Integrated multi-omics profiling reveals the role of the DNA methylation landscape in shaping biological heterogeneity and clinical behaviour of metastatic melanoma.

Background: We developed an integrated multi-omics analysis in metastatic melanoma (MM) cohorts to associate DNA methylation profiles with tumor progression, survival, response to adjuvant immunotherapy, structure of the tumor immune microenvironment and transcriptional programs of immunity and melanoma differentiation.

Methods: Lesions (n = 191) from a fully annotated, retrospective cohort of 165 AJCC 8th Stage III and IV melanoma patients (EPICA cohort) were characterized by reduced representation bisulfite sequencing, RNA sequencing, whole exome sequencing, quantitative immunohistochemistry and multiplex immunofluorescence analysis. The TCGA melanoma datasets were used for validation.

Impact of the tumor immune contexture in microsatellite-stable metastatic colorectal cancer treated with avelumab, cetuximab, and irinotecan.

The treatment of patients with microsatellite-stable (MSS) metastatic colorectal cancer (mCRC) remains a significant clinical challenge. Cetuximab, an anti-epidermal growth factor receptor (EGFR) monoclonal antibody (mAb), induces immunogenic cell death, potentially synergizing with immune checkpoint inhibitors. The phase 2, proof-of-concept, single-arm AVETUXIRI trial (ClinicalTrials.

Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network.

Background And Objective: In recent years, DNA methylation-tumor classification based on artificial intelligence algorithms has led to a notable improvement in diagnostic accuracy compared to traditional machine learning methods. In cancer, the methylation pattern likely reflects both the cell of origin and somatically acquired DNA methylation changes, making this epigenetic modification an ideal tool for tumor classification. We propose an in-depth method based on the Convolutional Neural Network for the DNA methylation-based classification of papillary thyroid carcinoma (PTC) and its follicular (fvPTC) and classical (cvPTC) subtypes.

Proteomic-based stemness score measures oncogenic dedifferentiation and enables the identification of druggable targets.

Cancer progression and therapeutic resistance are closely linked to a stemness phenotype. Here, we introduce a protein-expression-based stemness index (PROTsi) to evaluate oncogenic dedifferentiation in relation to histopathology, molecular features, and clinical outcomes. Utilizing datasets from the Clinical Proteomic Tumor Analysis Consortium across 11 tumor types, we validate PROTsi's effectiveness in accurately quantifying stem-like features.

Genome-wide methylome modeling via generative AI incorporating long- and short-range interactions.

Using millions of methylation segments, we developed DiffuCpG, a generative artificial intelligence (AI) diffusion model designed to solve the critical challenge of missing data in high-throughput methylation technologies. DiffuCpG goes beyond conventional methods by leveraging both short-range interactions including nearby CpGs from both latitude and longitude of the dataset, local DNA sequences, and long-range interactions, including three-dimensional genome architecture and long-distance correlations, to comprehensively model the methylome. Compared to previous methods, through extensive independent validations across different tissue types, cancers, and technologies (whole-genome bisulfite sequencing, enhanced reduced representation bisulfite sequencing, single-cell bisulfite sequencing, and methylation arrays), DiffuCpG has demonstrated superior performance in accuracy, scalability, and versatility.

A detailed guide to assessing genome assembly based on long-read sequencing data using Inspector.

Long-read sequencing technologies yield extended DNA sequences capable of spanning intricate, repetitive genome regions, thereby facilitating the generation of more precise and comprehensive genome assemblies. However, assembly errors are inevitable owing to inherent genomic complexity and limitations of sequencing technology and assembly algorithms, making assembly evaluation crucial. The genome assembly evaluation tool Inspector presents several advantages over existing long-read de novo assembly evaluation tools, including (1) both reference-free and reference-guided assembly evaluation; (2) the ability to detect both small- and large-scale structural errors; (3) the option of assembly error correction, which can improve the quality value of the original assembly; and (4) the ability to perform haplotype-resolved assembly evaluation.

