An unbiased lncRNAs dropout CRISPR-Cas9 screen reveals RP11-350G8.5 as a novel therapeutic target for Multiple Myeloma.

Multiple Myeloma (MM) is an incurable malignancy characterised by altered expression of coding and non-coding genes promoting tumour growth and drug resistance. Although the crucial role of long non-coding RNAs (lncRNAs) in MM is clearly established, the function of the non-coding RNAome, which might allow the design of novel therapeutics, is largely unknown. We performed an unbiased CRISPR-Cas9 loss-of-function screen of 671 lncRNAs in MM cells and their Bortezomib (BZB)-resistant derivative. To rank functionally and clinically relevant candidates, we designed and used a bioinformatic prioritisation pipeline combining functional data from cellular screens with prognostic and transcriptional data from MM patients. With this approach, we unveiled and prioritised 8 onco-lncRNAs essential for MM cell fitness, associated with high expression and poor prognosis in MM patients. The previously uncharacterised RP11-350G8.5 emerged as the most promising target, irrespective of BZB resistance. We i) demonstrated the anti-tumoral effect obtained by RP11-350G8.5 inhibition in vitro and in vivo; ii) highlighted a modulation of the unfolded protein response and the induction of immunogenic cell death triggered by the RP11-350G8.5 knock-out, via RNA-sequencing and molecular studies; iii) characterised its cytoplasmic homing through RNA-FISH; iv) predicted its 2D structure and identified 2 G-quadruplex and 3 hairpin-forming regions by biophysical assays, including Thioflavin T, 1H-NMR and circular dichroism to pave the way to the development of novel targeted therapeutics. Overall we provided innovative insights about unexplored lncRNAs in MM and identified RP11-350G8.5 as an oncogenic target for treatment-naïve and BZB-resistant MM patients.

Benchmark Software and Data for Evaluating CRISPR-Cas9 Experimental Pipelines Through the Assessment of a Calibration Screen.

Genome-wide genetic screens using CRISPR-guide RNA libraries are widely performed in mammalian cells to functionally characterize individual genes and for the discovery of new anticancer therapeutic targets. As the effectiveness of such powerful and precise tools for cancer pharmacogenomics is emerging, tools and methods for their quality assessment are becoming increasingly necessary. Here, we provide an R package and a high-quality reference data set for the assessment of novel experimental pipelines through which a single calibration experiment has been executed: a screen of the HT-29 human colorectal cancer cell line with a commercially available genome-wide library of single-guide RNAs. This package and data allow experimental researchers to benchmark their screens and produce a quality-control report, encompassing several quality and validation metrics. The R code used for processing the reference data set, for its quality assessment, as well as to evaluate the quality of a user-provided screen, and to reproduce the figures presented in this article is available at https://github.com/DepMap-Analytics/HT29benchmark. The reference data is publicly available on FigShare.

Impact of morphological features and chemical composition of tendon biomimetic scaffolds on immune recognition via Toll-like receptors.

Tendinopathies are a major worldwide clinical problem. The development of tendon biomimetic scaffolds is considered a promising, therapeutic approach. However, to be clinically effective, scaffolds should avoid immunological recognition. It has been well described that scaffolds composed of aligned fibers lead to a better tenocyte differentiation, vitality, proliferation and motility. However, little has been studied regarding the impact of fiber spatial distribution on the recognition by immune cells. Additionally, it has been suggested that higher hydrophilicity would reduce their immune recognition. Herein, polycaprolactone (PCL)-hyaluronic acid (HA)-based electrospun scaffolds were generated with different fiber diameters (in the nano- and micro-scales) and orientations as well as different grades of wettability and the impact of these properties on immunological recognition has been assessed, by means of Toll-like receptor (TLR) reporter cells. Our results showed that TLR 2/1 and TLR 2/6 were not triggered by the scaffolds. In addition, the TLR 4 signalling pathway seems to be triggered to a greater extent by higher PCL and HA concentrations, but the alignment of the fibers prevents the triggering of this receptor. Taken together, TLR reporter cells were shown to be a useful and effective tool to study the potential of scaffolds to induce immune responses and the results obtained can be used to inform the design of fibrous scaffolds for tendon repair.

A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data.

BACKGROUND: CRISPR-Cas9 dropout screens are formidable tools for investigating biology with unprecedented precision and scale. However, biases in data lead to potential confounding effects on interpretation and compromise overall quality. The activity of Cas9 is influenced by structural features of the target site, including copy number amplifications (CN bias). More worryingly, proximal targeted loci tend to generate similar gene-independent responses to CRISPR-Cas9 targeting (proximity bias), possibly due to Cas9-induced whole chromosome-arm truncations or other genomic structural features and different chromatin accessibility levels. RESULTS: We benchmarked eight computational methods, rigorously evaluating their ability to reduce both CN and proximity bias in the two largest publicly available cell-line-based CRISPR-Cas9 screens to date. We also evaluated the capability of each method to preserve data quality and heterogeneity by assessing the extent to which the processed data allows accurate detection of true positive essential genes, established oncogenetic addictions, and known/novel biomarkers of cancer dependency. Our analysis sheds light on the ability of each method to correct biases under different scenarios. AC-Chronos outperforms other methods in correcting both CN and proximity biases when jointly processing multiple screens of models with available CN information, whereas CRISPRcleanR is the top performing method for individual screens or when CN information is not available. In addition, Chronos and AC-Chronos yield a final dataset better able to recapitulate known sets of essential and non-essential genes. CONCLUSIONS: Overall, our investigation provides guidance for the selection of the most appropriate bias-correction method, based on its strengths, weaknesses and experimental settings.

The role of a mindful movement-based program (Movimento Biologico) in health promotion: results of a pre-post intervention study.

Introduction: Mindful movement is a comprehensive approach that integrates various bodily, emotional and cognitive aspects into physical activity, promoting overall well-being. This study assessed the impact of a mindful movement program, known as Movimento Biologico (MB), on participants psychological well-being (PWB), positive mental health (PMH), sense of coherence (SOC), and interoceptive awareness. Methods: MB program was conducted for students attending the bachelor's degree in Kinesiology and Sport Sciences of University of Perugia over 8 weeks (from October 16 to November 27, 2022). Participants were requested to fill in four questionnaires before and after the MB program: (1) 18-item PWB scale; (2) 9-item PMH scale; (3) 13-item SOC scale; (4) 32-item scale for Multidimensional Assessment of Interoceptive Awareness (MAIA). Wilcoxon signed-rank tests were used to assess changes, with significance set at p < 0.05. Results: Thirty-eight students (mean age 21.2, 60.5% male) participated. Several MAIA subscales, including noticing (p = 0.003), attention management (p = 0.002), emotional awareness (p = 0.007), self-regulation (p < 0.001), body listening (p = 0.001), and trusting (p = 0.001), showed significant improvements. PMH increased significantly (p = 0.015), and there was a significant enhancement in the autonomy subscale of PWB (p = 0.036). SOC and overall PWB also improved, though not significantly. Conclusion: The MB program significantly improved participants' positive mental health and interoceptive awareness. This likely resulted from better recognition and management of positive physiological sensations, a stronger link between physical sensations and emotions, enhanced confidence in one's body, and increased autonomy.

A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization.

Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

Distinct genetic liability profiles define clinically relevant patient strata across common diseases.

Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.