Type I IFNs promote cancer cell stemness by triggering the epigenetic regulator KDM1B.

Cancer stem cells (CSCs) are a subpopulation of cancer cells endowed with high tumorigenic, chemoresistant and metastatic potential. Nongenetic mechanisms of acquired resistance are increasingly being discovered, but molecular insights into the evolutionary process of CSCs are limited. Here, we show that type I interferons (IFNs-I) function as molecular hubs of resistance during immunogenic chemotherapy, triggering the epigenetic regulator demethylase 1B (KDM1B) to promote an adaptive, yet reversible, transcriptional rewiring of cancer cells towards stemness and immune escape. Accordingly, KDM1B inhibition prevents the appearance of IFN-I-induced CSCs, both in vitro and in vivo. Notably, IFN-I-induced CSCs are heterogeneous in terms of multidrug resistance, plasticity, invasiveness and immunogenicity. Moreover, in breast cancer (BC) patients receiving anthracycline-based chemotherapy, KDM1B positively correlated with CSC signatures. Our study identifies an IFN-I → KDM1B axis as a potent engine of cancer cell reprogramming, supporting KDM1B targeting as an attractive adjunctive to immunogenic drugs to prevent CSC expansion and increase the long-term benefit of therapy.

Clinical bioinformatics desiderata for molecular tumor boards.

Clinical Bioinformatics is a knowledge framework required to interpret data of medical interest via computational methods. This area became of dramatic importance in precision oncology, fueled by cancer genomic profiling: most definitions of Molecular Tumor Boards require the presence of bioinformaticians. However, all available literature remained rather vague on what are the specific needs in terms of digital tools and expertise to tackle and interpret genomics data to assign novel targeted or biomarker-driven targeted therapies to cancer patients. To fill this gap, in this article, we present a catalog of software families and human skills required for the tumor board bioinformatician, with specific examples of real-world applications associated with each element presented.

Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres.

BACKGROUND: The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. METHODS: 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. RESULTS: The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan-Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. CONCLUSIONS: The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research.

The Glioma-IRE project - Molecular profiling in patients with glioma: steps toward an individualized diagnostic and therapeutic approach.

BACKGROUND: This study aimed to characterize the genetic profile of patients with glioma and discuss the impact of next-generation sequencing in glioma diagnosis and treatment. METHODS: Between 2019 and 2022, we analyzed the genetic profile of 99 patients with glioma through the Oncomine Focus Assay. The assay enables the detection of mutations in 52 driver genes, including single nucleotide variants (SNVs), copy number variants (CNVs), and gene fusions. We also collected and analyzed patients' clinic characteristics and treatment outcomes. RESULTS: Over a period of 35 months, 700 patients with glioma followed by our neuro-oncology unit were screened, and 99 were enrolled in the study; most of the patients were excluded for inadequate non-morphological MRI or lack/inadequacy of the tissue samples. Based on our findings, most patients with glioma present mutations, such as SNVs, CNVs or gene fusions. Our data were similar to those reported by The Cancer Genome Atlas Program in terms of frequency of SNVs and CNVs, while we observed more cases of gene fusions. Median overall survival, progression-free survival, and time to progression were significantly lower for patients with grade VI glioblastoma than those with other gliomas. Only four patients were offered a targeted treatment based on the mutation detected; however, only one received treatment, the others could not receive the selected treatment because of worsening clinical status. CONCLUSION: Routine timely molecular profiling in patients with glioma should be implemented to offer patients an individualized diagnostic approach and provide them with advanced targeted therapy options if available.

The Molecular Tumor Board of the Regina Elena National Cancer Institute: from accrual to treatment in real-world.

BACKGROUND: Molecular Tumor Boards (MTB) operating in real-world have generated limited consensus on good practices for accrual, actionable alteration mapping, and outcome metrics. These topics are addressed herein in 124 MTB patients, all real-world accrued at progression, and lacking approved therapy options. METHODS: Actionable genomic alterations identified by tumor DNA (tDNA) and circulating tumor DNA (ctDNA) profiling were mapped by customized OncoKB criteria to reflect diagnostic/therapeutic indications as approved in Europe. Alterations were considered non-SoC when mapped at either OncoKB level 3, regardless of tDNA/ctDNA origin, or at OncoKB levels 1/2, provided they were undetectable in matched tDNA, and had not been exploited in previous therapy lines. RESULTS: Altogether, actionable alterations were detected in 54/124 (43.5%) MTB patients, but only in 39 cases (31%) were these alterations (25 from tDNA, 14 from ctDNA) actionable/unexploited, e.g. they had not resulted in the assignment of pre-MTB treatments. Interestingly, actionable and actionable/unexploited alterations both decreased (37.5% and 22.7% respectively) in a subset of 88 MTB patients profiled by tDNA-only, but increased considerably (77.7% and 66.7%) in 18 distinct patients undergoing combined tDNA/ctDNA testing, approaching the potential treatment opportunities (76.9%) in 147 treatment-naïve patients undergoing routine tDNA profiling for the first time. Non-SoC therapy was MTB-recommended to all 39 patients with actionable/unexploited alterations, but only 22 (56%) accessed the applicable drug, mainly due to clinical deterioration, lengthy drug-gathering procedures, and geographical distance from recruiting clinical trials. Partial response and stable disease were recorded in 8 and 7 of 19 evaluable patients, respectively. The time to progression (TTP) ratio (MTB-recommended treatment vs last pre-MTB treatment) exceeded the conventional Von Hoff 1.3 cut-off in 9/19 cases, high absolute TTP and Von Hoff values coinciding in 3 cases. Retrospectively, 8 patients receiving post-MTB treatment(s) as per physician's choice were noted to have a much longer overall survival from MTB accrual than 11 patients who had received no further treatment (35.09 vs 6.67 months, p = 0.006). CONCLUSIONS: MTB-recommended/non-SoC treatments are effective, including those assigned by ctDNA-only alterations. However, real-world MTBs may inadvertently recruit patients electively susceptible to diverse and/or multiple treatments.

