Single-cell landscape of idiopathic multicentric Castleman disease in identical twins.

ABSTRACT: Idiopathic multicentric Castleman disease (iMCD) is a rare cytokine-driven disorder characterized by systemic inflammation, generalized lymphadenopathy, and organ dysfunction. Here, we present an unusual occurrence of iMCD in identical twins and examined the immune milieu within the affected lymphoid organs and the host circulation using multiomic high-dimensional profiling. Using spatial enhanced resolution omics sequencing (Stereo-seq) transcriptomic profiling, we performed unsupervised spatially constrained clustering to identify different anatomic structures, mapping the follicles and interfollicular regions. After a cell segmentation approach, interleukin 6 (IL-6) pathway genes significantly colocalized with endothelial cells and fibroblastic reticular cells, confirming observations using a single-cell sequencing approach (10× Chromium). Furthermore, single-cell sequencing of peripheral blood mononuclear cells revealed an "inflammatory" peripheral monocytosis enriched for the expression of S100A family genes in both twins. In summary, we provided evidence of the putative cell-of-origin of IL-6 signals in iMCD and described a distinct monocytic host immune response phenotype through a unique identical twin model.

Establishment and characterization of a patient-derived solitary fibrous tumor/hemangiopericytoma cell line model.

Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma harboring NAB2-STAT6 gene fusions. Mechanistic studies and therapeutic development on SFT/HPC are impeded by scarcity and lack of system models. In this study, we established and characterized a novel SFT/HPC patient-derived cell line (PDC), SFT-S1, and screened for potential drug candidates that could be repurposed for the treatment of SFT/HPC. Immunohistochemistry profiles of the PDC was consistent with the patient's tumor sample (CD99+/CD34+/desmin-). RNA sequencing, followed by Sanger sequencing confirmed the pathognomonic NAB2exon3-STAT6exon18 fusion in both the PDC and the original tumor. Transcriptomic data showed strong enrichment for oncogenic pathways (epithelial-mesenchymal transition, FGF, EGR1 and TGFß signaling pathways) in the tumor. Whole genome sequencing identified potentially pathogenic somatic variants such as MAGEA10 and ABCA2. Among a panel of 14 targeted agents screened, dasatinib was identified to be the most potent small molecule inhibitor against the PDC (IC50, 473 nM), followed by osimertinib (IC50, 730 nM) and sunitinib (IC50, 1765 nM). Methylation profiling of the tumor suggests that this specific variant of SFT/HPC could lead to genome-wide hypomethylation. In conclusion, we established a novel PDC model of SFT/HPC with comprehensive characterization of its genomic, epigenomic and transcriptomic landscape, which can facilitate future preclinical studies of SFT/HPC, such as in vitro drug screening and in vivo drug testing.

Classification of HER2-negative breast cancers by ERBB2 copy number alteration status reveals molecular differences associated with chromosome 17 gene aberrations.

Background: Recently, HER2-negative breast cancers have been reclassified by protein expression into 'HER2-low' and 'HER2-zero' subgroups, but the consideration of HER2-low breast cancer as a distinct biological subtype with differing prognoses remains controversial. By contrast, non-neutral ERBB2 copy number alteration (CNA) status is associated with inferior survival outcomes compared to ERBB2 CNA-neutral breast cancer, providing an alternative approach to classification. Methods: Here, we investigated the molecular landscape of non-metastatic HER2-negative BCs in relation to ERBB2 CNA status to elucidate biological differences. Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) TCGA-BRCA datasets (n = 1875) were analyzed. Results: Nearly two-fifths of the cohort harbored ERBB2 CNAs (39.4%), which were significantly enriched within hormone receptor-negative (56.1%) than within hormone receptor-positive BCs (35.5%; p < 0.0001). Globally, CNAs across the genome were significantly higher in ERBB2 non-neutral compared to neutral cohorts (p < 0.0001). Notably, genetic aberrations on chromosome 17 - BRCA1, NF1, TP53, MAP2K4, and NCOR1 - were widespread in the ERBB2 non-neutral cases. While chromosome 17q arm-level alterations were largely in tandem with ERBB2 CNA status, arm-level loss in chromosome 17p was prevalent regardless of ERBB2 gain, amplification, or loss. Differential gene expression analysis demonstrated that pathways involved in the cell cycle, proteasome, and DNA replication were upregulated in ERBB2 non-neutral cases. Conclusion: Classification of HER2-negative BCs according to ERBB2 CNA status reveals differences in the genomic landscape. The implications of concurrent aberrations in other genes on chromosome 17 merit further research in ERBB2 non-neutral BCs.

