Variable Intra-Tumor Genomic Heterogeneity of Multiple Lesions in Patients With Hepatocellular Carcinoma

Multifunctional and stimuli-responsive liposomes in hepatocellular carcinoma diagnosis and therapy

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer, mainly occurring in Asian countries with an increased incidence rate globally. Currently, several kinds of therapies have been deployed for HCC therapy including surgical resection, chemotherapy, radiotherapy and immunotherapy. However, this tumor is still incurable, requiring novel strategies for its treatment. The nanomedicine has provided the new insights regarding the treatment of cancer that liposomes as lipid-based nanoparticles, have been widely applied in cancer therapy due to their biocompaitiblity, high drug loading and ease of synthesis and modification. The current review evaluates the application of liposomes for the HCC therapy. The drugs and genes lack targeting ability into tumor tissues and cells. Therefore, loading drugs or genes on liposomes can increase their accumulation in tumor site for HCC suppression. Moreover, the stimuli-responsive liposomes including pH-, redox- and light-sensitive liposomes are able to deliver drug into tumor microenvironment to improve therapeutic index. Since a number of receptors upregulate on HCC cells, the functionalization of liposomes with lactoferrin and peptides can promote the targeting ability towards HCC cells. Moreover, phototherapy can be induced by liposomes through loading phtoosensitizers to stimulate photothermal- and photodynamic-driven ablation of HCC cells. Overall, the findings are in line with the fact that liposomes are promising nanocarriers for the treatment of HCC.

Integrative molecular and spatial analysis reveals evolutionary dynamics and tumor-immune interplay of in situ and invasive acral melanoma

In acral melanoma (AM), progression from in situ (AMis) to invasive AM (iAM) leads to significantly reduced survival. However, evolutionary dynamics during this process remain elusive. Here, we report integrative molecular and spatial characterization of 147 AMs using genomics, bulk and single-cell transcriptomics, and spatial transcriptomics and proteomics. Vertical invasion from AMis to iAM displays an early and monoclonal seeding pattern. The subsequent regional expansion of iAM exhibits two distinct patterns, clonal expansion and subclonal diversification. Notably, molecular subtyping reveals an aggressive iAM subset featured with subclonal diversification, increased epithelial-mesenchymal transition (EMT), and spatial enrichment of APOE+/CD163+ macrophages. In vitro and ex vivo experiments further demonstrate that APOE+CD163+ macrophages promote tumor EMT via IGF1-IGF1R interaction. Adnexal involvement can predict AMis with higher invasive potential whereas APOE and CD163 serve as prognostic biomarkers for iAM. Altogether, our results provide implications for the early detection and treatment of AM.

Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation

BACKGROUND

Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15-20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with recurrent HCC to identify differentially expressed genes (DEGs), the involved pathways, biological functions, and potential gene signatures of recurrent HCC post-transplant using deep machine learning (ML) methodology.

MATERIALS AND METHODS

We analyzed the transcriptomic profiles of primary and recurrent tumor samples from 7 pairs of patients who underwent LT. Following differential gene expression analysis, we performed pathway enrichment, gene ontology (GO) analyses and protein-protein interactions (PPIs) with top 10 hub gene networks. We also predicted the landscape of infiltrating immune cells using Cibersortx. We next develop pathway and GO term-based deep learning models leveraging primary tissue gene expression data from The Cancer Genome Atlas (TCGA) to identify gene signatures in recurrent HCC.

RESULTS

The PI3K/Akt signaling pathway and cytokine-mediated signaling pathway were particularly activated in HCC recurrence. The recurrent tumors exhibited upregulation of an immune-escape related gene, CD274, in the top 10 hub gene analysis. Significantly higher infiltration of monocytes and lower M1 macrophages were found in recurrent HCC tumors. Our deep learning approach identified a 20-gene signature in recurrent HCC. Amongst the 20 genes, through multiple analysis, IL6 was found to be significantly associated with HCC recurrence.

CONCLUSION

Our deep learning approach identified PI3K/Akt signaling as potentially regulating cytokine-mediated functions and the expression of immune escape genes, leading to alterations in the pattern of immune cell infiltration. In conclusion, IL6 was identified to play an important role in HCC recurrence.

A multimodal atlas of hepatocellular carcinoma reveals convergent evolutionary paths and 'bad apple' effect on clinical trajectory

BACKGROUND & AIMS

Hepatocellular Carcinoma (HCC) is a highly fatal cancer characterized by high intra-tumor heterogeneity (ITH). A panoramic understanding of its tumor evolution, in relation to its clinical trajectory, may provide novel prognostic and treatment strategies.

METHODS

Through the Asia-Pacific Hepatocellular Carcinoma (AHCC) trials group (NCT03267641), we recruited one of the largest prospective cohorts of HCC with over 600 whole genome and transcriptome samples from 123 treatment-naïve patients.

RESULTS

Using a multi-region sampling approach, we revealed seven convergent genetic evolutionary paths governed by the early driver mutations, late copy number variations and viral integrations, which stratify patient clinical trajectories after surgical resection. Furthermore, such evolutionary paths shaped the molecular profiles, leading to distinct transcriptomic subtypes. Most significantly, although we found the coexistence of multiple transcriptomic subtypes within certain tumors, patient prognosis was best predicted by the most aggressive cell fraction of the tumor, rather than by overall degree of transcriptomic ITH level - a phenomenon we termed the 'bad apple' effect. Finally, we found that characteristics throughout early and late tumor evolution provide significant and complementary prognostic power in predicting patient survival.

CONCLUSIONS

Taken together, our study generated a comprehensive landscape of evolutionary history for HCC and provided a rich multi-omics resource for understanding tumor heterogeneity and clinical trajectories.

CLINICAL TRIAL NUMBER

NCT03267641 (Observational cohort) IMPACT AND IMPLICATIONS: This prospective study, utilizing comprehensive multi-sector, multi-omics sequencing and clinical data from surgically resected HCC, reveals critical insights into the role of tumor evolution and intra-tumor heterogeneity (ITH) in determining the prognosis of Hepatocellular Carcinoma (HCC). These findings are invaluable for oncology researchers and clinicians, as they underscore the influence of distinct evolutionary paths and the 'bad apple' effect, where the most aggressive tumor fraction dictates disease progression. These insights not only enhance prognostic accuracy post-surgical resection but also pave the way for developing personalized therapies tailored to specific tumor evolutionary and transcriptomic profiles. The co-existence of multiple sub-types within the same tumor prompts a re-appraisal of the utilities of depending on single samples to represent the entire tumor and suggests the need for clinical molecular imaging. This research thus marks a significant step forward in the clinical understanding and management of HCC, underscoring the importance of integrating tumor evolutionary dynamics and multi-omics biomarkers into therapeutic decision-making.

Pharmacogenomic profiling of intra-tumor heterogeneity using a large organoid biobank of liver cancer

Inter- and intra-tumor heterogeneity is a major hurdle in primary liver cancer (PLC) precision therapy. Here, we establish a PLC biobank, consisting of 399 tumor organoids derived from 144 patients, which recapitulates histopathology and genomic landscape of parental tumors, and is reliable for drug sensitivity screening, as evidenced by both in vivo models and patient response. Integrative analysis dissects PLC heterogeneity, regarding genomic/transcriptomic characteristics and sensitivity to seven clinically relevant drugs, as well as clinical associations. Pharmacogenomic analysis identifies and validates multi-gene expression signatures predicting drug response for better patient stratification. Furthermore, we reveal c-Jun as a major mediator of lenvatinib resistance through JNK and β-catenin signaling. A compound (PKUF-01) comprising moieties of lenvatinib and veratramine (c-Jun inhibitor) is synthesized and screened, exhibiting a marked synergistic effect. Together, our study characterizes the landscape of PLC heterogeneity, develops predictive biomarker panels, and identifies a lenvatinib-resistant mechanism for combination therapy.

