Host nasopharyngeal transcriptome dataset of a SARS-CoV-2 positive Italian cohort.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 has affected millions of people worldwide and has significant implications for public health. Host transcriptomics profiling provides comprehensive understanding of how the virus interacts with host cells and how the host responds to the virus. COVID-19 disease alters the host transcriptome, affecting cellular pathways and key molecular functions. To contribute to the global effort to understand the virus's effect on host cell transcriptome, we have generated a dataset from nasopharyngeal swabs of 35 individuals infected with SARS-CoV-2 from the Campania region in Italy during the three outbreaks, with different clinical conditions. This dataset will help to elucidate the complex interactions among genes and can be useful in the development of effective therapeutic pathways.

Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management.

In the complex and articulated machinery of the human genome, less than 2% of the transcriptome encodes for proteins, while at least 75% is actively transcribed into non-coding RNAs (ncRNAs). Among the non-coding transcripts, those ≥200 nucleotides long (lncRNAs) are receiving growing attention for their involvement in human diseases, particularly cancer. Genomic studies have revealed the multiplicity of processes, including neoplastic transformation and tumor progression, in which lncRNAs are involved by regulating gene expression at epigenetic, transcriptional, and post-transcriptional levels by mechanism(s) that still need to be clarified. In breast cancer, several lncRNAs were identified and demonstrated to have either oncogenic or tumor-suppressive roles. The functional understanding of the mechanisms of lncRNA action in this disease could represent a potential for translational applications, as these molecules may serve as novel biomarkers of clinical use and potential therapeutic targets. This review highlights the relationship between lncRNAs and the principal hallmark of the luminal breast cancer phenotype, estrogen receptor α (ERα), providing an overview of new potential ways to inhibit estrogenic signaling via this nuclear receptor toward escaping resistance to endocrine therapy.

Transcriptomic profiling of calcified aortic valves in clonal hematopoiesis of indeterminate potential carriers.

Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by the presence of clones of mutated blood cells without overt blood diseases. In the last few years, it has emerged that CHIP is associated with atherosclerosis and coronary calcification and that it is an independent determinant of cardiovascular mortality. Recently, CHIP has been found to occur frequently in patients with calcific aortic valve disease (CAVD) and it is associated with a poor prognosis after valve replacement. We assessed the frequency of CHIP by DNA sequencing in the blood cells of 168 CAVD patients undergoing surgical aortic valve replacement or transcatheter aortic valve implantation and investigated the effect of CHIP on 12 months survival. To investigate the pathological process of CAVD in CHIP carriers, we compared by RNA-Seq the aortic valve transcriptome of patients with or without CHIP and non-calcific controls. Transcriptomics data were validated by immunohistochemistry on formalin-embedded aortic valve samples. We confirm that CHIP is common in CAVD patients and that its presence is associated with higher mortality following valve replacement. Additionally, we show, for the first time, that CHIP is often accompanied by a broad cellular and humoral immune response in the explanted aortic valve. Our results suggest that an excessive inflammatory response in CHIP patients may be related to the onset and/or progression of CAVD and point to B cells as possible new effectors of CHIP-induced inflammation.

Combinatorial targeting of menin and the histone methyltransferase DOT1L as a novel therapeutic strategy for treatment of chemotherapy-resistant ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is characterized by a low response rate and high frequency of resistance development to currently available treatments. The therapeutic potential of histone methyltransferase DOT1L inhibitor in OC cells has been demonstrated, but optimal efficacy and safety of this targeted therapy approach still require improvement. We set forth to evaluate if this problem can be overcome by combinatorial targeting of this epigenetic modifier and menin, one of its functional partners in chromatin. METHODS: siRNA-mediated gene knock-down and pharmacological inhibition of menin, a key component of the MLL/SET1 complex and a fitness gene in OC cells, coupled to cell proliferation assays on a panel of high grade serous OC cell lines, including chemotherapy-sensitive and -resistant clones, were applied in order to evaluate how depletion or blockade of this enzyme influences growth and viability of OC cells. RNA sequencing was applied to identify menin target genes and pathways, and the effects of combined inhibition of menin and DOT1L on growth and transcriptome of these OC models were evaluated. RESULTS: Silencing and pharmacological inhibition of menin exert antiproliferative effects in all OC cells tested and, in PEO1 and PEO4 cells, a profound impact on transcriptome via down-regulation of cell cycle regulatory pathways, aryl hydrocarbon receptor, MYC and KRAS signalling. We demonstrated association of menin and DOT1L in OC cells and identified a subset of genes co-regulated by the two factors. Interestingly, co-treatment with DOT1L and menin pharmacological inhibitors exerts an additive effect on growth inhibition on chemotherapy-sensitive and -refractory OC cells mediated by transcriptome changes controlled by menin and DOT1L activities. CONCLUSION: These results indicate that menin functionally cooperates with DOT1L in OC cells modulating transcription of genes involved in key cellular functions including, among others, cell proliferation and survival, that are strongly affected by combined inhibition of these two epigenetic regulators, suggesting that this may represent a novel therapeutic strategy for chemotherapy-resistant OCs. TRIAL REGISTRATION: NA; The manuscript does not contain clinical trials.

