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Abstract Follicular lymphoma (FL) exhibits considerable variability in biological features and clinical trajectories across patients. To dissect the diversity of FL, we utilized a Bernoulli mixture model to identify genetic subtypes in 713 pre-treatment tumor tissue samples. Our analysis revealed the existence of five subtypes with unique genetic profiles that correlated with clinicopathological characteristics. The clusters were enriched in specific mutations as follows: CS (CREBBP and STAT6), TT (TNFAIP3 and TP53), GM (GNA13 and MEF2B), Q (quiescent, for low mutation burden), and AR (mutations of mTOR pathway-related genes). The subtype Q was enriched for patients with stage I disease and associated with a lower proliferative history than the other subtypes. The AR subtype was unique in its enrichment for IgM-expressing FL cases and was associated with advanced-stage and more than 4 nodal sites. The existence of subtypes was validated in an independent cohort of 418 samples from the GALLIUM trial. Notably, patients assigned to the TT subtype consistently experienced inferior progression-free survival when treated with immunochemotherapy. Our findings offer insight into core pathways distinctly linked with each FL cluster and are expected to be informative in the era of targeted therapies.

Glioblastoma (GBM) is the most common type of glioma and is uniformly fatal. Currently, tumour heterogeneity and mutation acquisition are major impedances for tailoring personalized therapy. We collected blood and tumour tissue samples from 25 GBM patients and 25 blood samples from healthy controls. Cell‐free DNA (cfDNA) was extracted from the plasma of GBM patients and from healthy controls. Tumour DNA was extracted from fresh tumour samples. Extracted DNA was sequenced using a whole‐genome sequencing procedure. We also collected 180 tumour DNA datasets from GBM patients publicly available at the TCGA/PANCANCER project. These data were analysed for mutations and gene–gene fusions that could be potential druggable targets. We found that plasma cfDNA concentrations in GBM patients were significantly elevated (22.6 ± 5 ng·mL−1), as compared to healthy controls (1.4 ± 0.4 ng·mL−1) of the same average age. We identified unique mutations in the cfDNA and tumour DNA of each GBM patient, including some of the most frequently mutated genes in GBM according to the COSMIC database (TP53, 18.75%; EGFR, 37.5%; NF1, 12.5%; LRP1B, 25%; IRS4, 25%). Using our gene–gene fusion database, ChiTaRS 5.0, we identified gene–gene fusions in cfDNA and tumour DNA, such as KDR–PDGFRA and NCDN–PDGFRA, which correspond to previously reported alterations of PDGFRA in GBM (44% of all samples). Interestingly, the PDGFRA protein fusions can be targeted by tyrosine kinase inhibitors such as imatinib, sunitinib, and sorafenib. Moreover, we identified BCR–ABL1 (in 8% of patients), COL1A1–PDGFB (8%), NIN–PDGFRB (8%), and FGFR1–BCR (4%) in cfDNA of patients, which can be targeted by analogues of imatinib. ROS1 fusions (CEP85L–ROS1 and GOPC–ROS1), identified in 8% of patient cfDNA, might be targeted by crizotinib, entrectinib, or larotrectinib. Thus, our study suggests that integrated analysis of cfDNA plasma concentration, gene mutations, and gene–gene fusions can serve as a diagnostic modality for distinguishing GBM patients who may benefit from targeted therapy. These results open new avenues for precision medicine in GBM, using noninvasive liquid biopsy diagnostics to assess personalized patient profiles. Moreover, repeated detection of druggable targets over the course of the disease may provide real‐time information on the evolving molecular landscape of the tumour.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 infections has quickly developed into a global public health threat. COVID-19 patients show distinct clinical features, and in some cases, during the severe stage of the condition, the disease severity leads to an acute respiratory disorder. In spite of several pieces of research in this area, the molecular mechanisms behind the development of disease severity are still not clearly understood. Recent studies demonstrated that SARS-CoV-2 alters the host cell splicing and transcriptional response to overcome the host immune response that provides the virus with favorable conditions to replicate efficiently within the host cells. In several disease conditions, aberrant splicing could lead to the development of novel chimeric transcripts that could promote the functional alternations of the cell. As severe SARS-CoV-2 infection was reported to cause abnormal splicing in the infected cells, we could expect the generation and expression of novel chimeric transcripts. However, no study so far has attempted to check whether novel chimeric transcripts are expressed in severe SARS-CoV-2 infections. In this study, we analyzed several publicly available blood transcriptome datasets of severe COVID-19, mild COVID-19, other severe respiratory viral infected patients, and healthy individuals. We identified 424 severe COVID-19 -specific chimeric transcripts, 42 of which were recurrent. Further, we detected 189 chimeric transcripts common to severe COVID-19 and multiple severe respiratory viral infections. Pathway and gene enrichment analysis of the parental genes of these two subsets of chimeric transcripts reveals that these are potentially involved in immune-related processes, interferon signaling, and inflammatory responses, which signify their potential association with immune dysfunction leading to the development of disease severity. Our study provides the first detailed expression landscape of chimeric transcripts in severe COVID-19 and other severe respiratory viral infections.