Heterogeneity of hepatocellular carcinoma: from mechanisms to clinical implications

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

Deep whole-genome analysis of 494 hepatocellular carcinomas

Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China1-3. However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited4-8, with current analyses of HCC mainly from non-HBV-enriched populations9,10. Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS_H8. Pentanucleotide context analysis and experimental validation confirmed that SBS_H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications.

Mechanism-guided fine-tuned microbiome potentiates anti-tumor immunity in HCC

Microbiome, including bacteria, fungi, and viruses, plays a crucial role in shaping distal and proximal anti-tumor immunity. Mounting evidence showed that commensal microbiome critically modulates immunophenotyping of hepatocellular carcinoma (HCC), a leading cause of cancer-related death. However, their role in anti-tumor surveillance of HCC is still poorly understood. Herein, we spotlighted growing interests in how the microbiome influences the progression and immunotherapeutic responses of HCC via changing local tumor microenvironment (TME) upon translocating to the sites of HCC through different "cell-type niches". Moreover, we summarized not only the associations but also the deep insight into the mechanisms of how the extrinsic microbiomes interplay with hosts to shape immune surveillance and regulate TME and immunotherapeutic responses. Collectively, we provided a rationale for a mechanism-guided fine-tuned microbiome to be neoadjuvant immunotherapy in the near future.

Molecular evolution in different subtypes of multifocal hepatocellular carcinoma

BACKGROUND

Multifocal hepatocellular carcinoma (MF-HCC) accounts for > 40% of HCCs, exhibiting a poor prognosis than single primary HCCs. Characterizing molecular features including dynamic changes of mutational signature along with clonal evolution, intrahepatic metastatic timing, and genetic footprint in the preneoplastic stage underlying different subtypes of MF-HCC are important for understanding their molecular evolution and developing a precision management strategy.

METHODS

We conducted whole-exome sequencing in 74 tumor samples from spatially distinct regions in 35 resected lesions and adjacent noncancerous tissues from 11 patients, 15 histologically confirmed preneoplastic lesions, and six samples from peripheral blood mononuclear cells. A previously published MF-HCC cohort (n = 9) was included as an independent validation dataset. We combined well-established approaches to investigate tumor heterogeneity, intrahepatic metastatic timing, and molecular footprints in different subtypes of MF-HCCs.

RESULTS

We classified MF-HCCs patients into three subtypes, including intrahepatic metastasis, multicentric occurrence, and mixed intrahepatic metastasis and multicentric occurrence. The dynamic changes in mutational signatures between tumor subclonal expansions demonstrated varied etiologies (e.g., aristolochic acid exposure) underlying the clonal progression in different MF-HCC subtypes. Furthermore, the clonal evolution in intrahepatic metastasis exhibited an early metastatic seeding at 10-4-0.01 cm3 in primary tumor volume (below the limits of clinical detection), further validated in an independent cohort. In addition, mutational footprints in the preneoplastic lesions for multicentric occurrence patients revealed common preneoplastic arising clones, evidently being ancestors of different tumor lesions.

CONCLUSION

Our study comprehensively characterized the varied tumor clonal evolutionary history underlying different subtypes of MF-HCC and provided important implications for optimizing personalized clinical management for MF-HCC.

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast-enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.

Lineage tracing for multiple lung cancer by spatiotemporal heterogeneity using a multi-omics analysis method integrating genomic, transcriptomic, and immune-related features

Introduction

The distinction between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) holds clinical significance in staging, therapeutic intervention, and prognosis assessment for multiple lung cancer. Lineage tracing by clinicopathologic features alone remains a clinical challenge; thus, we aimed to develop a multi-omics analysis method delineating spatiotemporal heterogeneity based on tumor genomic profiling.

Methods

Between 2012 and 2022, 11 specimens were collected from two patients diagnosed with multiple lung cancer (LU1 and LU2) with synchronous/metachronous tumors. A novel multi-omics analysis method based on whole-exome sequencing, transcriptome sequencing (RNA-Seq), and tumor neoantigen prediction was developed to define the lineage. Traditional clinicopathologic reviews and an imaging-based algorithm were performed to verify the results.

Results

Seven tissue biopsies were collected from LU1. The multi-omics analysis method demonstrated that three synchronous tumors observed in 2018 (LU1B/C/D) had strong molecular heterogeneity, various RNA expression and immune microenvironment characteristics, and unique neoantigens. These results suggested that LU1B, LU1C, and LU1D were MPLC, consistent with traditional lineage tracing approaches. The high mutational landscape similarity score (75.1%), similar RNA expression features, and considerable shared neoantigens (n = 241) revealed the IPM relationship between LU1F and LU1G which were two samples detected simultaneously in 2021. Although the multi-omics analysis method aligned with the imaging-based algorithm, pathology and clinicopathologic approaches suggested MPLC owing to different histological types of LU1F/G. Moreover, controversial lineage or misclassification of LU2's synchronous/metachronous samples (LU2B/D and LU2C/E) traced by traditional approaches might be corrected by the multi-omics analysis method. Spatiotemporal heterogeneity profiled by the multi-omics analysis method suggested that LU2D possibly had the same lineage as LU2B (similarity score, 12.9%; shared neoantigens, n = 71); gefitinib treatment and EGFR, TP53, and RB1 mutations suggested the possibility that LU2E might result from histology transformation of LU2C despite the lack of LU2C biopsy and its histology. By contrast, histological interpretation was indeterminate for LU2D, and LU2E was defined as a primary or progression lesion of LU2C by histological, clinicopathologic, or imaging-based approaches.

Conclusion

This novel multi-omics analysis method improves the accuracy of lineage tracing by tracking the spatiotemporal heterogeneity of serial samples. Further validation is required for its clinical application in accurate diagnosis, disease management, and improving prognosis.

Potential Predictive Biomarkers of Systemic Drug Therapy for Hepatocellular Carcinoma: Anticipated Usefulness in Clinical Practice

In the systemic drug treatment of hepatocellular carcinoma, only the tyrosine kinase inhibitor (TKI) sorafenib was available for a period. This was followed by the development of regorafenib as a second-line treatment after sorafenib, and then lenvatinib, a new TKI, proved non-inferiority to sorafenib and became available as a first-line treatment. Subsequently, cabozantinib, another TKI, was introduced as a second-line treatment, along with ramucirumab, the only drug proven to be predictive of therapeutic efficacy when AFP levels are >400 ng/mL. It is an anti-VEGF receptor antibody. More recently, immune checkpoint inhibitors have become the mainstay of systemic therapy and can now be used as a first-line standard treatment for HCC. However, the objective response rate for these drugs is currently only 30% to 40%, and there is a high incidence of side effects. Additionally, there are no practical biomarkers to predict their therapeutic effects. Therefore, this review provides an overview of extensive research conducted on potential HCC biomarkers from blood, tissue, or imaging information that can be used in practice to predict the therapeutic efficacy of systemic therapy before its initiation.

