Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review.

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Case report: PIK3CA somatic mutation leading to Klippel Trenaunay Syndrome and multiple tumors.

We report a case of Klippel Trenaunay Syndrome that was monitored both clinically and molecularly over a period of 9 years. A somatic mosaic mutation of PIK3CA (p(E545G)) was identified using both cfDNA NGS liquid biopsy and tissue biopsy. At the age of 56, due to intervening clonal mutations in PIK3CA background, she developed a squamous cell carcinoma in the right affected leg which was treated surgically. Nine years later, lung bilateral adenocarcinoma arose on PIK3CA mutated tissues supported by different clonal mutations. One year later, the patient died from metastases led by a new FGFR3 clone unresponsive to standard-of-care, immunotherapy-based. Our results highlight the presence of a molecular hallmark underlying neoplastic transformation that occurs upon an angiodysplastic process and support the view that PIK3CA mutated tissues must be treated as precancerous lesions. Importantly, they remark the effectiveness of combining cfDNA NGS liquid and tissue biopsies to monitor disease evolution as well as to identify aggressive clones targetable by tailored therapy, which is more efficient than conventional protocols.

Modeling PCDH19 clustering epilepsy by Neurogenin 2 induction of patient-derived induced pluripotent stem cells.

BACKGROUND: Loss of function mutations in PCDH19 gene causes an X-linked, infant-onset clustering epilepsy, associated with intellectual disability and autistic features. The unique pattern of inheritance includes random X-chromosome inactivation, which leads to pathological tissue mosaicism. Females carrying PCDH19 mutations are affected, while males have a normal phenotype. No cure is presently available for this disease. METHODS: Fibroblasts from a female patient carrying frameshift mutation were reprogrammed into human induced pluripotent stem cells (hiPSCs). To create a cell model of PCDH19-clustering epilepsy (PCDH19-CE) where both cell populations co-exist, we created mosaic neurons by mixing wild-type (WT) and mutated (mut) hiPSC clones, and differentiated them into mature neurons with overexpression of the transcriptional factor Neurogenin 2. RESULTS: We generated functional neurons from patient-derived iPSC using a rapid and efficient method of differentiation through overexpression of Neurogenin 2. Was revealed an accelerated maturation and higher arborisation in the mutated neurons, while the mosaic neurons showed the highest frequency of action potential firing and hyperexcitability features, compared to mutated and WT neurons. CONCLUSIONS: Our findings provide evidence that PCDH19 c.2133delG mutation affects proper metaphases with increased numbers of centrosomes in stem cells and accelerates neuronal maturation in premature cells. PCDH19 mosaic neurons showed elevated excitability, representing the situation in PCDH19-CE brain. We suggest Ngn2 hiPSC-derived PCDH19 neurons as an informative experimental tool for understanding the pathogenesis of PCDH19-CE and a suitable approach for use in targeted drug screening strategies.

Different Liquid Biopsies for the Management of Non-Small Cell Lung Cancer in the Mutational Oncology Era.

In the last ten years, liquid biopsy has been slowly joining the traditional invasive techniques for the diagnosis and monitoring of tumors. Liquid biopsies allow easy repeated sampling of blood, reflect the tumor scenario, and make personalized therapy real for the patient. Liquid biopsies isolate and utilize different substrates present in patients' body fluids such as circulating tumor cells, circulating tumor DNA, tumor extracellular vesicles, etc. One of the most-used solid cancers in the development of the non-invasive liquid biopsy approach that has benefited from scientific advances is non-small cell lung cancer (NSCLC). Using liquid biopsy, it is possible to have more details on NSCLC staging, progression, heterogeneity, gene mutations and clonal evolution, etc., basing the treatment on precision medicine as well as on the screening of markers for therapeutic resistance. With this review, the authors propose a complete and current overview of all different liquid biopsies available to date, to understand how much has been carried out and how much remains to be completed for a better characterization of NSCLC.