Whole-Exome Sequencing Revealed New Candidate Genes for Human Dilated Cardiomyopathy.

Dilated cardiomyopathy (DCM) is a complex disease affecting young adults. It is a pathological condition impairing myocardium activity that leads to heart failure and, in the most severe cases, transplantation, which is currently the only possible therapy for the disease. DCM can be attributed to many genetic determinants interacting with environmental factors, resulting in a highly variable phenotype. Due to this complexity, the early identification of causative gene mutations is an important goal to provide a genetic diagnosis, implement pre-symptomatic interventions, and predict prognosis. The advent of next-generation sequencing (NGS) has opened a new path for mutation screening, and exome sequencing provides a promising approach for identifying causal variants in known genes and novel disease-associated candidates. We analyzed the whole-exome sequencing (WES) of 15 patients affected by DCM without overloading (hypertension, valvular, or congenital heart disease) or chronic ischemic conditions. We identified 70 pathogenic or likely pathogenic variants and 1240 variants of uncertain clinical significance. Gene ontology enrichment analysis was performed to assess the potential connections between affected genes and biological or molecular function, identifying genes directly related to extracellular matrix organization, transcellular movement through the solute carrier and ATP-binding cassette transporter, and vitamin B12 metabolism. We found variants in genes implicated to a different extent in cardiac function that may represent new players in the complex genetic scenario of DCM.

Targeted molecular profiling of epithelial ovarian cancer from Italian BRCA wild-type patients with a BRCA and PARP pathways gene panel.

Ovarian cancer (OC) is the fifth most common type of cancer in women and the fourth most common cause of cancer death in women. Identification of pathogenic variants in OC tissues has an important clinical significance for therapeutic and prevention purposes. This study aims to evaluate the mutational profile of a patient cohort, negative for BRCA1/2 germinal variants and Mismatch Repair defects, using next-generation sequencing (NGS) approach on DNA from formalin-fixed paraffin-embedded samples. We used a custom NGS panel, targeting 34 cancer-related genes, mainly of the BRCA and PARP pathways, and analyzed NGS data to identify somatic and germline variants in Italian patients affected by primary epithelial ovarian cancer. We analyzed 75 epithelial ovarian cancer tissues and identified 54 pathogenic variants and 56 variants of unknown significance. TP53 was characterized by the highest mutational rate, occurring in 55% of tested epithelial ovarian cancers (EOCs). Interestingly, a subset of 8 EOCs showed pathogenic variants of homologous recombination pathway, which could be sensitive to PARP-inhibitor therapies. Germline analysis of actionable genes revealed 4 patients carrier of pathogenic germline variants respectively of RAD51C (2 patients), RAD51D, and PALB2. Molecular profiling of EOCs using our custom NGS panel has enabled the detection of both somatic and germline variants, allowing the selection of patients suitable for targeted therapies, and the identification of high-risk OC families that can benefit from genetic counseling and testing.

Integration of miRNA:mRNA Co-Expression Revealed Crucial Mechanisms Modulated in Immunogenic Cancer Cell Death.