Analysis of genomic and immune intratumor heterogeneity in linitis plastica via multiregional exome and T-cell receptor sequencing

The molecular landscape and the intratumor heterogeneity (ITH) architecture of gastric linitis plastica (LP) are poorly understood. We performed whole-exome sequencing (WES) and T-cell receptor (TCR) sequencing on 40 tumor regions from four LP patients. The landscape and ITH at the genomic and immunological levels in LP tumors were compared with multiple cancers that have previously been reported. The lymphocyte infiltration was further assessed by immunohistochemistry (IHC) in LP tumors. In total, we identified 6339 non-silent mutations from multi-samples, with a median tumor mutation burden (TMB) of 3.30 mutations per Mb, comparable to gastric adenocarcinoma from the Cancer Genome Atlas (TCGA) cohort (P = 0.53). An extremely high level of genomic ITH was observed, with only 12.42%, 5.37%, 5.35%, and 30.67% of mutations detectable across 10 regions within the same tumors of each patient, respectively. TCR sequencing revealed that TCR clonality was substantially lower in LP than in multi-cancers. IHC using antibodies against CD4, CD8, and PD-L1 demonstrated scant T-cell infiltration in the four LP tumors. Furthermore, profound TCR ITH was observed in all LP tumors, with no T-cell clones shared across tumor regions in any of the patients, while over 94% of T-cell clones were restricted to individual tumor regions. The Morisita overlap index (MOI) ranged from 0.21 to 0.66 among multi-regions within the same tumors, significantly lower than that of lung cancer (P = 0.002). Our results show that LP harbored extremely high genomic and TCR ITH and suppressed T-cell infiltration, suggesting a potential contribution to the frequent recurrence and poor therapeutic response of this adenocarcinoma.

Single-cell Deconvolution of a Specific Malignant Cell Population as a Poor Prognostic Biomarker in Low-risk Clear Cell Renal Cell Carcinoma Patients

BACKGROUND

Intratumor heterogeneity (ITH) is a key feature in clear cell renal cell carcinomas (ccRCCs) that impacts outcomes such as aggressiveness, response to treatments, or recurrence. In particular, it may explain tumor relapse after surgery in clinically low-risk patients who did not benefit from adjuvant therapy. Recently, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to unravel expression ITH (eITH) and might enable better assessment of clinical outcomes in ccRCC.

OBJECTIVE

To explore eITH in ccRCC with a focus on malignant cells (MCs) and assess its relevance to improve prognosis for low-risk patients.

DESIGN, SETTING, AND PARTICIPANTS

We performed scRNA-seq on tumor samples from five untreated ccRCC patients ranging from pT1a to pT3b. Data were complemented with a published dataset composed of pairs of matched normal and ccRCC samples.

INTERVENTION

Radical or partial nephrectomy on untreated ccRCC patients.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Viability and cell type proportions were determined by flow cytometry. Following scRNA-seq, a functional analysis was performed and tumor progression trajectories were inferred. A deconvolution approach was applied on an external cohort, and Kaplan-Meier survival curves were estimated with respect to the prevalence of malignant clusters.

RESULTS AND LIMITATIONS

We analyzed 54 812 cells and identified 35 cell subpopulations. The eITH analysis revealed that each tumor contained various degrees of clonal diversity. The transcriptomic signatures of MCs in one particularly heterogeneous sample were used to design a deconvolution-based strategy that allowed the risk stratification of 310 low-risk ccRCC patients.

CONCLUSIONS

We described eITH in ccRCCs, and used this information to establish significant cell population-based prognostic signatures and better discriminate ccRCC patients. This approach has the potential to improve the stratification of clinically low-risk patients and their therapeutic management.

PATIENT SUMMARY

We sequenced the RNA content of individual cell subpopulations composed of clear cell renal cell carcinomas and identified specific malignant cells the genetic information of which can be used to predict tumor progression.

Differentiation of acute and chronic vertebral compression fractures using conventional CT based on deep transfer learning features and hand-crafted radiomics features

BACKGROUND

We evaluated the diagnostic efficacy of deep learning radiomics (DLR) and hand-crafted radiomics (HCR) features in differentiating acute and chronic vertebral compression fractures (VCFs).

METHODS

A total of 365 patients with VCFs were retrospectively analysed based on their computed tomography (CT) scan data. All patients completed MRI examination within 2 weeks. There were 315 acute VCFs and 205 chronic VCFs. Deep transfer learning (DTL) features and HCR features were extracted from CT images of patients with VCFs using DLR and traditional radiomics, respectively, and feature fusion was performed to establish the least absolute shrinkage and selection operator. The MRI display of vertebral bone marrow oedema was used as the gold standard for acute VCF, and the model performance was evaluated using the receiver operating characteristic (ROC).To separately evaluate the effectiveness of DLR, traditional radiomics and feature fusion in the differential diagnosis of acute and chronic VCFs, we constructed a nomogram based on the clinical baseline data to visualize the classification evaluation. The predictive power of each model was compared using the Delong test, and the clinical value of the nomogram was evaluated using decision curve analysis (DCA).

RESULTS

Fifty DTL features were obtained from DLR, 41 HCR features were obtained from traditional radiomics, and 77 features fusion were obtained after feature screening and fusion of the two. The area under the curve (AUC) of the DLR model in the training cohort and test cohort were 0.992 (95% confidence interval (CI), 0.983-0.999) and 0.871 (95% CI, 0.805-0.938), respectively. While the AUCs of the conventional radiomics model in the training cohort and test cohort were 0.973 (95% CI, 0.955-0.990) and 0.854 (95% CI, 0.773-0.934), respectively. The AUCs of the features fusion model in the training cohort and test cohort were 0.997 (95% CI, 0.994-0.999) and 0.915 (95% CI, 0.855-0.974), respectively. The AUCs of nomogram constructed by the features fusion in combination with clinical baseline data were 0.998 (95% CI, 0.996-0.999) and 0.946 (95% CI, 0.906-0.987) in the training cohort and test cohort, respectively. The Delong test showed that the differences between the features fusion model and the nomogram in the training cohort and the test cohort were not statistically significant (P values were 0.794 and 0.668, respectively), and the differences in the other prediction models in the training cohort and the test cohort were statistically significant (P < 0.05). DCA showed that the nomogram had high clinical value.

CONCLUSION

The features fusion model can be used for the differential diagnosis of acute and chronic VCFs, and its differential diagnosis ability is improved when compared with that when either radiomics is used alone. At the same time, the nomogram has a high predictive value for acute and chronic VCFs and can be a potential decision-making tool to assist clinicians, especially when a patient is unable to undergo spinal MRI examination.

