Hepatocellular Carcinoma in Mongolia Delineates Unique Molecular Traits and a Mutational Signature Associated with Environmental Agents.

PURPOSE: Mongolia has the world's highest incidence of hepatocellular carcinoma (HCC), with ∼100 cases/100,000 inhabitants, although the reasons for this have not been thoroughly delineated. EXPERIMENTAL DESIGN: We performed a molecular characterization of Mongolian (n = 192) compared with Western (n = 187) HCCs by RNA sequencing and whole-exome sequencing to unveil distinct genomic and transcriptomic features associated with environmental factors in this population. RESULTS: Mongolian patients were younger, with higher female prevalence, and with predominantly HBV-HDV coinfection etiology. Mongolian HCCs presented significantly higher rates of protein-coding mutations (121 vs. 70 mutations per tumor in Western), and in specific driver HCC genes (i.e., APOB and TSC2). Four mutational signatures characterized Mongolian samples, one of which was novel (SBS Mongolia) and present in 25% of Mongolian HCC cases. This signature showed a distinct substitution profile with a high proportion of T>G substitutions and was significantly associated with a signature of exposure to the environmental agent dimethyl sulfate (71%), a 2A carcinogenic associated with coal combustion. Transcriptomic-based analysis delineated three molecular clusters, two not present in Western HCC; one with a highly inflamed profile and the other significantly associated with younger female patients. CONCLUSIONS: Mongolian HCC has unique molecular traits with a high mutational burden and a novel mutational signature associated with genotoxic environmental factors present in this country.

CXCR2 inhibition enables NASH-HCC immunotherapy.

OBJECTIVE: Hepatocellular carcinoma (HCC) is increasingly associated with non-alcoholic steatohepatitis (NASH). HCC immunotherapy offers great promise; however, recent data suggests NASH-HCC may be less sensitive to conventional immune checkpoint inhibition (ICI). We hypothesised that targeting neutrophils using a CXCR2 small molecule inhibitor may sensitise NASH-HCC to ICI therapy. DESIGN: Neutrophil infiltration was characterised in human HCC and mouse models of HCC. Late-stage intervention with anti-PD1 and/or a CXCR2 inhibitor was performed in murine models of NASH-HCC. The tumour immune microenvironment was characterised by imaging mass cytometry, RNA-seq and flow cytometry. RESULTS: Neutrophils expressing CXCR2, a receptor crucial to neutrophil recruitment in acute-injury, are highly represented in human NASH-HCC. In models of NASH-HCC lacking response to ICI, the combination of a CXCR2 antagonist with anti-PD1 suppressed tumour burden and extended survival. Combination therapy increased intratumoural XCR1+ dendritic cell activation and CD8+ T cell numbers which are associated with anti-tumoural immunity, this was confirmed by loss of therapeutic effect on genetic impairment of myeloid cell recruitment, neutralisation of the XCR1-ligand XCL1 or depletion of CD8+ T cells. Therapeutic benefit was accompanied by an unexpected increase in tumour-associated neutrophils (TANs) which switched from a protumour to anti-tumour progenitor-like neutrophil phenotype. Reprogrammed TANs were found in direct contact with CD8+ T cells in clusters that were enriched for the cytotoxic anti-tumoural protease granzyme B. Neutrophil reprogramming was not observed in the circulation indicative of the combination therapy selectively influencing TANs. CONCLUSION: CXCR2-inhibition induces reprogramming of the tumour immune microenvironment that promotes ICI in NASH-HCC.

Cabozantinib Enhances Anti-PD1 Activity and Elicits a Neutrophil-Based Immune Response in Hepatocellular Carcinoma.