Activating antiviral immune responses potentiates immune checkpoint inhibition in glioblastoma models.

Viral mimicry refers to the activation of innate antiviral immune responses due to the induction of endogenous retroelements (REs). Viral mimicry augments antitumor immune responses and sensitizes solid tumors to immunotherapy. Here, we found that targeting what we believe to be a novel, master epigenetic regulator, Zinc Finger Protein 638 (ZNF638), induces viral mimicry in glioblastoma (GBM) preclinical models and potentiates immune checkpoint inhibition (ICI).

DNA methylation status classifies pleural mesothelioma cells according to their immune profile: implication for precision epigenetic therapy.

Background: Co-targeting of immune checkpoint inhibitors (ICI) CTLA-4 and PD-1 has recently become the new first-line standard of care therapy of pleural mesothelioma (PM) patients, with a significant improvement of overall survival (OS) over conventional chemotherapy. The analysis by tumor histotype demonstrated greater efficacy of ICI therapy compared to standard chemotherapy in non-epithelioid (non-E) vs. epithelioid (E) PM, although some E PM patients also benefit from ICI treatment.

Leveraging mRNA technology for antigen based immuno-oncology therapies.

The application of messenger RNA (mRNA) technology in antigen-based immuno-oncology therapies represents a significant advancement in cancer treatment. Cancer vaccines are an effective combinatorial partner to sensitize the host immune system to the tumor and boost the efficacy of immune therapies. Selecting suitable tumor antigens is the key step to devising effective vaccinations and amplifying the immune response.

Treatment options for unstable posterior pelvic ring lesions: A multicenter retrospective cohort study of the Italian Society for the Traumatology of the Pelvis.

Purpose: Posterior pelvic ring lesions are a common finding in patients with pelvic trauma, representing a challenging condition for trauma surgeons. Surgical options are different and there is not yet evidence about the best option. Aim of the study are: (i) to compare Lumbopelvic fixation (LPF) and ilio-sacral screw fixation (ISS) regarding clinical and radiological outcome in unstable posterior pelvic ring injuries, both as whole population and single similar fracture types according to Tile classification (C1vsC1, C2vsC2, C3vsC3); (ii) to analyze clinical outcomes and complications in lumbopelvic fixation group, comparing open and closed reduction technique.

Whole-exome profiles of inflammatory breast cancer and pathological response to neoadjuvant chemotherapy.

Background: Neoadjuvant chemotherapy (NACT) became a standard treatment strategy for patients with inflammatory breast cancer (IBC) because of high disease aggressiveness. However, given the heterogeneity of IBC, no molecular feature reliably predicts the response to chemotherapy. Whole-exome sequencing (WES) of clinical tumor samples provides an opportunity to identify genomic alterations associated with chemosensitivity.

Targeting ZNF638 activates antiviral immune responses and potentiates immune checkpoint inhibition in glioblastoma.

Viral mimicry refers to the activation of innate anti-viral immune responses due to the induction of endogenous retroelement (RE) expression. Viral mimicry has been previously described to augment anti-tumor immune responses and sensitize solid tumors to immunotherapy including colorectal cancer, melanoma, and clear renal cell carcinoma. Here, we found that targeting a novel, master epigenetic regulator, Zinc Finger Protein 638 (ZNF638), induces viral mimicry in glioblastoma (GBM) preclinical models and potentiates immune checkpoint inhibition (ICI).

MoNETA: MultiOmics Network Embedding for SubType Analysis.

Cells are complex systems whose behavior emerges from a huge number of reactions taking place within and among different molecular districts. The availability of bulk and single-cell omics data fueled the creation of multi-omics systems biology models capturing the dynamics within and between omics layers. Powerful modeling strategies are needed to cope with the increased amount of data to be interrogated and the relative research questions.