Genomic instability drives tumorigenesis and metastasis and its implications for cancer therapy

Genetic instability can be caused by external factors and may also be associated with intracellular damage. At the same time, there is a large body of research investigating the mechanisms by which genetic instability occurs and demonstrating the relationship between genomic stability and tumors. Nowadays, tumorigenesis development is one of the hottest research areas. It is a vital factor affecting tumor treatment. Mechanisms of genomic stability and tumorigenesis development are relatively complex. Researchers have been working on these aspects of research. To explore the research progress of genomic stability and tumorigenesis, development, and treatment, the authors searched PubMed with the keywords "genome instability" "chromosome instability" "DNA damage" "tumor spread" and "cancer treatment". This extracts the information relevant to this study. Results: This review introduces genomic stability, drivers of tumor development, tumor cell characteristics, tumor metastasis, and tumor treatment. Among them, immunotherapy is more important in tumor treatment, which can effectively inhibit tumor metastasis and kill tumor cells. Breakthroughs in tumorigenesis development studies and discoveries in tumor metastasis will provide new therapeutic techniques. New tumor treatment methods can effectively prevent tumor metastasis and improve the cure rate of tumors.

A new and rare type of hepatocellular carcinoma: Survival and gene analysis of portal vein tumour thrombus-type hepatocellular carcinoma

BACKGROUND

Portal vein tumour thrombus (PVTT) in patients with hepatocellular carcinoma (HCC) is known as a major complication associated with poor survival. We clinically defined a new and rare type of HCC, PVTT-type HCC (PVTT-HCC), in a small group of HCC patients with HCC presenting only as PVTT without a demonstrable parenchyma tumour. The clinicopathological and biological features of PVTT-HCC are not clear.

METHODS

The data for patients who had PVTT-HCC with histologically confirmed HCC from January 2004 to December 2012 at the Eastern Hepatobiliary Surgery Hospital were retrospectively analysed. The survival outcomes of patients with PVTT-HCC were compared with those of HCC patients with PVTT (HCC-PVTT). Propensity score matching (PSM) analysis was performed to match patients at a ratio of 1:3. Then, we performed RNA-Seq analysis of liver samples from PVTT-HCC and HCC-PVTT patients to identify and compare differentially expressed genes and biological pathways between the two groups.

RESULTS

We observed and collected 10 rare cases of PVTT-HCC and performed a prospective cohort study to compare overall survival (OS) between PVTT-HCC and HCC-PVTT. PVTT invaded the main portal vein in 10 PVTT-HCC patients. Univariate and multivariate analyses demonstrated that ChildPugh (A/B), different treatments (LR/non-LR), and different groups were independent risk factors for OS. The median OS was 10.3 months (95 % CI = 6.7-13.8) in the HCC-PVTT group and 7.5 months (95 % CI = 2.8-12.1) in the PVTT-HCC group (P = 0.042). From RNA-Seq, 1630 differentially expressed genes were obtained, of which 731 were upregulated and 899 downregulated in PVTT-HCC compared with HCC-PVTT.

CONCLUSIONS

The survival outcomes of patients with PVTT-HCC were worse than those of patients with HCC-PVTT. RNA-Seq demonstrated differential gene expression between PVTT-HCC and HCC-PVTT, indicating that the former may have distinguishing biological characteristics and be a new and rare type of HCC.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

Understanding the Immunoenvironment of Primary Liver Cancer: A Histopathology Perspective

One of the most common cancers worldwide, primary liver cancer remains a major cause of cancer-related mortality. Hepatocellular carcinoma and cholangiocarcinoma represent the majority of primary liver cancer cases. Despite advances in the development of novel anti-cancer therapies that exploit targets within the immune system, survival rates from liver cancer remain poor. Furthermore, responses to immunotherapies, such as immune checkpoint inhibitors, have revealed limited and variable responses amongst patients with hepatocellular carcinoma, although combination immunotherapies have shown recent breakthroughs in clinical trials. This has shifted the focus towards improving our understanding of the underlying immune and molecular characteristics of liver tumours that may influence their response to immune-modulating treatments. In this review, we outline the complex interactions that occur in the tumour microenvironment of hepatocellular carcinoma and cholangiocarcinoma, respectively, from a histopathological perspective. We explore the potential role of a classification system based on immune-specific characteristics within each cancer type, the importance of understanding inter- and intra-tumoural heterogeneity and consider the future role of histopathology and novel technologies within this field.

Chemokine clouding and liver cancer heterogeneity: Does it impact clinical outcomes?

Tumor heterogeneity is a predominant feature of hepatocellular carcinoma (HCC) that plays a crucial role in chemoresistance and limits the efficacy of available chemo/immunotherapy regimens. Thus, a better understanding regarding the molecular determinants of tumor heterogeneity will help in developing newer strategies for effective HCC management. Chemokines, a sub-family of cytokines are one of the key molecular determinants of tumor heterogeneity in HCC and are involved in cell survival, growth, migration, and angiogenesis. Herein, we provide a panoramic insight into the role of chemokines in HCC heterogeneity at genetic, epigenetic, metabolic, immune cell composition, and tumor microenvironment levels and its impact on clinical outcomes. Interestingly, our in-silico analysis data showed that expression of chemokine receptors impacts infiltration of various immune cell populations into the liver tumor and leads to heterogeneity. Thus, it is evident that aberrant chemokines clouding impacts HCC tumor heterogeneity and understanding this phenomenon in depth could be harnessed for the development of personalized medicine strategies in future.

Clinical value of identifying genes that inhibit hepatocellular carcinomas

INTRODUCTION

Primary liver cancer is a major health problem being the sixth most frequent cancer in the world and the fourth most frequent cause of cancer-related death in the world. The most common histological type of liver cancer is hepatocellular carcinoma (HCC, 75-80%).

AREAS COVERED

Based on primary literature, this review provides an updated analysis of studies of genetic characterization of HCC at the level of gene mutation profiling, copy number alterations and gene expression, with definition of molecular subgroups and identification of some molecular biomarkers and therapeutic targets.

EXPERT OPINION

A detailed and comprehensive study of the genetic abnormalities characterizing different HCC subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of these tumors may provide a fundamental contribution to improve the survival of a subset of HCC patients. Immunotherapy represents a new fundamental strategy for the treatment of HCC.

Factors of Early Recurrence After Resection for Intrahepatic Cholangiocarcinoma

BACKGROUND

Two-thirds of patients undergoing liver resection for intrahepatic cholangiocarcinoma experience recurrence after surgery. Our aim was to identify factors associated with early recurrence after resection for intrahepatic cholangiocarcinoma.

METHODS

Patients with intrahepatic cholangiocarcinoma undergoing curative intent resection (complete resection and lymphadenectomy) were included in two centers between 2005 and 2021 and were divided into three groups: early recurrence (< 12 months after resection), delayed recurrence (> 12 months), and no recurrence. Patients experiencing early (< 90 days) postoperative mortality were excluded.

RESULTS

Among 120 included patients, 44 (36.7%) experienced early recurrence, 24 (20.0%) experienced delayed recurrence, and 52 (43.3%) did not experience recurrence after a median follow-up of 59 months (IQR: 26-113). The median recurrence-free survival was 16 months (95% CI: 9.6-22.4). Median overall survival was 55 months (95% CI: 45.7-64.3), while it was 25 months for patients with early recurrence (p < 0.001). Patients with early recurrence had significantly larger tumors (59.1% of tumors > 70 mm in early vs. 58.3% in delayed vs. 26.9% in no recurrence group, p = 0.002), multiple lesions (65.9% vs. 29.2% vs. 11.5%, p < 0.001), and positive lymph nodes (N +) (38.6% vs. 37.5% vs. 11.5%, p = 0.005). In multivariable analysis, presence of multiple lesions (OR: 9.324; 95% CI: 3.051-28.489; p < 0.001) and positive lymph nodes (OR: 3.307. 95% CI: 1.001-11.011. p = 0.05) were associated with early recurrence.