Development of a somatic variant registry in a National Cancer Center: towards Molecular Real World Data preparedness.

The Biomedical Research field is currently advancing to develop Clinical Trials and translational projects based on Real World Evidence. To make this transition feasible, clinical centers need to work toward Data Accessibility and Interoperability. This task is particularly challenging when applied to Genomics, that entered in routinary screening in the last years via mostly amplicon-based Next-Generation Sequencing panels. Said experiments produce up to hundreds of features per patient, and their summarized results are often stored in static clinical reports, making critical information inaccessible to automated access and Federated Search consortia. In this study, we present a reanalysis of 4620 solid tumor sequencing samples in five different histology settings. Furthermore, we describe all the Bioinformatics and Data Engineering processes that were put in place in order to create a Somatic Variant Registry able to deal with the large biotechnological variability of routinary Genomics Profiling.

Machine learning endometrial cancer risk prediction model: integrating guidelines of European Society for Medical Oncology with the tumor immune framework.

OBJECTIVE: Current prognostic factors for endometrial cancer are not sufficient to predict recurrence in early stages. Treatment choices are based on the prognostic factors included in the risk classes defined by the ESMO-ESGO-ESTRO (European Society for Medical Oncology-European Society of Gynaecological Oncology-European Society for Radiotherapy and Oncology) consensus conference with the new biomolecular classification based on POLE, TP53, and microsatellite instability status. However, a minority of early stage cases relapse regardless of their low risk profiles. Integration of the immune context status to existing molecular based models has not been fully evaluated. This study aims to investigate whether the integration of the immune landscape in the tumor microenvironment could improve clinical risk prediction models and allow better profiling of early stages. METHODS: Leveraging the potential of in silico deconvolution tools, we estimated the relative abundances of immune populations in public data and then applied feature selection methods to generate a machine learning based model for disease free survival probability prediction. RESULTS: We included information on International Federation of Gynecology and Obstetrics (FIGO) stage, tumor mutational burden, microsatellite instability, POLEmut status, interferon γ signature, and relative abundances of monocytes, natural killer cells, and CD4+T cells to build a relapse prediction model and obtained a balanced accuracy of 69%. We further identified two novel early stage profiles that undergo different pathways of recurrence. CONCLUSION: This study presents an extension of current prognostic factors for endometrial cancer by exploiting machine learning models and deconvolution techniques on available public biomolecular data. Prospective clinical trials are advisable to validate the early stage stratification.

Molecular dissection of a hyper-aggressive CBFB-MYH11/FLT3-ITD-positive acute myeloid leukemia.

Acute Myeloid Leukaemia (AML) is a haematological malignancy showing a hypervariable landscape of clinical outcomes and phenotypic differences, explainable by heterogeneity at the cellular and molecular level. Among the most common genomic alterations, CBFB-MYH11 rearrangement and FLT3-ITD gene mutations, have opposite clinical significance and are unfrequently associated. We present here a Molecular Case Report in which these two events co-exist an ultra-aggressive phenotype resulting in death in 4 days from hospital admittance. Somatic and germline Whole Exome Sequencing analysis was performed to uncover other putative driver mutations, de-novo genomic structural events or germline clusters increasing cancer insurgence. Only three mutations in LTK, BCAS2 and LGAS9 were found, unlikely causative of the exhibited phenotype, prompting to additional investigation of the rare CBFB-MYH11/ FLT3-ITD scenario.

Hepatitis B protein HBx binds the DLEU2 lncRNA to sustain cccDNA and host cancer-related gene transcription.

OBJECTIVE: The HBV HBx regulatory protein is required for transcription from the covalently closed circular DNA (cccDNA) minichromosome and affects the epigenetic control of both viral and host cellular chromatin. DESIGN: We explored, in relevant cellular models of HBV replication, the functional consequences of HBx interaction with DLEU2, a long non-coding RNA (lncRNA) expressed in the liver and increased in human hepatocellular carcinoma (HCC), in the regulation of host target genes and the HBV cccDNA. RESULTS: We show that HBx binds the promoter region, enhances the transcription and induces the accumulation of DLEU2 in infected hepatocytes. We found that nuclear DLEU2 directly binds HBx and the histone methyltransferase enhancer of zeste homolog 2 (EZH2), the catalytic active subunit of the polycomb repressor complex 2 (PRC2) complex. Computational modelling and biochemical evidence suggest that HBx and EZH2 share two preferential binding sites in DLEU2 intron 1. HBx and DLEU2 co-recruitment on the cccDNA displaces EZH2 from the viral chromatin to boost transcription and viral replication. DLEU2-HBx association with target host promoters relieves EZH2 repression and leads to the transcriptional activation of a subset of EZH2/PRC2 target genes in HBV-infected cells and HBV-related HCCs. CONCLUSIONS: Our results highlight the ability of HBx to bind RNA to impact on the epigenetic control of both viral cccDNA and host genes and provide a new key to understand the role of DLEU2 and EZH2 overexpression in HBV-related HCCs and HBx contribution to hepatocytes transformation.