PURPOSE: Immune checkpoint inhibitors combined with antiangiogenic agents produce benefits in the treatment of advanced hepatocellular carcinoma (HCC). We investigated the efficacy and immunomodulatory activity of cabozantinib alone and combined with anti-PD1 in experimental models of HCC, and explored the potential target population that might benefit from this combination. EXPERIMENTAL DESIGN: C57BL/6J mice bearing subcutaneous Hepa1-6 or Hep53.4 tumors received cabozantinib, anti-PD1, their combination, or placebo. Tumor and blood samples were analyzed by flow cytometry, IHC, transcriptome, and cytokine profiling. Cabozantinib-related effects were validated in a colorectal cancer patient-derived xenograft model. Transcriptomic data from three human HCC cohorts (cohort 1: n = 167, cohort 2: n = 57, The Cancer Genome Atlas: n = 319) were used to cluster patients according to neutrophil features, and assess their impact on survival. RESULTS: The combination of cabozantinib and anti-PD1 showed increased antitumor efficacy compared with monotherapy and placebo (P < 0.05). Cabozantinib alone significantly increased neutrophil infiltration and reduced intratumor CD8+PD1+ T-cell proportions, while the combination with anti-PD1 further stimulated both effects and significantly decreased regulatory T cell (Treg) infiltration (all P < 0.05). In blood, cabozantinib and especially combination increased the proportions of overall T cells (P < 0.01) and memory/effector T cells (P < 0.05), while lowering the neutrophil-to-lymphocyte ratio (P < 0.001 for combination). Unsupervised clustering of human HCCs revealed that high tumor enrichment in neutrophil features observed with the treatment combination was linked to less aggressive tumors with more differentiated and less proliferative phenotypes. CONCLUSIONS: Cabozantinib in combination with anti-PD1 enhanced antitumor immunity by bringing together innate neutrophil-driven and adaptive immune responses, a mechanism of action which favors this approach for HCC treatment.

PCIG: a web-based application to explore immune-genomics interactions across cancer types.

MOTIVATION: Genomic alterations can modulate the tumor immunophenotype depending on their nature and tissue of origin. Although this immune-genomic interaction may shape disease progression and response to immunotherapy, the factors governing such dynamics and the influence of each tissue-specific context remain poorly understood. RESULTS: Here, we have developed the PanCancer ImmunoGenomics (PCIG) tool, a web-based resource that provides researchers with the opportunity to mine immunome-genome relationships across several cancer types using data from the Pan-Cancer Analysis of Whole-Genomes (PCAWG) study, which comprises >2,600 samples spanning across 20 different cancer primary sites. PCIG yields an integrative analysis of the crosstalk between somatic genomic alterations and different immune features, thus helping to understand immune response-related processes. AVAILABILITY AND IMPLEMENTATION: PCIG is freely available at https://pcig.vhio.net and is supported by all major web browsers. PCIG was developed with Django, which is a Python-based free and open-source framework, and it uses SQL Server as a relational database management system. The code is freely available for download at GitHub https://github.com/AnnaPG/PCIG and in its online supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Copy-Number Alteration Burden Differentially Impacts Immune Profiles and Molecular Features of Hepatocellular Carcinoma.

PURPOSE: Chromosomal instability is a hallmark of cancer that results in broad and focal copy-number alterations (CNAs), two events associated with distinct molecular, immunologic, and clinical features. In hepatocellular carcinoma (HCC), the role of CNAs has not been thoroughly assessed. Thus, we dissected the impact of CNA burdens on HCC molecular and immune features. EXPERIMENTAL DESIGN: We analyzed SNP array data from 452 paired tumor/adjacent resected HCCs and 25 dysplastic nodules. For each sample, broad and focal CNA burdens were quantified using CNApp, and the resulting broad scores (BS) and focal scores (FS) were correlated with transcriptomic, mutational, and methylation profiles, tumor immune composition, and clinicopathologic data. RESULTS: HCCs with low broad CNA burdens (defined as BS ≤ 4; 17%) presented high inflammation, active infiltrate signaling, high cytolytic activity, and enrichment of the "HCC immune class" and gene signatures related to antigen presentation. Conversely, tumors with chromosomal instability (high broad CNA loads, BS ≥ 11; 40%), displayed immune-excluded traits and were linked to proliferation, TP53 dysfunction, and DNA repair. Candidate determinants of the low cytotoxicity and immune exclusion features of high-BS tumors included alterations in antigen-presenting machinery (i.e., HLA), widespread hypomethylation, and decreased rates of observed/expected neoantigenic mutations. High FSs were independent of tumor immune features, but were related to proliferation, TP53 dysfunction, and progenitor cell traits. CONCLUSIONS: HCCs with high chromosomal instability exhibit features of immune exclusion, whereas tumors displaying low burdens of broad CNAs present an immune active profile. These CNA scores can be tested to predict response to immunotherapies.