CONCLUSION

Early recurrence after curative resection of intrahepatic cholangiocarcinoma is frequent and is associated with the presence of multiple lesions and positive lymph nodes, raising the question of surgery's futility in this context.

Personalized treatment for hepatocellular carcinoma: Current status and future perspectives

Systemic treatment for hepatocellular carcinoma (HCC) has been advancing rapidly over the last decade. More novel agents, including both targeted agents and immune checkpoint inhibitors, are available for physicians to use sequentially or concurrently for patients with advanced HCC. Despite more options, only a proportion of patients benefit from each regimen. Therefore, clinicians are facing challenges on how to choose the right regimen for the right patient with HCC, which raises the importance of personalized treatment approach. To advance personalized treatment for HCC, one approach relies on the acquisition of biomarker data from clinical trials to evaluate clinical parameters or genotypes in association with outcomes of selected drugs. This approach has led to finding of high baseline alpha-fetoprotein levels in association with benefits of ramucirumab. Cumulative findings from multiple clinical trials and translational studies also suggest that selected etiology and/or genotype of HCC could predict resistance to immune checkpoint inhibitors. The second approach is to decipher the tumor heterogeneity of HCC with an aim to identify clinically relevant patterns to guide clinical decisions. Tumor heterogeneity could exist within a single tumor (intra-tumoral heterogeneity), among different tumors in the same patient (inter-tumoral heterogeneity) or between primary and recurrent tumors (temporal tumor heterogeneity). The analyses of tumor heterogeneity have also been powered by coverage of tumor immune environment and incorporation of circulating tumor nucleic acid technology. Emerging publications have been reported above tumor heterogeneity exist in HCC, which is potentially clinically impactful.

Mutational signatures and processes in hepatobiliary cancers

The evolutionary history of hepatobiliary cancers is embedded in their genomes. By analysing their catalogue of somatic mutations and the DNA sequence context in which they occur, it is possible to infer the mechanisms underpinning tumorigenesis. These mutational signatures reflect the exogenous and endogenous origins of genetic damage as well as the capacity of hepatobiliary cells to repair and replicate DNA. Genomic analysis of thousands of patients with hepatobiliary cancers has highlighted the diversity of mutagenic processes active in these malignancies, highlighting a prominent source of the inter-cancer-type, inter-patient, intertumour and intratumoural heterogeneity that is observed clinically. However, a substantial proportion of mutational signatures detected in hepatocellular carcinoma and biliary tract cancer remain of unknown cause, emphasizing the important contribution of processes yet to be identified. Exploiting mutational signatures to retrospectively understand hepatobiliary carcinogenesis could advance preventative management of these aggressive tumours as well as potentially predict treatment response and guide the development of therapies targeting tumour evolution.

Hepatitis B Virus-Associated Hepatocellular Carcinoma

Hepatitis B virus (HBV) is DNA-based virus, member of the Hepadnaviridae family, which can cause liver disease and increased risk of hepatocellular carcinoma (HCC) in infected individuals, replicating within the hepatocytes and interacting with several cellular proteins. Chronic hepatitis B can progressively lead to liver cirrhosis, which is an independent risk factor for HCC. Complications as liver decompensation or HCC impact the survival of HBV patients and concurrent HDV infection worsens the disease. The available data provide evidence that HBV infection is associated with the risk of developing HCC with or without an underlying liver cirrhosis, due to various direct and indirect mechanisms promoting hepatocarcinogenesis. The molecular profile of HBV-HCC is extensively and continuously under study, and it is the result of altered molecular pathways, which modify the microenvironment and lead to DNA damage. HBV produces the protein HBx, which has a central role in the oncogenetic process. Furthermore, the molecular profile of HBV-HCC was recently discerned from that of HDV-HCC, despite the obligatory dependence of HDV on HBV. Proper management of the underlying HBV-related liver disease is fundamental, including HCC surveillance, viral suppression, and application of adequate predictive models. When HBV-HCC occurs, liver function and HCC characteristics guide the physician among treatment strategies but always considering the viral etiology in the treatment choice.

Molecular pathogenesis and systemic therapies for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains one of the most prevalent and deadliest cancers. The poor outcome associated with HCC is dramatically changing due to the advent of effective systemic therapies. Here we discuss the molecular pathogenesis of HCC, molecular classes and determinants of heterogeneity. In addition, effective single-agent and combination systemic therapies involving immunotherapies as standard of care are analyzed. Finally, we propose a flowchart of sequential therapies, explore mechanisms of resistance and address the need for predictive biomarkers.

Innate and Adaptive Immunopathogeneses in Viral Hepatitis; Crucial Determinants of Hepatocellular Carcinoma

Viral hepatitis B (HBV) and hepatitis C (HCV) infections remain the most common risk factors for the development of hepatocellular carcinoma (HCC), and their heterogeneous distribution influences the global prevalence of this common type of liver cancer. Typical hepatitis infection elicits various immune responses within the liver microenvironment, and viral persistence induces chronic liver inflammation and carcinogenesis. HBV is directly mutagenic but can also cause low-grade liver inflammation characterized by episodes of intermittent high-grade liver inflammation, liver fibrosis, and cirrhosis, which can progress to decompensated liver disease and HCC. Equally, the absence of key innate and adaptive immune responses in chronic HCV infection dampens viral eradication and induces an exhausted and immunosuppressive liver niche that favors HCC development and progression. The objectives of this review are to (i) discuss the epidemiological pattern of HBV and HCV infections, (ii) understand the host immune response to acute and chronic viral hepatitis, and (iii) explore the link between this diseased immune environment and the development and progression of HCC in preclinical models and HCC patients.

Downregulation of a mitochondrial micropeptide, MPM, promotes hepatoma metastasis by enhancing mitochondrial complex I activity

We and others have shown that MPM (micropeptide in mitochondria) regulates myogenic differentiation and muscle development. However, the roles of MPM in cancer development remain unknown. Here we revealed that MPM was downregulated significantly in human hepatocellular carcinoma (HCC) tissues and its decrease was associated with increased metastasis potential and HCC recurrence. Gain- and loss-of-function investigations disclosed that in vitro migration/invasion and in vivo liver/lung metastasis of hepatoma cells were repressed by restoring MPM expression and increased by silencing MPM. Mechanism investigations revealed that MPM interacted with NDUFA7. Mitochondrial complex I activity was inhibited by overexpressing MPM and enhanced by siMPM, and this effect of siMPM was attenuated by knocking down NDUFA7. The NAD⁺/NADH ratio, which was regulated by complex I, was reduced by MPM but increased by siMPM. Treatment with the NAD⁺ precursor nicotinamide abrogated the inhibitory effect of MPM on hepatoma cell migration. Further investigations showed that miR-17-5p bound to MPM and inhibited MPM expression. miR-17-5p upregulation was associated with MPM downregulation in HCC tissues. These findings indicate that a decrease in MPM expression may promote hepatoma metastasis by increasing mitochondrial complex I activity and the NAD⁺/NADH ratio.

