subtype within a single tumor. Such phenotypic ITH was found to be much more informative in predicting patient survival than genomic ITH and explains the poor efficacy of single-target systemic therapies in HCC. Taken together, we not only revealed an unprecedentedly dynamic landscape of phenotypic heterogeneity in HCC, but also highlighted the importance of studying phenotypic evolution across cancer types.

Aberrant Upregulation of Indoleamine 2,3-Dioxygenase 1 Promotes Proliferation and Metastasis of Hepatocellular Carcinoma Cells via Coordinated Activation of AhR and β-Catenin Signaling

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related death worldwide. Chronic liver inflammation due to hepatitis virus infection and other major effectors is a major risk factor of HCC. Indoleamine 2,3-dioxygenase 1 (IDO1), a heme enzyme highly expressed upon stimulation with proinflammatory cytokines such as interferon-γ (IFN-γ), is activated to modulate the tumor microenvironment and potentially crucial in the development of certain cancer types. Earlier studies have majorly reported an immunomodulatory function of IDO1. However, the specific role of IDO1 in cancer cells, particularly HCC, remains to be clarified. Analysis of The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) dataset in the current study revealed a significant correlation between IDO1 expression and HCC. We further established inducible IDO1-expressing cell models by coupling lentivirus-mediated knockdown and IFN-γ induction of IDO1 in normal and HCC cells. In functional assays, proliferation and motility-related functions of HCC cells were compromised upon suppression of IDO1, which may partially be rescued by its enzymatic product, kynurenine (KYN), while normal hepatocytes were not affected. Aryl hydrocarbon receptor (AhR), a reported endogenous KYN receptor, is suggested to participate in tumorigenesis. In mechanistic studies, IDO1 activation promoted both AhR and β-catenin activity and nuclear translocation. Immunofluorescence staining and co-immunoprecipitation assays further disclosed interactions between AhR and β-catenin. In addition, we identified a Src-PTEN-PI3K/Akt-GSK-3β axis involved in β-catenin stabilization and activation following IDO1-mediated AhR activation. IDO1-induced AhR and β-catenin modulated the expression of proliferation- and EMT-related genes to facilitate growth and metastasis of HCC cells. Our collective findings provide a mechanistic basis for the design of more efficacious IDO1-targeted therapy for HCC.