High temporal resolution RNA-seq time course data reveals widespread synchronous activation between mammalian lncRNAs and neighboring protein-coding genes.

The advent of massively parallel sequencing revealed extensive transcription beyond protein-coding genes, identifying tens of thousands of long noncoding RNAs (lncRNAs). Selected functional examples raised the possibility that lncRNAs, as a class, may maintain broad regulatory roles. Expression of lncRNAs is strongly linked with adjacent protein-coding gene expression, suggesting potential cis-regulatory functions. A more detailed understanding of these regulatory roles may be obtained through careful examination of the precise timing of lncRNA expression relative to adjacent protein-coding genes. Despite the diversity of reported lncRNA regulatory mechanisms, where causal cis-regulatory relationships exist, lncRNA transcription is expected to precede changes in target gene expression. Using a high temporal resolution RNA-seq time course, we profiled the expression dynamics of several thousand lncRNAs and protein-coding genes in synchronized, transitioning human cells. Our findings reveal that lncRNAs are expressed synchronously with adjacent protein-coding genes. Analysis of lipopolysaccharide-activated mouse dendritic cells revealed the same temporal relationship observed in transitioning human cells. Our findings suggest broad-scale cis-regulatory roles for lncRNAs are not common. The strong association between lncRNAs and adjacent genes may instead indicate an origin as transcriptional by-products from active protein-coding gene promoters and enhancers.

Measurable residual disease analysis in paediatric acute lymphoblastic leukaemia patients with ABL-class fusions.

BACKGROUND: ABL-class fusions including NUP214-ABL1 and EBF1-PDGFRB occur in high risk acute lymphoblastic leukaemia (ALL) with gene expression patterns similar to BCR-ABL-positive ALL. Our aim was to evaluate new DNA-based measurable residual disease (MRD) tests detecting these fusions and IKZF1-deletions in comparison with conventional immunoglobulin/T-cell receptor (Ig/TCR) markers. METHODS: Precise genomic breakpoints were defined from targeted or whole genome next generation sequencing for ABL-fusions and BCR-ABL1. Quantitative PCR assays were designed and used to re-measure MRD in remission bone marrow samples previously tested using Ig/TCR markers. All MRD testing complied with EuroMRD guidelines. RESULTS: ABL-class patients had 46% 5year event-free survival and 79% 5year overall survival. All had sensitive fusion tests giving high concordance between Ig/TCR and ABL-class fusion results (21 patients, n = 257 samples, r2 = 0.9786, P < 0.0001) and Ig/TCR and IKZF1-deletion results (9 patients, n = 143 samples, r2 = 0.9661, P < 0.0001). In contrast, in BCR-ABL1 patients, Ig/TCR and BCR-ABL1 tests were discordant in 32% (40 patients, n = 346 samples, r2 = 0.4703, P < 0.0001) and IKZF1-deletion results were closer to Ig/TCR (25 patients, n = 176, r2 = 0.8631, P < 0.0001). CONCLUSIONS: MRD monitoring based on patient-specific assays detecting gene fusions or recurrent assays for IKZF1-deletions is feasible and provides good alternatives to Ig/TCR tests to monitor MRD in ABL-class ALL.

Monitoring of childhood ALL using BCR-ABL1 genomic breakpoints identifies a subgroup with CML-like biology.

We used the genomic breakpoint between BCR and ABL1 genes for the DNA-based monitoring of minimal residual disease (MRD) in 48 patients with childhood acute lymphoblastic leukemia (ALL). Comparing the results with standard MRD monitoring based on immunoglobulin/T-cell receptor (Ig/TCR) gene rearrangements and with quantification of IKZF1 deletion, we observed very good correlation for the methods in a majority of patients; however, >20% of children (25% [8/32] with minor and 12.5% [1/8] with major-BCR-ABL1 variants in the consecutive cohorts) had significantly (>1 log) higher levels of BCR-ABL1 fusion than Ig/TCR rearrangements and/or IKZF1 deletion. We performed cell sorting of the diagnostic material and assessed the frequency of BCR-ABL1-positive cells in various hematopoietic subpopulations; 12% to 83% of non-ALL B lymphocytes, T cells, and/or myeloid cells harbored the BCR-ABL1 fusion in patients with discrepant MRD results. The multilineage involvement of the BCR-ABL1-positive clone demonstrates that in some patients diagnosed with BCR-ABL1-positive ALL, a multipotent hematopoietic progenitor is affected by the BCR-ABL1 fusion. These patients have BCR-ABL1-positive clonal hematopoiesis resembling a chronic myeloid leukemia (CML)-like disease manifesting in "lymphoid blast crisis." The biological heterogeneity of BCR-ABL1-positive ALL may impact the patient outcomes and optimal treatment (early stem cell transplantation vs long-term administration of tyrosine-kinase inhibitors) as well as on MRD testing. Therefore, we recommend further investigations on CML-like BCR-ABL1-positive ALL.

Deciphering cancer cell state plasticity with single-cell genomics and artificial intelligence.