Immunogenic cell death (ICD) in cancer represents a functionally unique therapeutic response that can induce tumor-targeting immune responses. ICD is characterized by the exposure and release of numerous damage-associated molecular patterns (DAMPs), which confer adjuvanticity to dying cancer cells. The spatiotemporally defined emission of DAMPs during ICD has been well described, whereas the epigenetic mechanisms that regulate ICD hallmarks have not yet been deeply elucidated. Here, we aimed to examine the involvement of miRNAs and their putative targets using well-established in vitro models of ICD. To this end, B cell lymphoma (Mino) and breast cancer (MDA-MB-231) cell lines were exposed to two different ICD inducers, the combination of retinoic acid (RA) and interferon-alpha (IFN-α) and doxorubicin, and to non ICD inducers such as gamma irradiation. Then, miRNA and mRNA profiles were studied by next generation sequencing. Co-expression analysis identified 16 miRNAs differentially modulated in cells undergoing ICD. Integrated miRNA-mRNA functional analysis revealed candidate miRNAs, mRNAs, and modulated pathways associated with Immune System Process (GO Term). Specifically, ICD induced a distinctive transcriptional signature hallmarked by regulation of antigen presentation, a crucial step for proper activation of immune system antitumor response. Interestingly, the major histocompatibility complex class I (MHC-I) pathway was upregulated whereas class II (MHC-II) was downregulated. Analysis of MHC-II associated transcripts and HLA-DR surface expression confirmed inhibition of this pathway by ICD on lymphoma cells. miR-4284 and miR-212-3p were the strongest miRNAs upregulated by ICD associated with this event and miR-212-3p overexpression was able to downregulate surface expression of HLA-DR. It is well known that MHC-II expression on tumor cells facilitates the recruitment of CD4+ T cells. However, the interaction between tumor MHC-II and inhibitory coreceptors on tumor-associated lymphocytes could provide an immunosuppressive signal that directly represses effector cytotoxic activity. In this context, MHC-II downregulation by ICD could enhance antitumor immunity. Overall, we found that the miRNA profile was significantly altered during ICD. Several miRNAs are predicted to be involved in the regulation of MHC-I and II pathways, whose implication in ICD is demonstrated herein for the first time, which could eventually modulate tumor recognition and attack by the immune system.

Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor. METHODS: Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy. RESULTS: By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs. CONCLUSIONS: These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.

Combinatorial targeting of a chromatin complex comprising Dot1L, menin and the tyrosine kinase BAZ1B reveals a new therapeutic vulnerability of endocrine therapy-resistant breast cancer.

BACKGROUND: Targeting vulnerabilities of cancer cells by inhibiting key regulators of cell proliferation or survival represents a promising way to overcome resistance to current therapies. In breast cancer (BC), resistance to endocrine therapy results from constitutively active or aberrant estrogen receptor alpha (ERα) signaling to the genome. Targeting components of the ERα pathway in these tumors represents, therefore, a rational way toward effective new treatments. Interaction proteomics identified several proteins associated with ERα in BC cells, including epigenetic complexes controlling gene transcription comprising the scaffold protein menin and the histone methyltransferase Dot1L. METHODS: We combined chromatin immunoprecipitation, transcriptome sequencing, siRNA-mediated gene knockdown (kd), pharmacological inhibition coupled to cellular and functional assays and interaction proteomics in antiestrogen (AE)-sensitive and AE-resistant human BC cell models to: map menin and Dot1L chromatin localization, search for their common and specific target genes, measure the effects of single or combinatorial knockdown or pharmacological inhibition of these proteins on cell proliferation and survival, and characterize their nuclear interactomes. RESULTS: Dot1L and menin associate in MCF-7 cells chromatin, where they co-localize in a significant fraction of sites, resulting in co-regulation of genes involved, among others, in estrogen, p53, HIF1α and death receptor signaling, regulation of cell cycle and epithelial-to-mesenchymal transition. Specific inhibitors of the two factors synergize with each other for inhibition of cell proliferation of AE (tamoxifen or fulvestrant)-sensitive and AE-resistant BC cells. Menin and Dot1L interactomes share a sizeable fraction of their nuclear partners, the majority being known BC fitness genes. Interestingly, these include B-WICH and WINAC complexes that share BAZ1B, a bromodomain protein comprising a tyrosine-protein kinase domain playing a central role in chromatin remodeling and transcriptional regulation. BAZ1B kd caused significant inhibition of ERα expression, proliferation and transcriptome changes resulting in inhibition of estrogen, myc, mTOR, PI3K and AKT signaling and metabolic pathways in AE-sensitive and AE-resistant BC cells. CONCLUSIONS: Identification of a functional interplay between ERα, Dot1L, menin and BAZ1B and the significant effects of their co-inhibition on cell proliferation and survival in cell models of endocrine therapy-resistant BC reveal a new therapeutic vulnerability of these aggressive diseases.

Histone Methyltransferase DOT1L as a Promising Epigenetic Target for Treatment of Solid Tumors.