Diagnostic accuracy of circulating free DNA testing for the detection of KRAS mutations in non-small cell lung cancer: A systematic review and meta-analysis.

Kirsten rat sarcoma viral oncogene homolog (KRAS) gene encodes a GTPase that acts as a molecular switch for intracellular signal transduction, promoting cell growth and proliferation. Mutations in the KRAS gene represent important biomarkers for NSCLC targeted therapy. However, detection of KRAS mutations in tissues has shown some limitations. During the last years, analyses of circulating free DNA (cfDNA) has emerged as an alternative and minimally invasive, approach to investigate tumor molecular changes. Here, we assessed the diagnostic performance of cfDNA analysis, compared to tissues through a meta-analysis and systematic review of existing literature. From 561 candidate papers, we finally identified 40 studies, including 2,805 NSCLC patients. We extracted values relating to the number of true-positive, false-positive, false-negative, and true-negative. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio, each with 95% CI, were calculated. A summary receiver operating characteristic curve and the area under curve (AUC) were used to evaluate the overall diagnostic performance. The pooled sensitivity was 0.71 (95% CI 0.68-0.74) and the specificity was 0.93 (95% CI 0.92-0.94). The diagnostic odds ratio was 35.24 (95% CI 24.88-49.91) and the area under the curve was 0.92 (SE = 0.094). These results provide evidence that detection of KRAS mutation using cfDNA testing is of adequate diagnostic accuracy thus offering to the clinicians a new promising screening test for NSCLC patients.

Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity.

The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets.

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males.

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways.Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor.

The Phenomenon of Multidrug Resistance in Glioblastomas.

The most common and aggressive brain tumor in the adult population is glioblastoma (GBM). The lifespan of patients does not exceed 22 months. One of the reasons for the low effectiveness of GBM treatment is its radioresistance and chemoresistance. In the current review, we discuss the phenomenon of multidrug resistance of GBM in the context of the expression of ABC family transporter proteins and the mechanisms of proliferation, angiogenesis, and recurrence. We focused on the search of molecular targets among growth factors, receptors, signal transduction proteins, microRNAs, transcription factors, proto-oncogenes, tumor suppressor genes, and their single-nucleotide polymorphisms.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Rare variants in Toll-like receptor 7 results in functional impairment and downregulation of cytokine-mediated signaling in COVID-19 patients.

Toll-like receptors (TLR) are crucial components in the initiation of innate immune responses to a variety of pathogens, triggering the production of pro-inflammatory cytokines and type I and II interferons, which are responsible for innate antiviral responses. Among the different TLRs, TLR7 recognizes several single-stranded RNA viruses including SARS-CoV-2. We and others identified rare loss-of-function variants in X-chromosomal TLR7 in young men with severe COVID-19 and with no prior history of major chronic diseases, that were associated with impaired TLR7 signaling as well as type I and II IFN responses. Here, we performed RNA sequencing to investigate transcriptome variations following imiquimod stimulation of peripheral blood mononuclear cells isolated from patients carrying previously identified hypomorphic, hypofunctional, and loss-of-function TLR7 variants. Our investigation revealed a profound impairment of the TLR7 pathway in patients carrying loss-of-function variants. Of note, a failure in IFNγ upregulation following stimulation was also observed in cells harboring the hypofunctional and hypomorphic variants. We also identified new TLR7 variants in severely affected male patients for which a functional characterization of the TLR7 pathway was performed demonstrating a decrease in mRNA levels in the IFNα, IFNγ, RSAD2, ACOD1, IFIT2, and CXCL10 genes.

SELP Asp603Asn and severe thrombosis in COVID-19 males.