Initial clinical trials and surveillance data have shown that the most commonly administered BNT162b2 COVID-19 mRNA vaccine is effective and safe. However, several cases of mRNA vaccine-induced mild to moderate adverse events were recently reported. Here, we report a rare case of myositis after injection of the first dose of BNT162b2 COVID-19 mRNA vaccine into the left deltoid muscle of a 34-year-old, previously healthy woman who presented progressive proximal muscle weakness, progressive dysphagia, and dyspnea with respiratory failure. One month after vaccination, BNT162b2 vaccine mRNA expression was detected in a tissue biopsy of the right deltoid and quadriceps muscles. We propose this case as a rare example of COVID-19 mRNA vaccine-induced myositis. This study comprehensively characterizes the clinical and molecular features of BNT162b2 mRNA vaccine-associated myositis in which the patient was severely affected.

Soil bacteria respond rapidly to changes in new environmental conditions. For adaptation to the new environment, they could mutate their genome, which impacts the alternation of the functional and regulatory landscape. Sometimes, these genetic and ecological changes may drive the bacterial evolution and sympatric speciation. Although sympatric speciation has been controversial since Darwin suggested it in 1859, there are several strong theoretical or empirical evidences to support it. Sympatric speciation associated with soil bacteria remains largely unexplored. Here, we provide potential evidence of sympatric speciation of soil bacteria by comparison of metagenomics from two sharply contrasting abutting divergence rock and soil types (Senonian chalk and its rendzina soil, and abutting Pleistocene basalt rock and basalt soil). We identified several bacterial species with significant genetic differences in the same species between the two soil types and ecologies. We show that the bacterial community composition has significantly diverged between the two soils; correspondingly, their functions were differentiated in order to adapt to the local ecological stresses. The ecologies, such as water availability and pH value, shaped the adaptation and speciation of soil bacteria revealed by the clear-cut genetic divergence. Furthermore, by a novel analysis scheme of riboswitches, we highlight significant differences in structured non-coding RNAs between the soil bacteria from two divergence soil types, which could be an important driver for functional adaptation. Our study provides new insight into the evolutionary divergence and incipient sympatric speciation of soil bacteria under microclimatic ecological differences.

In cancers and other complex diseases, the fusion of two genes can lead to the production of chimeric RNAs, which are associated with disease development. Several recurrent chimeric RNAs are expressed in different cancers and are thus used for clinical cancer diagnosis. Rheumatoid arthritis (RA) is an immune-mediated joint disorder resulting in synovial inflammation and joint destruction. Despite advances in therapy, many patients do not respond to treatment and present persistent inflammation. Understanding the landscape of chimeric RNA expression in RA patients could provide a better insight into RA pathogenesis, which might provide better treatment strategies and tailored therapies. Accordingly, we analyzed the publicly available RNA-seq data of synovium tissue from 151 RA patients and 28 healthy controls and were able to identify 37 recurrent chimeric RNAs found to be expressed in at least 3 RA samples. Furthermore, the parental genes of these 37 recurrent chimeric RNAs were found to be differentially expressed and enriched in immune-related processes, such as adaptive immune response and the positive regulation of B-cell activation. Interestingly, the appearance of 5 coding and 23 non-coding chimeric RNAs might be associated with regulating their parental gene expression, leading to the generation of dysfunctional immune responses, such as inflammation and bone destruction. Therefore, in this paper, we present the first study to demonstrate the novel chimeric RNAs that are highly expressed and functional in RA.

A new coronavirus infection, COVID-19, has recently emerged, and has caused a global pandemic along with an international public health emergency. Currently, no licensed vaccines are available for COVID-19. The identification of immunodominant epitopes for both B- and T-cells that induce protective responses in the host is crucial for effective vaccine design. Computational prediction of potential epitopes might significantly reduce the time required to screen peptide libraries as part of emergent vaccine design. In our present study, we used an extensive immunoinformatics-based approach to predict conserved immunodominant epitopes from the proteome of SARS-CoV-2. Regions from SARS-CoV-2 protein sequences were defined as immunodominant, based on the following three criteria regarding B- and T-cell epitopes: (i) they were both mapped, (ii) they predicted protective antigens, and (iii) they were completely identical to experimentally validated epitopes of SARS-CoV. Further, structural and molecular docking analyses were performed in order to understand the binding interactions of the identified immunodominant epitopes with human major histocompatibility complexes (MHC). Our study provides a set of potential immunodominant epitopes that could enable the generation of both antibody- and cell-mediated immunity. This could contribute to developing peptide vaccine-based adaptive immunotherapy against SARS-CoV-2 infections and prevent future pandemic outbreaks.