Gene expression signature as a surrogate marker of microvascular invasion on routine hepatocellular carcinoma biopsies

BACKGROUND & AIMS

Microvascular invasion (MVI), a major risk factor for tumor recurrence after surgery in hepatocellular carcinoma (HCC), is only detectable by microscopic examination of the surgical specimen. We aimed to define a transcriptomic signature associated with MVI in HCC than can be applied to formalin-fixed paraffin-embedded (FFPE) biopsies for use in clinical practice.

METHODS

To identify a gene expression signature related to MVI by using NanoString technology, we selected a set of 200 genes according to the literature and RNA-sequencing data obtained from a cohort of 150 frozen HCC samples previously published. We used 178 FFPE-archived HCC samples, including 109 surgical samples for the training set and 69 paired pre-operative biopsies for the validation set. In 14 cases of the training set, a paired biopsy was available and was also analyzed.

RESULTS

We identified a 6-gene signature (ROS1, UGT2B7, FAS, ANGPTL7, GMNN, MKI67) strongly associated with MVI in the training set of FFPE surgical HCC samples, with 82% accuracy (sensitivity 82%, specificity 81%, AUC 0.82). The NanoString gene expression was highly correlated in 14 paired surgical/biopsy HCC samples (mean R: 0.97). In the validation set of 69 FFPE HCC biopsies, the 6-gene NanoString signature predicted MVI with 74% accuracy (sensitivity 73%, specificity 76%, AUC 0.74). Moreover, on multivariate analysis, the MVI signature was associated with overall survival in both sets (hazard ratio 2.29; 95% CI 1.03-5.07; p = 0.041).

CONCLUSION

We defined a 6-gene signature that can accurately predict MVI in FFPE HCC biopsy samples, which is also associated with overall survival, although its survival impact must be confirmed by extensive study with further clinical data.

LAY SUMMARY

Microvascular invasion, a major risk factor for tumor recurrence after surgery in hepatocellular carcinoma, is only detectable by microscopic examination of a surgical specimen. In this study, we defined a relevant surrogate signature of microvascular invasion in hepatocellular carcinoma that may be applied in clinical practice with routine tumor biopsy and integrated into the therapeutic strategy.

Liver-specific LINC01146, a promising prognostic indicator, inhibits the malignant phenotype of hepatocellular carcinoma cells both in vitro and in vivo

Background

Long non-coding RNAs (lncRNAs) are involved in the development of hepatocellular carcinoma (HCC). We aimed to investigate the function of LINC01146 in HCC.

Methods

The expression of LINC01146 in HCC tissues was explored via The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and was verified using quantitative real-time polymerase chain reaction (qRT–PCR) in our HCC cohort. Kaplan–Meier analysis was used to assess the relationship between LINC01146 and the prognosis of HCC patients. Cell Counting Kit 8, colony formation assays, Transwell assays, flow cytometric assays, and tumour formation models in nude mice were conducted to reveal the effects of LINC01146 on HCC cells both in vitro and in vivo. Bioinformatic methods were used to explore the possible potential pathways of LINC01146 in HCC.

Results

LINC01146 was significantly decreased in HCC tissues compared with adjacent normal tissues and was found to be related to the clinical presentations of malignancy and the poor prognosis of HCC patients. Overexpression of LINC01146 inhibited the proliferation, migration, and invasion of HCC cells in vitro, while promoting their apoptosis. In contrast, downregulation of LINC01146 exerted the opposite effects on HCC cells in vitro. In addition, overexpression of LINC01146 significantly inhibited tumour growth, while downregulation of LINC01146 promoted tumour growth in vivo. Furthermore, the coexpressed genes of LINC01146 were mainly involved in the “metabolic pathway” and “complement and coagulation cascade pathway”.

Conclusion

LINC01146 expression was found to be decreased in HCC tissues and associated with the prognosis of HCC patients. It may serve as a cancer suppressor and prognostic biomarker in HCC.

Genetic Landscape of Multistep Hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Although several targeted therapy agents are available for advanced HCC, their antitumor efficacy remains limited. As the complex genetic landscape of HCC would compromise the antitumor efficacy of targeted therapy, a deeper understanding of the genetic landscape of hepatocarcinogenesis is necessary. Recent comprehensive genetic analyses have revealed the driver genes of HCC, which accumulate during the multistage process of hepatocarcinogenesis, facilitating HCC genetic heterogeneity. In addition, as early genetic changes may represent key therapeutic targets, the genetic landscapes of early HCC and precancerous liver tissues have been characterized in recent years, in parallel with the advancement of next-generation sequencing analysis. In this review article, we first summarize the landscape of the liver cancer genome and its intratumor heterogeneity. We then introduce recent insight on early genetic alterations in hepatocarcinogenesis, especially those in early HCC and noncancerous liver tissues. Finally, we summarize the multistep accumulation of genetic aberrations throughout cancer progression and discuss the future perspective towards the clinical application of this genetic information.

High-Mobility Group AT-Hook 1 Served as a Prognosis Biomarker and Associated with Immune Infiltrate in Hepatocellular Carcinoma

BACKGROUND

The protein high-mobility group AT-hook 1 (HMGA1) has been demonstrated that modulated cellular proliferation, invasion, and apoptosis with a poor prognosis in miscellaneous carcinomas. However, the mechanism of circumstantial carcinogenesis and association with the immune microenvironment of HMGA1 in hepatocellular carcinoma (HCC) had not been extensively explored.

METHODS

The gene expression, clinicopathological correlation, and prognosis analysis were performed in the data obtained from TCGA. The results were further validated by ICGC and GEO database and external validation cohort from Guangxi. The HMGA1 protein expression was further examined in the HPA database. Biological function analyses were conducted by GSEA, STRING database, and Coexpedia online tool. Using TIMER and CIBERSORT method, the relationship between immune infiltrate and HMGA1 was investigated.

RESULTS

In HCC, HMGA1 had much higher transcriptional and proteomic expression than in corresponding paraneoplastic tissue. Patients with high HMGA1 expression had a poor prognosis and unpromising clinicopathological features. High HMGA1 expression was closely related to the cell cycle, tumorigenesis, substance metabolism, and immune processes by regulating complex signaling pathways. Notably, HMGA1 may be associated with TP53 mutational carcinogenesis. Moreover, increased HMGA1 expression may lead to an increase in immune infiltration and a decrease in tumor purity in HCC. CIBERSORT analysis elucidated that the amount of B cell naive, B cell memory, T cells gamma delta, macrophages M2, and mast cell resting decreased when HMGA1 expression was high, whereas T cells follicular helper, macrophages M0, and Dendritic cells resting increased.

CONCLUSION

In conclusions, HMGA1 is a potent prognostic biomarker and a sign of immune infiltration in HCC, which may be a potential immunotherapy target for HCC.

Single-Cell DNA Sequencing Reveals Punctuated and Gradual Clonal Evolution in Hepatocellular Carcinoma

BACKGROUND & AIMS

Copy number alterations (CNAs), elicited by genome instability, are a major source of intratumor heterogeneity. How CNAs evolve in hepatocellular carcinoma (HCC) remains unknown.

METHODS

We performed single-cell DNA sequencing (scDNA-seq) on 1275 cells isolated from 10 patients with HCC, ploidy-resolved scDNA-seq on 356 cells from 1 additional patient, and single-cell RNA sequencing on 27,344 cells from 3 additional patients. Three statistical fitting models were compared to investigate the CNA accumulation pattern.

