From a genome-wide screen of RNAi molecules against SARS-CoV-2 to a validated broad-spectrum and potent prophylaxis.

Expanding the arsenal of prophylactic approaches against SARS-CoV-2 is of utmost importance, specifically those strategies that are resistant to antigenic drift in Spike. Here, we conducted a screen of over 16,000 RNAi triggers against the SARS-CoV-2 genome, using a massively parallel assay to identify hyper-potent siRNAs. We selected Ten candidates for in vitro validation and found five siRNAs that exhibited hyper-potent activity (IC50 < 20 pM) and strong blockade of infectivity in live-virus experiments. We further enhanced this activity by combinatorial pairing of the siRNA candidates and identified cocktails that were active against multiple types of variants of concern (VOC). We then examined over 2,000 possible mutations in the siRNA target sites by using saturation mutagenesis and confirmed broad protection of the leading cocktail against future variants. Finally, we demonstrated that intranasal administration of this siRNA cocktail effectively attenuates clinical signs and viral measures of disease in the gold-standard Syrian hamster model. Our results pave the way for the development of an additional layer of antiviral prophylaxis that is orthogonal to vaccines and monoclonal antibodies.

Genome wide screen of RNAi molecules against SARS-CoV-2 creates a broadly potent prophylaxis.

Expanding the arsenal of prophylactic approaches against SARS-CoV-2 is of utmost importance, specifically those strategies that are resistant to antigenic drift in Spike. Here, we conducted a screen with over 16,000 RNAi triggers against the SARS-CoV-2 genome using a massively parallel assay to identify hyper-potent siRNAs. We selected 10 candidates for in vitro validation and found five siRNAs that exhibited hyper-potent activity with IC50<20pM and strong neutralisation in live virus experiments. We further enhanced the activity by combinatorial pairing of the siRNA candidates to develop siRNA cocktails and found that these cocktails are active against multiple types of variants of concern (VOC). We examined over 2,000 possible mutations to the siRNA target sites using saturation mutagenesis and identified broad protection against future variants. Finally, we demonstrated that intranasal administration of the siRNA cocktail effectively attenuates clinical signs and viral measures of disease in the Syrian hamster model. Our results pave the way to development of an additional layer of antiviral prophylaxis that is orthogonal to vaccines and monoclonal antibodies.

Chromoanagenesis Landscape in 10,000 TCGA Patients.

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor's nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

Expanding cancer predisposition genes with ultra-rare cancer-exclusive human variations.

It is estimated that up to 10% of cancer incidents are attributed to inherited genetic alterations. Despite extensive research, there are still gaps in our understanding of genetic predisposition to cancer. It was theorized that ultra-rare variants partially account for the missing heritable component. We harness the UK BioBank dataset of ~ 500,000 individuals, 14% of which were diagnosed with cancer, to detect ultra-rare, possibly high-penetrance cancer predisposition variants. We report on 115 cancer-exclusive ultra-rare variations and nominate 26 variants with additional independent evidence as cancer predisposition variants. We conclude that population cohorts are valuable source for expanding the collection of novel cancer predisposition genes.

Substantial batch effects in TCGA exome sequences undermine pan-cancer analysis of germline variants.

BACKGROUND: In recent years, research on cancer predisposition germline variants has emerged as a prominent field. The identity of somatic mutations is based on a reliable mapping of the patient germline variants. In addition, the statistics of germline variants frequencies in healthy individuals and cancer patients is the basis for seeking candidates for cancer predisposition genes. The Cancer Genome Atlas (TCGA) is one of the main sources of such data, providing a diverse collection of molecular data including deep sequencing for more than 30 types of cancer from > 10,000 patients. METHODS: Our hypothesis in this study is that whole exome sequences from blood samples of cancer patients are not expected to show systematic differences among cancer types. To test this hypothesis, we analyzed common and rare germline variants across six cancer types, covering 2241 samples from TCGA. In our analysis we accounted for inherent variables in the data including the different variant calling protocols, sequencing platforms, and ethnicity. RESULTS: We report on substantial batch effects in germline variants associated with cancer types. We attribute the effect to the specific sequencing centers that produced the data. Specifically, we measured 30% variability in the number of reported germline variants per sample across sequencing centers. The batch effect is further expressed in nucleotide composition and variant frequencies. Importantly, the batch effect causes substantial differences in germline variant distribution patterns across numerous genes, including prominent cancer predisposition genes such as BRCA1, RET, MAX, and KRAS. For most of known cancer predisposition genes, we found a distinct batch-dependent difference in germline variants. CONCLUSION: TCGA germline data is exposed to strong batch effects with substantial variabilities among TCGA sequencing centers. We claim that those batch effects are consequential for numerous TCGA pan-cancer studies. In particular, these effects may compromise the reliability and the potency to detect new cancer predisposition genes. Furthermore, interpretation of pan-cancer analyses should be revisited in view of the source of the genomic data after accounting for the reported batch effects.

Characteristics of myeloproliferative neoplasms in patients exposed to ionizing radiation following the Chernobyl nuclear accident.

Myeloproliferative neoplasms (MPNs) driver mutations are usually found in JAK2, MPL, and CALR genes; however, 10%-15% of cases are triple negative (TN). A previous study showed lower rate of JAK2 V617F in primary myelofibrosis patients exposed to low doses of ionizing radiation (IR) from Chernobyl accident. To examine distinct driver mutations, we enrolled 281 Ukrainian IR-exposed and unexposed MPN patients. Genomic DNA was obtained from peripheral blood leukocytes. JAK2 V617F, MPL W515, types 1- and 2-like CALR mutations were identified by Sanger Sequencing and real time polymerase chain reaction. Chromosomal alterations were assessed by oligo-SNP microarray platform. Additional genetic variants were identified by whole exome and targeted sequencing. Statistical significance was evaluated by Fisher's exact test and Wilcoxon's rank sum test (R, version 3.4.2). IR-exposed MPN patients exhibited a different genetic profile vs unexposed: lower rate of JAK2 V617F (58.4% vs 75.4%, P = .0077), higher rate of type 1-like CALR mutation (12.2% vs 3.1%, P = .0056), higher rate of TN cases (27.8% vs 16.2%, P = .0366), higher rate of potentially pathogenic sequence variants (mean numbers: 4.8 vs 3.1, P = .0242). Furthermore, we identified several potential drivers specific to IR-exposed TN MPN patients: ATM p.S1691R with copy-neutral loss of heterozygosity at 11q; EZH2 p.D659G at 7q and SUZ12 p.V71 M at 17q with copy number loss. Thus, IR-exposed MPN patients represent a group with distinct genomic characteristics worthy of further study.

Enhancing identification of cancer types via lowly-expressed microRNAs.

The primary function of microRNAs (miRNAs) is to maintain cell homeostasis. In cancerous tissues miRNAs' expression undergo drastic alterations. In this study, we use miRNA expression profiles from The Cancer Genome Atlas of 24 cancer types and 3 healthy tissues, collected from >8500 samples. We seek to classify the cancer's origin and tissue identification using the expression from 1046 reported miRNAs. Despite an apparent uniform appearance of miRNAs among cancerous samples, we recover indispensable information from lowly expressed miRNAs regarding the cancer/tissue types. Multiclass support vector machine classification yields an average recall of 58% in identifying the correct tissue and tumor types. Data discretization had led to substantial improvement, reaching an average recall of 91% (95% median). We propose a straightforward protocol as a crucial step in classifying tumors of unknown primary origin. Our counter-intuitive conclusion is that in almost all cancer types, highly expressing miRNAs mask the significant signal that lower expressed miRNAs provide.