Molecular classification and therapeutic targets in extrahepatic cholangiocarcinoma.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA), a deadly malignancy of the bile ducts, can be classified based on its anatomical location into either intrahepatic (iCCA) or extrahepatic (eCCA), each with different pathogenesis and clinical management. There is limited understanding of the molecular landscape of eCCA and no targeted therapy with clinical efficacy has been approved. We aimed to provide a molecular classification of eCCA and identify potential targets for molecular therapies. METHODS: An integrative genomic analysis of an international multicenter cohort of 189 eCCA cases was conducted. Genomic analysis included whole-genome expression, targeted DNA-sequencing and immunohistochemistry. Molecular findings were validated in an external set of 181 biliary tract tumors from the ICGC. RESULTS: KRAS (36.7%), TP53 (34.7%), ARID1A (14%) and SMAD4 (10.7%) were the most prevalent mutations, with ∼25% of tumors having a putative actionable genomic alteration according to OncoKB. Transcriptome-based unsupervised clustering helped us define 4 molecular classes of eCCA. Tumors classified within the Metabolic class (19%) showed a hepatocyte-like phenotype with activation of the transcription factor HNF4A and enrichment in gene signatures related to bile acid metabolism. The Proliferation class (23%), more common in patients with distal CCA, was characterized by enrichment of MYC targets, ERBB2 mutations/amplifications and activation of mTOR signaling. The Mesenchymal class (47%) was defined by signatures of epithelial-mesenchymal transition, aberrant TGFß signaling and poor overall survival. Finally, tumors in the Immune class (11%) had a higher lymphocyte infiltration, overexpression of PD-1/PD-L1 and molecular features associated with a better response to immune checkpoint inhibitors. CONCLUSION: An integrative molecular characterization identified distinct subclasses of eCCA. Genomic traits of each class provide the rationale for exploring patient stratification and novel therapeutic approaches. LAY SUMMARY: Targeted therapies have not been approved for the treatment of extrahepatic cholangiocarcinoma. We performed a multi-platform molecular characterization of this tumor in a cohort of 189 patients. These analyses revealed 4 novel transcriptome-based molecular classes of extrahepatic cholangiocarcinoma and identified ∼25% of tumors with actionable genomic alterations, which has potential prognostic and therapeutic implications.

CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications.

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/.

In most cases, human cells contain two copies of each of their genes, yet sometimes this can change, an effect called copy number alteration (CNA). Cancer is a genetic disease and thus, studying the DNA from tumor samples is crucial to improving diagnosis and choosing the right treatment. Most tumors contain cells with CNAs; however, the impact of CNAs in cancer progression is poorly understood. CNAs can be studied by examining the genome of tumor cells and finding which regions display an unusual number of copies. It may also be possible to gather information about different cancer types by analyzing the CNAs in a tumor, but this approach requires the analysis of large amounts of data. To aid the analysis of CNAs in cancer cells, Franch-Expósito, Bassaganyas et al. have created an online tool called CNApp, which is able to identify and count CNAs in genomic data and link them to features associated with different cancers. The hope is that a better understanding of the effect of CNAs in cancer could help better diagnose cancers, and improve outcomes for patients. Potentially, this could also predict what type of treatment would work better for a specific tumor. Besides, by using a machine-learning approach, the tool can also make predictions about specific cancer subtypes in order to facilitate clinical decisions. Franch-Expósito, Bassaganyas et al. tested CNApp using previously existing cancer data from 33 different cancer types to show how CNApp can help the interpretation of CNAs in cancer. Moreover, CNApp can also use CNAs to identify different types of bowel (colorectal) cancer in a way that could help doctors to make decisions about treatment. Together these findings show that CNApp provides an adaptable and accessible research tool for the study of cancer genomics, which could provide opportunities to inform medical procedures.

Molecular portrait of high alpha-fetoprotein in hepatocellular carcinoma: implications for biomarker-driven clinical trials.

The clinical utility of serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC) is widely recognised. However, a clear understanding of the mechanisms of AFP overexpression and the molecular traits of patients with AFP-high tumours are not known. We assessed transcriptome data, whole-exome sequencing data and DNA methylome profiling of 520 HCC patients from two independent cohorts to identify distinct molecular traits of patients with AFP-high tumours (serum concentration > 400 ng/ml), which represents an accepted prognostic cut-off and a predictor of response to ramucirumab. Those AFP-high tumours (18% of resected cases) were characterised by significantly lower AFP promoter methylation (p < 0.001), significant enrichment of progenitor-cell features (CK19, EPCAM), higher incidence of BAP1 oncogene mutations (8.5% vs 1.6%) and lower mutational rates of CTNNB1 (14% vs 30%). Specifically, AFP-high tumours displayed significant activation of VEGF signalling (p < 0.001), which might provide the rationale for the reported benefit of ramucirumab in this subgroup of patients.