RESULTS

Cells in the tumor were categorized into the following 3 subpopulations: euploid, pseudoeuploid, and aneuploid. Our scDNA-seq analysis revealed that CNA accumulation followed a dual-phase copy number evolution model, that is, a punctuated phase followed by a gradual phase. Patients who exhibited prolonged gradual phase showed higher intratumor heterogeneity and worse disease-free survival. Integrating bulk RNA sequencing of 17 patients with HCC, published datasets of 1196 liver tumors, and immunohistochemical staining of 202 HCC tumors, we found that high expression of CAD, a gene involved in pyrimidine synthesis, was correlated with rapid tumorigenesis and reduced survival. The dual-phase copy number evolution model was validated by our single-cell RNA sequencing data and published scDNA-seq datasets of other cancer types. Furthermore, ploidy-resolved scDNA-seq revealed the common clonal origin of diploid- and polyploid-aneuploid cells, suggesting that polyploid tumor cells were generated by whole genome doubling of diploid tumor cells.

CONCLUSIONS

Our work revealed a novel dual-phase copy number evolution model, showed HCC with longer gradual phase was more severe, identified CAD as a promising biomarker for early recurrence of HCC, and supported the diploid origin of polyploid HCC.

Cancer stem cells: advances in biology and clinical translation-a Keystone Symposia report

The test for the cancer stem cell (CSC) hypothesis is to find a target expressed on all, and only CSCs in a patient tumor, then eliminate all cells with that target that eliminates the cancer. That test has not yet been achieved, but CSC diagnostics and targets found on CSCs and some other cells have resulted in a few clinically relevant therapies. However, it has become apparent that eliminating the subset of tumor cells characterized by self-renewal properties is essential for long-term tumor control. CSCs are able to regenerate and initiate tumor growth, recapitulating the heterogeneity present in the tumor before treatment. As great progress has been made in identifying and elucidating the biology of CSCs as well as their interactions with the tumor microenvironment, the time seems ripe for novel therapeutic strategies that target CSCs to find clinical applicability. On May 19-21, 2021, researchers in cancer stem cells met virtually for the Keystone eSymposium "Cancer Stem Cells: Advances in Biology and Clinical Translation" to discuss recent advances in the understanding of CSCs as well as clinical efforts to target these populations.

Personalized circulating tumor DNA in patients with hepatocellular carcinoma: a pilot study

BACKGROUND

Mutational analysis of circulating tumor DNA (ctDNA) can potentially be used for early detection of recurrence after resection for hepatocellular carcinoma (HCC). Mutations from tumor may be identified in plasma as an early sign of recurrence. We conducted a pilot study investigating if somatic mutations could be detected in plasma in patients undergoing liver resection for HCC and in patients with advanced non-resectable HCC.

METHODS AND RESULTS

We prospectively included patients undergoing curative liver resection for HCC. Tumor tissue was investigated with whole exome sequencing and preoperative blood samples were evaluated for ctDNA using targeted next-generation sequencing (NGS) with TruSight Oncology 500 including 523 cancer-associated genes. Subsequently, the method was evaluated in patients with advanced HCC. We included eight patients curatively resected for HCC, where tumor tissue mutations were identified in seven patients. However, only in one patient tumor specific mutations were found in the preoperative blood sample. In all three patients with advanced HCC, tumor mutations were detected in the blood.

CONCLUSIONS

In patients with resectable HCC, ctDNA could not be reliably detected using the applied targeted NGS method. In contrast, ctDNA was detected in all patients with advanced HCC. Small tumors, tumor heterogeneity and limited sequencing coverage may explain the lack of detectable ctDNA.

Identification of Gene-Set Signature in Early-Stage Hepatocellular Carcinoma and Relevant Immune Characteristics

Background

The incidence of hepatocellular carcinoma (HCC) is rising worldwide, and there is limited therapeutic efficacy due to tumor microenvironment heterogeneity and difficulty in early-stage screening. This study aimed to develop and validate a gene set-based signature for early-stage HCC (eHCC) patients and further explored specific marker dysregulation mechanisms as well as immune characteristics.

Methods

We performed an integrated bioinformatics analysis of genomic, transcriptomic, and clinical data with three independent cohorts. We systematically reviewed the crosstalk between specific genes, tumor prognosis, immune characteristics, and biological function in the different pathological stage samples. Univariate and multivariate survival analyses were performed in The Cancer Genome Atlas (TCGA) patients with survival data. Diethylnitrosamine (DEN)-induced HCC in Wistar rats was employed to verify the reliability of the predictions.

Results

We identified a Cluster gene that potentially segregates patients with eHCC from non-tumor, through integrated analysis of expression, overall survival, immune cell characteristics, and biology function landscapes. Immune infiltration analysis showed that lower infiltration of specific immune cells may be responsible for significantly worse prognosis in HCC (hazard ratio, 1.691; 95% CI: 1.171–2.441; p = 0.012), such as CD8 Tem and cytotoxic T cells (CTLs) in eHCC. Our results identified that Cluster C1 signature presented a high accuracy in predicting CD8 Tem and CTL immune cells (receiver operating characteristic (ROC) = 0.647) and cancerization (ROC = 0.946) in liver. As a central member of Cluster C1, overexpressed PRKDC was associated with the higher genetic alteration in eHCC than advanced-stage HCC (aHCC), which was also connected to immune cell-related poor prognosis. Finally, the predictive outcome of Cluster C1 and PRKDC alteration in DEN-induced eHCC rats was also confirmed.

Conclusions

As a tumor prognosis-relevant gene set-based signature, Cluster C1 showed an effective approach to predict cancerization of eHCC and its related immune characteristics with considerable clinical value.

In Vivo and In Vitro Models of Hepatocellular Carcinoma: Current Strategies for Translational Modeling

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer-related death globally. HCC is a complex multistep disease and usually emerges in the setting of chronic liver diseases. The molecular pathogenesis of HCC varies according to the etiology, mainly caused by chronic hepatitis B and C virus infections, chronic alcohol consumption, aflatoxin-contaminated food, and non-alcoholic fatty liver disease associated with metabolic syndrome or diabetes mellitus. The establishment of HCC models has become essential for both basic and translational research to improve our understanding of the pathophysiology and unravel new molecular drivers of this disease. The ideal model should recapitulate key events observed during hepatocarcinogenesis and HCC progression in view of establishing effective diagnostic and therapeutic strategies to be translated into clinical practice. Despite considerable efforts currently devoted to liver cancer research, only a few anti-HCC drugs are available, and patient prognosis and survival are still poor. The present paper provides a state-of-the-art overview of in vivo and in vitro models used for translational modeling of HCC with a specific focus on their key molecular hallmarks.

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.

Genomic characterization of rare molecular subclasses of hepatocellular carcinoma

Primary liver cancer, consisting of both cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC), is the second leading cause of cancer deaths worldwide. Our goal is to genomically characterize rare HCC subclasses to provide insight into disease biology. Leveraging The Cancer Genome Atlas (TCGA) to perform a combined analysis of CCA (n = 36) and HCC (n = 275), we integrated multiple genomic platforms, to assess transcriptional profiles, mutational signatures, and copy number patterns to uncover underlying etiology and linage specific patterns. We identified two molecular classes distinct from prototypical HCC tumors. The first, CCA-Like, although histologically indistinguishable from HCC, had enrichment of CCA mutations (IDH1, BAP1), mutational signatures, and transcriptional patterns (SOX9, KRT19). CCA-Like, however, retained a copy number landscape similar to HCC, suggesting a hepatocellular linage. The second, Blast-Like, is enriched in TP53 mutations, HBV infection, exposure related mutational signatures and transcriptionally similar to hepatoblasts. Although these subclasses are molecularly distinct, they both have a worse progression-free survival compared to classical HCC tumors, yet are clinically treated the same. The identification of and characterization of CCA-Like and Blast-Like subclasses advance our knowledge of HCC as well as represents an urgent need for the identification of class specific biomarkers and targeted therapy.