Thromboembolism is a frequent cause of severity and mortality in COVID-19. However, the etiology of this phenomenon is not well understood. A cohort of 1186 subjects, from the GEN-COVID consortium, infected by SARS-CoV-2 with different severity was stratified by sex and adjusted by age. Then, common coding variants from whole exome sequencing were mined by LASSO logistic regression. The homozygosity of the cell adhesion molecule P-selectin gene (SELP) rs6127 (c.1807G > A; p.Asp603Asn) which has been already associated with thrombotic risk is found to be associated with severity in the male subcohort of 513 subjects (odds ratio = 2.27, 95% Confidence Interval 1.54-3.36). As the SELP gene is downregulated by testosterone, the odd ratio is increased in males older than 50 (OR 2.42, 95% CI 1.53-3.82). Asn/Asn homozygotes have increased D-dimers values especially when associated with poly Q ≥ 23 in the androgen receptor (OR 3.26, 95% CI 1.41-7.52). These results provide a rationale for the repurposing of antibodies against P-selectin as adjuvant therapy in rs6127 male homozygotes especially if older than 50 or with an impaired androgen receptor.

C9orf72 Intermediate Repeats Confer Genetic Risk for Severe COVID-19 Pneumonia Independently of Age.

A cytokine storm, autoimmune features and dysfunctions of myeloid cells significantly contribute to severe coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Genetic background of the host seems to be partly responsible for severe phenotype and genes related to innate immune response seem critical host determinants. The C9orf72 gene has a role in vesicular trafficking, autophagy regulation and lysosome functions, is highly expressed in myeloid cells and is involved in immune functions, regulating the lysosomal degradation of mediators of innate immunity. A large non-coding hexanucleotide repeat expansion (HRE) in this gene is the main genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), both characterized by neuroinflammation and high systemic levels of proinflammatory cytokines, while HREs of intermediate length, although rare, are more frequent in autoimmune disorders. C9orf72 full mutation results in haploinsufficiency and intermediate HREs seem to modulate gene expression as well and impair autophagy. Herein, we sought to explore whether intermediate HREs in C9orf72 may be a risk factor for severe COVID-19. Although we found intermediate HREs in only a small portion of 240 patients with severe COVID-19 pneumonia, the magnitude of risk for requiring non-invasive or mechanical ventilation conferred by harboring intermediate repeats >10 units in at least one C9orf72 allele was more than twice respect to having shorter expansions, when adjusted for age (odds ratio (OR) 2.36; 95% confidence interval (CI) 1.04-5.37, p = 0.040). The association between intermediate repeats >10 units and more severe clinical outcome (p = 0.025) was also validated in an independent cohort of 201 SARS-CoV-2 infected patients. These data suggest that C9orf72 HREs >10 units may influence the pathogenic process driving more severe COVID-19 phenotypes.

Severe COVID-19 in Hospitalized Carriers of Single CFTR Pathogenic Variants.

The clinical presentation of COVID-19 is extremely heterogeneous, ranging from asymptomatic to severely ill patients. Thus, host genetic factors may be involved in determining disease presentation and progression. Given that carriers of single cystic fibrosis (CF)-causing variants of the CFTR gene-CF-carriers-are more susceptible to respiratory tract infections, our aim was to determine their likelihood of undergoing severe COVID-19. We implemented a cohort study of 874 individuals diagnosed with COVID-19, during the first pandemic wave in Italy. Whole exome sequencing was performed and validated CF-causing variants were identified. Forty subjects (16 females and 24 males) were found to be CF-carriers. Among mechanically ventilated patients, CF-carriers were more represented (8.7%) and they were significantly (p < 0.05) younger (mean age 51 years) compared to noncarriers (mean age 61.42 years). Furthermore, in the whole cohort, the age of male CF-carriers was lower, compared to noncarriers (p < 0.05). CF-carriers had a relative risk of presenting an abnormal inflammatory response (CRP ≥ 20 mg/dL) of 1.69 (p < 0.05) and their hazard ratio of death at day 14 was 3.10 (p < 0.05) in a multivariate regression model, adjusted for age, sex and comorbidities. In conclusion, CF-carriers are more susceptible to the severe form of COVID-19, showing also higher risk of 14-day death.

Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity.

The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and provides novel insights into the molecular mechanisms of severe disease, leading to new therapeutic targets and sensitive detection of at-risk individuals.