The histone lysine methyltransferase DOT1L (DOT1-like histone lysine methyltransferase) is responsible for the epigenetic regulation of gene expression through specific methylation of lysine79 residue of histone H3 (H3K79) in actively transcribed genes. Its normal activity is crucial for embryonic development and adult tissues functions, whereas its aberrant functioning is known to contribute to leukemogenesis. DOT1L is the only lysine methyltransferase that does not contain a SET domain, which is a feature that allowed the development of selective DOT1L inhibitors that are currently investigated in Phase I clinical trials for cancer treatment. Recently, abnormal expression of this enzyme has been associated with poor survival and increased aggressiveness of several solid tumors. In this review evidences of aberrant DOT1L expression and activity in breast, ovarian, prostate, colon, and other solid tumors, and its relationships with biological and clinical behavior of the disease and response to therapies, are summarized. Current knowledge of the structural basis of DOT1L ability to regulate cell proliferation, invasion, plasticity and stemness, cell cycle progression, cell-to-cell signaling, epithelial-to-mesenchymal transition, and chemoresistance, through cooperation with several molecular partners including noncoding RNAs, is also reviewed. Finally, available options for the treatment of therapeutically challenging solid tumors by targeting DOT1L are discussed.

Kinship assignment with the ForenSeq™ DNA Signature Prep Kit: Sources of error in simulated and real cases.

Kinship recognition between anonymous DNA samples is becoming a relevant issue in forensics, more so with the increasing number of DNA profiles in databanks. Also, NGS-based genotyping is being increasingly used in routine personal identification, to simultaneously type large numbers of markers of different kind. In the present work, we explored computationally and experimentally the performance of the ForenSeq™ DNA Signature Prep Kit in identifying the true relationship between two anonymous samples, distinguishing it from other possible relationships. We analyzed with Familias R series of 10,000 pairs with 9 different simulated relationships, corresponding to different degrees of autosomal sharing. For each pair we obtained likelihood ratios for five kinship hypotheses vs. unrelatedness, and used their ranking to identify the preferred relationship. We also typed 21 subjects from two pedigrees, representing from parent-child to 4th cousins relationships. As expected, the power for identifying the true relationship decays in the order of autosomal sharing. Parent-child and full siblings can be robustly identified against other relationships. For half-siblings the chance of reaching a significant conclusion is already small. For more distant relationships the proportion of cases correctly and significantly identified is 10% or less. Bidirectional errors in kinship attribution include the suggestion of relatedness when this does not exist (10-50%), and the suggestion of independence in pairs of individuals more than 4 generations apart (25-60%). The real cases revealed a relevant effect of genotype miscalling at some loci, which could only be partly avoided by modulating the analysis parameters. In conclusion, with the exception of first degree relatives, the kit can be useful to inform additional investigations, but does not usually provide probatory results.

Higher Integrin Alpha 3 Beta1 Expression in Papillary Thyroid Cancer Is Associated with Worst Outcome.

Integrins are cell-extracellular matrix adhesion molecules whose expression level undergoes quantitative changes upon neoplastic transformation and are considered functionally related to the development of cancer metastasis. We analyzed the largest mRNA-seq dataset available to determine the expression pattern of integrin family subunits in papillary thyroid carcinomas (PTC). ITGA2, 3, 6, V, and ITGB1 integrin subunits were overexpressed in PTC compared to normal thyroid tissue. The PTC histology variants "classical" and "tall cell" displayed a similar integrin expression profile with a higher level of ITGA3, ITGAV, and ITGB1, which differed from that of the "follicular" variant. Interestingly, compared to RAS mutations, BRAFV600E mutation was associated with a significantly higher expression of integrins. Some integrin subunits were associated with advanced disease stage, lymph node metastasis, extrathyroidal extension, and high-risk groups. Among them, ITGA3 expression displayed the highest correlation with advanced disease and was associated with a negative prognosis. In vitro scratch assay and Matrigel invasion assay in two different PTC cell lines confirmed α3ß1 role in cell motility and invasion, supporting its involvement during tumor progression. These results demonstrate the existence of a PTC-specific integrin expression signature correlated to histopathology, specific driver gene mutations, and aggressiveness of the disease.

HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities): a specific and comprehensive pipeline for metagenomic shotgun sequencing data analysis.

BACKGROUND: Next-Generation-Sequencing (NGS) enables detection of microorganisms present in biological and other matrices of various origin and nature, allowing not only the identification of known phyla and strains but also the discovery of novel ones. The large amount of metagenomic shotgun data produced by NGS require comprehensive and user-friendly pipelines for data analysis, that speed up the bioinformatics steps, relieving the users from the need to manually perform complex and time-consuming tasks. RESULTS: We describe here HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities), an exhaustive pipeline for metagenomics data analysis, comprising three independent analytical modules designed for an inclusive analysis of large NGS datasets. CONCLUSIONS: HOME-BIO is a powerful and easy-to-use tool that can be run also by users with limited computational expertise. It allows in-depth analyses by removing low-complexity/ problematic reads, integrating the analytical steps that lead to a comprehensive taxonomy profile of each sample by querying different source databases, and it is customizable according to specific users' needs.

WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data.

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND ( Workflow for p IRNAs a Nd beyon D), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

Regulation of Metabolic Reprogramming by Long Non-Coding RNAs in Cancer.

Metabolic reprogramming is a well described hallmark of cancer. Oncogenic stimuli and the microenvironment shape the metabolic phenotype of cancer cells, causing pathological modifications of carbohydrate, amino acid and lipid metabolism that support the uncontrolled growth and proliferation of cancer cells. Conversely, metabolic alterations in cancer can drive changes in genetic programs affecting cell proliferation and differentiation. In recent years, the role of non-coding RNAs in metabolic reprogramming in cancer has been extensively studied. Here, we review this topic, with a focus on glucose, glutamine, and lipid metabolism and point to some evidence that metabolic alterations occurring in cancer can drive changes in non-coding RNA expression, thus adding an additional level of complexity in the relationship between metabolism and genetic programs in cancer cells.

Metabolic Regulation of Epigenetic Modifications and Cell Differentiation in Cancer.

Metabolic reprogramming is a hallmark of cancer, with consistent rewiring of glucose, glutamine, and mitochondrial metabolism. While these metabolic alterations are adequate to meet the metabolic needs of cell growth and proliferation, the changes in critical metabolites have also consequences for the regulation of the cell differentiation state. Cancer evolution is characterized by progression towards a poorly differentiated, stem-like phenotype, and epigenetic modulation of the chromatin structure is an important prerequisite for the maintenance of an undifferentiated state by repression of lineage-specific genes. Epigenetic modifiers depend on intermediates of cellular metabolism both as substrates and as co-factors. Therefore, the metabolic reprogramming that occurs in cancer likely plays an important role in the process of the de-differentiation characteristic of the neoplastic process. Here, we review the epigenetic consequences of metabolic reprogramming in cancer, with particular focus on the role of mitochondrial intermediates and hypoxia in the regulation of cellular de-differentiation. We also discuss therapeutic implications.

Identification of Antiestrogen-Bound Estrogen Receptor α Interactomes in Hormone-Responsive Human Breast Cancer Cell Nuclei.

Estrogen receptor alpha (ERα) is a ligand-inducible transcription factor which mediates estrogen actions in hormone-responsive tumors and is targeted by effective anticancer therapies based on the ERα antagonist ligands, selective estrogen receptor modulators (such as Tamoxifen/TAM) or disruptors (such as Fulvestrant/ICI). Despite its importance for cancer therapy, including acquired resistance to endocrine therapy, the molecular basis of ERα response to different ligands is not fully known to date. Interaction proteomics shows great potential to identify and characterize molecular mechanisms of disease based on physical and functional protein-protein interaction networks. Tandem affinity purification coupled to mass spectrometry is applied here for mapping in hormone-responsive breast cancer cells nuclei, the ERα interactomes, induced by each of the two classes of antiestrogens. The results provide new insights on the molecular bases for antiestrogen-mediated control of ERα function and reveal new potential ways to overcome endocrine therapy resistance in cancer.

An Overview of Candidate Therapeutic Target Genes in Ovarian Cancer.

Ovarian cancer (OC) shows the highest mortality rate among gynecological malignancies and, because of the absence of specific symptoms, it is frequently diagnosed at an advanced stage, mainly due to the lack of specific and early biomarkers, such as those based on cancer molecular signature identification. Indeed, although significant progress has been made toward improving the clinical outcome of other cancers, rates of mortality for OC are essentially unchanged since 1980, suggesting the need of new approaches to identify and characterize the molecular mechanisms underlying pathogenesis and progression of these malignancies. In addition, due to the low response rate and the high frequency of resistance to current treatments, emerging therapeutic strategies against OC focus on targeting single factors and pathways specifically involved in tumor growth and metastasis. To date, loss-of-function screenings are extensively applied to identify key drug targets in cancer, seeking for more effective, disease-tailored treatments to overcome lack of response or resistance to current therapies. We review here the information relative to essential genes and functional pathways recently discovered in OC, often strictly interconnected with each other and representing promising biomarkers and molecular targets to treat these malignancies.