Jeffrey Damrauer, Markia Smith et al. used existing datasets from cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) to characterize two subsets of HCC distinct from prototypical HCC tumors, based on comprehensive analysis of molecular data. The two classes differed from HCC by their copy number, gene expression and mutational signature and exhibited worse progression free survival, highlighting the need to identify class-specific biomarkers and develop targeted therapies for these forms of cancer.

The role of bone marrow-derived cells in the origin of liver cancer revealed by single-cell sequencing

Objective: Epithelial cancers often originate from progenitor cells, while the origin of hepatocellular carcinoma (HCC) is still controversial. HCC, one of the deadliest cancers, is closely linked with liver injuries and chronic inflammation, which trigger massive infiltration of bone marrow-derived cells (BMDCs) during liver repair. Methods: To address the possible roles of BMDCs in HCC origination, we established a diethylnitrosamine (DEN)-induced HCC model in bone marrow transplanted mice. Immunohistochemistry and frozen tissue immunofluorescence were used to verify DEN-induced HCC in the pathology of the disease. The cellular origin of DEN-induced HCC was further studied by single cell sequencing, single-cell nested PCR, and immunofluorescence-fluorescence in situ hybridization. Results: Studies by using single cell sequencing and biochemical analysis revealed that HCC cells in these mice were coming from donor mice BMDCs, and not from recipient mice. Furthermore, the copy numbers of mouse orthologs of several HCC-related genes previously reported in human HCC were also altered in our mouse model. DEN-induced HCCs exhibited a similar histological phenotype and genomic profile as human HCCs. Conclusions: These results suggested that BMDCs are an important origin of HCC, which provide important clues to HCC prevention, detection, and treatments.

Hepatic Cancer Stem Cells: Molecular Mechanisms, Therapeutic Implications, and Circulating Biomarkers

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. HCC is associated with multiple risk factors and is characterized by a marked tumor heterogeneity that makes its molecular classification difficult to apply in the clinics. The lack of circulating biomarkers for the diagnosis, prognosis, and prediction of response to treatments further undermines the possibility of developing personalized therapies. Accumulating evidence affirms the involvement of cancer stem cells (CSCs) in tumor heterogeneity, recurrence, and drug resistance. Owing to the contribution of CSCs to treatment failure, there is an urgent need to develop novel therapeutic strategies targeting, not only the tumor bulk, but also the CSC subpopulation. Clarification of the molecular mechanisms influencing CSC properties, and the identification of their functional roles in tumor progression, may facilitate the discovery of novel CSC-based therapeutic targets to be used alone, or in combination with current anticancer agents, for the treatment of HCC. Here, we review the driving forces behind the regulation of liver CSCs and their therapeutic implications. Additionally, we provide data on their possible exploitation as prognostic and predictive biomarkers in patients with HCC.

IDH Mutation Subgroup Status Associates with Intratumor Heterogeneity and the Tumor Microenvironment in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is highly heterogeneous. Here, the authors perform exome sequencing and bulk RNA sequencing on 73 tumor regions from 14 ICC patients to portray the multi-faceted intratumor heterogeneity (ITH) landscape of ICC. The authors show that ITH is highly concordant across genomic, transcriptomic, and immune levels. Comparison of these data to 8 published datasets reveals significantly higher degrees of ITH in ICC than hepatocellular carcinoma. Remarkably, the authors find that high-ITH tumors highly overlap with the IDH (isocitrate dehydrogenase)-mutant subgroup (IDH-SG), comprising of IDH-mutated tumors and IDH-like tumors, that is, those IDH-wildtype tumors that exhibit similar molecular profiles to the IDH-mutated ones. Furthermore, IDH-SG exhibits less T cell infiltration and lower T cell cytotoxicity, indicating a colder tumor microenvironment (TME). The higher ITH and colder TME of IDH-SG are successfully validated by single-cell RNA sequencing on 17 503 cells from 4 patients. Collectively, the study shows that IDH mutant subgroup status, rather than IDH mutation alone, is associated with ITH and the TME of ICC tumors. The results highlight that IDH-like patients may also benefit from IDH targeted therapies and provide important implications for the diagnosis and treatment of ICC.

Detection of CTNNB1 Hotspot Mutations in Cell-Free DNA from the Urine of Hepatocellular Carcinoma Patients

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. The beta-catenin gene, CTNNB1, is among the most frequently mutated in HCC tissues. However, mutational analysis of HCC tumors is hampered by the difficulty of obtaining tissue samples using traditional biopsy. Here, we explored the feasibility of detecting tumor-derived CTNNB1 mutations in cell-free DNA (cfDNA) extracted from the urine of HCC patients. Using a short amplicon qPCR assay targeting HCC mutational hotspot CTNNB1 codons 32-37 (exon 3), we detected CTNNB1 mutations in 25% (18/73) of HCC tissues and 24% (15/62) of pre-operative HCC urine samples in two independent cohorts. Among the CTNNB1-mutation-positive patients with available matched pre- and post-operative urine (n = 13), nine showed apparent elimination (n = 7) or severalfold reduction (n = 2) of the mutation in urine following tumor resection. Four of the seven patients with no detectable mutations in postoperative urine remained recurrence-free within five years after surgery. In contrast, all six patients with mutation-positive in post-operative urine recurred, including the two with reduced mutation levels. This is the first report of association between the presence of CTNNB1 mutations in pre- and post-operative urine cfDNA and HCC recurrence with implications for minimum residual disease detection.

Lenvatinib: established and promising drug for the treatment of advanced hepatocellular carcinoma

INTRODUCTION

: The evolving therapeutic landscape of advanced hepatocellular carcinoma (HCC) includes the increasing implementation of target-therapy and immunotherapy. Lenvatinib, a multi-target tyrosine kinase inhibitor (TKI), is an emerging first-line therapy for hepatocellular carcinoma. Its approval has changed the scenario of first-line therapies for advanced HCC, where just sorafenib proved clinical efficacy for over a decade.

AREAS COVERED

: The current evidence on the role of lenvatinib for patients with advanced HCC is reviewed in this article. Particularly, therapeutic mechanisms and clinical efficacy of lenvatinib are summarized and the management of adverse events is discussed. In addition, future perspectives on the emerging role of combine therapy for HCC are highlighted.

EXPERT OPINION

In the first line, lenvatinib was found to be non-inferior to sorafenib for overall survival, with significantly better progression-free survival and objective response rate. Immune checkpoint inhibitors (ICIs) are now part of HCC treatment, and recently the combination of atezolizumab plus bevacizumab has become the recommended standard of care first-line therapy for selected patients. The antitumor and immunomodulatory activities that lenvatinib shows in preclinical studies, and the positive outcomes achieved using a combination of lenvatinib plus ICIs, open new perspectives for advanced HCC treatment.