Cancer stem cell plasticity refers to the ability of tumour cells to dynamically switch between states-for example, from cancer stem cells to non-cancer stem cell states. Governed by regulatory processes, cells transition through a continuum, with this transition space often referred to as a cell state landscape. Plasticity in cancer cell states leads to divergent biological behaviours, with certain cell states, or state transitions, responsible for tumour progression and therapeutic response. The advent of single-cell assays means these features can now be measured for individual cancer cells and at scale. However, the high dimensionality of this data, complex relationships between genomic features, and a lack of precise knowledge of the genomic profiles defining cancer cell states have opened the door for artificial intelligence methods for depicting cancer cell state landscapes. The contribution of cell state plasticity to cancer phenotypes such as treatment resistance, metastasis, and dormancy has been masked by analysis of 'bulk' genomic data-constituted of the average signal from millions of cells. Single-cell technologies solve this problem by producing a high-dimensional cellular landscape of the tumour ecosystem, quantifying the genomic profiles of individual cells, and creating a more detailed model to investigate cancer plasticity (Genome Res 31:1719, 2021; Semin Cancer Biol 53: 48-58, 2018; Signal Transduct Target Ther 5:1-36, 2020). In conjunction, rapid development in artificial intelligence methods has led to numerous tools that can be employed to study cancer cell plasticity.

TNFAIP3 Reduction-of-Function Drives Female Infertility and CNS Inflammation.

Women with autoimmune and inflammatory aetiologies can exhibit reduced fecundity. TNFAIP3 is a master negative regulator of inflammation, and has been linked to many inflammatory conditions by genome wide associations studies, however its role in fertility remains unknown. Here we show that mice harbouring a mild Tnfaip3 reduction-of-function coding variant (Tnfaip3I325N) that reduces the threshold for inflammatory NF-κB activation, exhibit reduced fecundity. Sub-fertility in Tnfaip3I325N mice is associated with irregular estrous cycling, low numbers of ovarian secondary follicles, impaired mammary gland development and insulin resistance. These pathological features are associated with infertility in human subjects. Transplantation of Tnfaip3I325N ovaries, mammary glands or pancreatic islets into wild-type recipients rescued estrous cycling, mammary branching and hyperinsulinemia respectively, pointing towards a cell-extrinsic hormonal mechanism. Examination of hypothalamic brain sections revealed increased levels of microglial activation with reduced levels of luteinizing hormone. TNFAIP3 coding variants may offer one contributing mechanism for the cause of sub-fertility observed across otherwise healthy populations as well as for the wide variety of auto-inflammatory conditions to which TNFAIP3 is associated. Further, TNFAIP3 represents a molecular mechanism that links heightened immunity with neuronal inflammatory homeostasis. These data also highlight that tuning-up immunity with TNFAIP3 comes with the potentially evolutionary significant trade-off of reduced fertility.

DropletQC: improved identification of empty droplets and damaged cells in single-cell RNA-seq data.

BACKGROUND: Advances in droplet-based single-cell RNA-sequencing (scRNA-seq) have dramatically increased throughput, allowing tens of thousands of cells to be routinely sequenced in a single experiment. In addition to cells, droplets capture cell-free "ambient" RNA predominantly caused by lysis of cells during sample preparation. Samples with high ambient RNA concentration can create challenges in accurately distinguishing cell-containing droplets and droplets containing ambient RNA. Current methods to separate these groups often retain a significant number of droplets that do not contain cells or empty droplets. Additionally, there are currently no methods available to detect droplets containing damaged cells, which comprise partially lysed cells, the original source of the ambient RNA. RESULTS: Here, we describe DropletQC, a new method that is able to detect empty droplets, damaged, and intact cells, and accurately distinguish them from one another. This approach is based on a novel quality control metric, the nuclear fraction, which quantifies for each droplet the fraction of RNA originating from unspliced, nuclear pre-mRNA. We demonstrate how DropletQC provides a powerful extension to existing computational methods for identifying empty droplets such as EmptyDrops. CONCLUSIONS: We implement DropletQC as an R package, which can be easily integrated into existing single-cell analysis workflows.

Differential expression of MUC4, GPR110 and IL2RA defines two groups of CRLF2-rearranged acute lymphoblastic leukemia patients with distinct secondary lesions.

CRLF2-rearrangements (CRLF2-r) occur frequently in Ph-like B-ALL, a high-risk ALL sub-type characterized by a signaling profile similar to Ph + ALL, however accumulating evidence indicates genetic heterogeneity within CRLF2-r ALL. We performed thorough genomic characterization of 35 CRLF2-r cases (P2RY8-CRLF2 n = 18; IGH-CRLF2 n = 17). Activating JAK2 mutations were present in 34% of patients, and a CRLF2-F232C mutation was identified in an additional 17%. IKZF1 deletions were detected in 63% of cases. The majority of patients (26/35) classified as Ph-like, and these were characterized by significantly higher levels of MUC4, GPR110 and IL2RA/CD25. In addition, Ph-like CRLF2-r samples were significantly enriched for IKZF1 deletions, JAK2/CRLF2 mutations and increased expression of JAK/STAT target genes (CISH, SOCS1), suggesting that mutation-driven CRLF2/JAK2 activation is more frequent in this sub-group. Less is known about the genomics of CRLF2-r cases lacking JAK2-pathway mutations, but KRAS/NRAS mutations were identified in 4/9 non-Ph-like samples. This work highlights the heterogeneity of secondary lesions which may arise and influence intracellular-pathway activation in CRLF2-r patients, and importantly presents distinct therapeutic targets within a group of patients harboring identical primary translocations, for whom efficient directed therapies are currently lacking.