The miR-28-5p Targetome Discovery Identified SREBF2 as One of the Mediators of the miR-28-5p Tumor Suppressor Activity in Prostate Cancer Cells

miR-28-5p is downregulated in some tumor tissues in which it has been demonstrated to have tumor suppressor (TS) activity. Here, we demonstrate that miR-28-5p acts as a TS in prostate cancer (PCa) cells affecting cell proliferation/survival, as well as migration and invasion. Using the miRNA pull out assay and next generation sequencing, we collected the complete repertoire of miR-28-5p targets, obtaining a data set (miR-28-5p targetome) of 191 mRNAs. Filtering the targetome with TargetScan 7, PITA and RNA22, we found that 61% of the transcripts had miR-28-5p binding sites. To assign a functional value to the captured transcripts, we grouped the miR-28-5p targets into gene families with annotated function and showed that six transcripts belong to the transcription factor category. Among them we selected SREBF2, a gene with an important role in PCa. We validated miR-28-5p/SREBF2 interaction, demonstrating that SREBF2 inhibition affects almost all the tumor processes altered by miR-28-5p re-expression, suggesting that SREBF2 is an important mediator of miR-28-5p TS activity. Our findings support the identification of the targetome of cancer-related miRNAs as a tool to discover genes and pathways fundamental for tumor development, and potential new targets for anti-tumor therapy

Heterozygosity for Neuronal Ceroid Lipofuscinosis predisposes to Bipolar Disorder

Objective: Bipolar Disorder (BD) is an heritable chronic mental disorder causing psychosocial impairment, affecting patients with depressive/manic episodes. The familial transmission of BD does not follow any of the simple Mendelian patterns of inheritance. The aim of this study is to describe a new large family with twelve affected BD members: WES was performed in eight of them, three of which were diagnosed for BD, and one was reported as a "borderline" individual. Material and methods: WES data allowed us to select variants in common between the affected subjects, once including and once excluding a "borderline" subject with moderate anxiety and traits of obsessive-compulsive disorder. Results: Results were in favor of new predisposing BD genes, electing a heterozygous missense variant in CLN6 resulting in a "borderline" phenotype that if combined with a heterozygous missense variant in ZNF92 is responsible for the more severe BD phenotype. Both rare missense changes are predicted to disrupt the protein function. Conclusions: Loss of both alleles in CLN6 causes Neuronal Ceroid Lipofuscinosis, a severe progressive neurological disorder of childhood. Our results indicate that heterozygous CLN6 carriers, previously reported as healthy, may be susceptible to bipolar disorder late in life if associated with additional variants in ZNF92

MIXER: a Machine-learning method to detect genomic Imbalances exploiting X chromosome exome reads

Whole Exome Sequencing (WES) is rapidly becoming a first-tier test, thanks to declining costs and automatic clinical pipelines. However, while identification of small variants follows standardized workflows, there is no agreement on methods for detection of Copy Number Variants (CNVs). A plethora of WES-based CNV callers have been developed, each showing good performance towards only a limited range of CNV classes/sizes. As clinical CNVs extend from large rearrangements to single genes, more versatile approaches are needed to be of enhanced diagnostic use

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Simple Summary Metastatic colorectal cancer (mCRC) has high incidence and mortality. Nevertheless, innovative biomarkers have been developed for predicting the response to therapy. We have examined the ability of learning methods to build prognostic and predictive models to predict response to chemotherapy, alone or combined with targeted therapy in mCRC patients, by targeting specific narrative publications. After a literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. We showed that all investigations conducted in this field provided generally promising results in predicting the response to therapy or toxic side-effects, using a meta-analytic approach. We found that radiomics and molecular biomarker signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Our study supports the use of computer science for developing personalized treatment decision processes for mCRC patients. Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80-0.95 and 0.83, 95% C.I. 0.74-0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set

CNVScan: detecting borderline copy number variations in NGS data via scan statistics

In this paper we propose CNVScan, a CNV detection method based on scan statistics that overcomes limitations of previous read count (RC) based approaches mainly by being a window-less approach. The scans statistics have been used before mainly in epidemiology and ecology studies, but never before was applied to the CNV detection problem to the best of our knowledge. Since we avoid windowing we do not have to choose an optimal window-size which is a key step in many previous approaches. Extensive simulated experiments with single read data in extreme situations (low coverage, short reads, homo/heterozygoticity) show that this approach is very effective for a range of small CNV (200-500 bp) for which previous state-of-the-art methods are not suitable

Recombinant human cytomegalovirus (HCMV) RL13 binds human immunoglobulin G Fc.

The human cytomegalovirus (HCMV) protein RL13 has recently been described to be present in all primary isolates but rapidly mutated in culture adapted viruses. Although these data suggest a crucial role for this gene product in HCMV primary infection, no function has so far been assigned to this protein. Working with RL13 expressed in isolation in transfected human epithelial cells, we demonstrated that recombinant RL13 from the clinical HCMV isolates TR and Merlin have selective human immunoglobulin (Ig)-binding properties towards IgG1 and IgG2 subtypes. An additional Fc binding protein, RL12, was also identified as an IgG1 and IgG2 binding protein but not further characterized. The glycoprotein RL13 trafficked to the plasma membrane where it bound and internalized exogenous IgG or its constant fragment (Fcγ). Analysis of RL13 ectodomain mutants suggested that the RL13 Ig-like domain is responsible for the Fc binding activity. Ligand-dependent internalization relied on a YxxL endocytic motif located in the C-terminal tail of RL13. Additionally, we showed that the tyrosine residue could be replaced by phenylalanine but not by alanine, indicating that the internalization signal was independent from phosphorylation events. In sum, RL13 binds human IgG and may contribute to HCMV immune evasion in the infected host, but this function does not readily explain the instability of the RL13 gene during viral propagation in cultured cells

RL13 C-terminal YxxL motif is required for internalization.

<p><b>A</b>: Local multiple sequence alignment of the RL13 C-terminus. The gray box indicates the transmembrane domain, the black box the YxxL internalization motif. Darker color indicates higher conservation. Asterisks (*) below the alignments represent conserved amino acid in all sequences; colons (:) represent residues with similar physicochemical properties; dots (.) semi-conserved residues. <b>B</b>: Graphical representation of RL13 mutations used in this study. RL13 TR cytoplasmic tail sequence is shown with mutated amino acids in bold. Amino acids unchanged from the wild-type sequence are represented by a dot. Deleted amino acids are represented by a |. <b>C</b>: Internalization efficiency of RL13 variants. HEK293T cells were transfected with the indicated plasmids coding for wild type and mutated RL13. 48 h post-transfection, cells were detached and incubated on ice for 60 min with human Fcγ fragment. Cells were then washed and incubated in medium at 37°C for 30 min to allow for endocytosis (T37). The control sample remained on ice (T0). Following incubation, cells were cooled quickly by rinsing twice with cold PBS; Fcγ that remained on the cell surface after endocytosis was stained with Alexa Fluor 647-conjugated goat anti-human IgG and analyzed by flow cytometry. The % of internalization was calculated from the mean fluorescence intensities of transfected cells with the following formula: (T0–T37)/T0×100%. Value retrieved from RL13 wild type was set to 100%. Values are the mean and range of three independent experiments. Significant differences, <i>P</i><0,001 (two-tailed unpaired Student's t-test), compared to RL13 are indicated by *.</p