Differential methylation of circulating free DNA assessed through cfMeDiP as a new tool for breast cancer diagnosis and detection of BRCA1/2 mutation.

Background: Recent studies have highlighted the importance of the cell-free DNA (cfDNA) methylation profile in detecting breast cancer (BC) and its different subtypes. We investigated whether plasma cfDNA methylation, using cell-free Methylated DNA Immunoprecipitation and High-Throughput Sequencing (cfMeDIP-seq), may be informative in characterizing breast cancer in patients with BRCA1/2 germline mutations for early cancer detection and response to therapy.

Methods: We enrolled 23 BC patients with germline mutation of BRCA1 and BRCA2 genes, 19 healthy controls without BRCA1/2 mutation, and two healthy individuals who carried BRCA1/2 mutations.

γ-aminobutyric acid receptor B signaling drives glioblastoma in females in an immune-dependent manner.

Sex differences in immune responses impact cancer outcomes and treatment response, including in glioblastoma (GBM). However, host factors underlying sex specific immune-cancer interactions are poorly understood. Here, we identify the neurotransmitter γ-aminobutyric acid (GABA) as a driver of GBM-promoting immune response in females.

Identification and bioinformatic characterization of a serum miRNA signature for early detection of laryngeal squamous cell carcinoma.

Background: The growing understanding of cancer biology and the establishment of new treatment modalities has not yielded the expected results in terms of survival for Laryngeal Squamous Cell Cancer (LSCC). Early diagnosis, as well as prompt identification of patients with high risk of relapse would ensure greater chance of therapeutic success. However, this goal remains a challenge due to the absence of specific biomarkers for this neoplasm.

Reinventing gene expression connectivity through regulatory and spatial structural empowerment via principal node aggregation graph neural network.

The intricacies of the human genome, manifested as a complex network of genes, transcend conventional representations in text or numerical matrices. The intricate gene-to-gene relationships inherent in this complexity find a more suitable depiction in graph structures. In the pursuit of predicting gene expression, an endeavor shared by predecessors like the L1000 and Enformer methods, we introduce a novel spatial graph-neural network (GNN) approach.

Mutational landscape of inflammatory breast cancer.

Background: Inflammatory breast cancer (IBC) is the most pro-metastatic form of BC. Better understanding of its enigmatic pathophysiology is crucial. We report here the largest whole-exome sequencing (WES) study of clinical IBC samples.

Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions.

Background: Osteoarthritis (OA) is a multifactorial, hypertrophic, and degenerative condition involving the whole joint and affecting a high percentage of middle-aged people. It is due to a combination of factors, although the pivotal mechanisms underlying the disease are still obscure. Moreover, current treatments are still poorly effective, and patients experience a painful and degenerative disease course.

Epigenetic remodeling to improve the efficacy of immunotherapy in human glioblastoma: pre-clinical evidence for development of new immunotherapy approaches.

Background: Glioblastoma multiforme (GBM) is a highly aggressive primary brain tumor, that is refractory to standard treatment and to immunotherapy with immune-checkpoint inhibitors (ICI). Noteworthy, melanoma brain metastases (MM-BM), that share the same niche as GBM, frequently respond to current ICI therapies. Epigenetic modifications regulate GBM cellular proliferation, invasion, and prognosis and may negatively regulate the cross-talk between malignant cells and immune cells in the tumor milieu, likely contributing to limit the efficacy of ICI therapy of GBM.

MiR-449a antagonizes EMT through IL-6-mediated -signaling in laryngeal squamous cancer.

MicroRNAs (miRNAs) are involved in post-transcriptional gene expression regulation and in mechanisms of cancer growth and metastases. In this light, miRNAs could be promising therapeutic targets and biomarkers in clinical practice. Therefore, we investigated if specific miRNAs and their target genes contribute to laryngeal squamous cell carcinoma (LSCC) development.

Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution.

Tumor deconvolution enables the identification of diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold-standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g.