Spatial transcriptomics reveal topological immune landscapes of Asian head and neck angiosarcoma.

Angiosarcomas are rare malignant tumors of the endothelium, arising commonly from the head and neck region (AS-HN) and recently associated with ultraviolet (UV) exposure and human herpesvirus-7 infection. We examined 81 cases of angiosarcomas, including 47 cases of AS-HN, integrating information from whole genome sequencing, gene expression profiling and spatial transcriptomics (10X Visium). In the AS-HN cohort, we observed recurrent somatic mutations in CSMD3 (18%), LRP1B (18%), MUC16 (18%), POT1 (16%) and TP53 (16%). UV-positive AS-HN harbored significantly higher tumor mutation burden than UV-negative cases (p = 0.0294). NanoString profiling identified three clusters with distinct tumor inflammation signature scores (p < 0.001). Spatial transcriptomics revealed topological profiles of the tumor microenvironment, identifying dominant but tumor-excluded inflammatory signals in immune-hot cases and immune foci even in otherwise immune-cold cases. In conclusion, spatial transcriptomics reveal the tumor immune landscape of angiosarcoma, and in combination with multi-omic information, may improve implementation of treatment strategies.

Super-enhancer hypermutation alters oncogene expression in B cell lymphoma.

Diffuse large B cell lymphoma (DLBCL) is the most common B cell non-Hodgkin lymphoma and remains incurable in around 40% of patients. Efforts to sequence the coding genome identified several genes and pathways that are altered in this disease, including potential therapeutic targets1-5. However, the non-coding genome of DLBCL remains largely unexplored. Here we show that active super-enhancers are highly and specifically hypermutated in 92% of samples from individuals with DLBCL, display signatures of activation-induced cytidine deaminase activity, and are linked to genes that encode B cell developmental regulators and oncogenes. As evidence of oncogenic relevance, we show that the hypermutated super-enhancers linked to the BCL6, BCL2 and CXCR4 proto-oncogenes prevent the binding and transcriptional downregulation of the corresponding target gene by transcriptional repressors, including BLIMP1 (targeting BCL6) and the steroid receptor NR3C1 (targeting BCL2 and CXCR4). Genetic correction of selected mutations restored repressor DNA binding, downregulated target gene expression and led to the counter-selection of cells containing corrected alleles, indicating an oncogenic dependency on the super-enhancer mutations. This pervasive super-enhancer mutational mechanism reveals a major set of genetic lesions deregulating gene expression, which expands the involvement of known oncogenes in DLBCL pathogenesis and identifies new deregulated gene targets of therapeutic relevance.

The Multi-Dimensional Biomarker Landscape in Cancer Immunotherapy.

The field of immuno-oncology is now at the forefront of cancer care and is rapidly evolving. The immune checkpoint blockade has been demonstrated to restore antitumor responses in several cancer types. However, durable responses can be observed only in a subset of patients, highlighting the importance of investigating the tumor microenvironment (TME) and cellular heterogeneity to define the phenotypes that contribute to resistance as opposed to those that confer susceptibility to immune surveillance and immunotherapy. In this review, we summarize how some of the most widely used conventional technologies and biomarkers may be useful for the purpose of predicting immunotherapy outcomes in patients, and discuss their shortcomings. We also provide an overview of how emerging single-cell spatial omics may be applied to further advance our understanding of the interactions within the TME, and how these technologies help to deliver important new insights into biomarker discovery to improve the prediction of patient response.

Ligand-mediated PAI-1 inhibition in a mouse model of peritoneal carcinomatosis.

Peritoneal carcinomatosis (PC) present a ubiquitous clinical conundrum in all intra-abdominal malignancies. Via functional and transcriptomic experiments of ascites-treated PC cells, we identify STAT3 as a key signaling pathway. Integrative analysis of publicly available databases and correlation with clinical cohorts (n = 7,359) reveal putative clinically significant activating ligands of STAT3 signaling. We further validate a 3-biomarker prognostic panel in ascites independent of clinical covariates in a prospective study (n = 149). Via single-cell sequencing experiments, we uncover that PAI-1, a key component of the prognostic biomarker panel, is largely secreted by fibroblasts and mesothelial cells. Molecular stratification of ascites using PAI-1 levels and STAT3 activation in ascites-treated cells highlight a therapeutic opportunity based on a phenomenon of paracrine addiction. These results are recapitulated in patient-derived ascites-dependent xenografts. Here, we demonstrate therapeutic proof of concept of direct ligand inhibition of a prognostic target within an enclosed biological space.

Multiregion sequencing of sarcomatoid renal cell carcinoma arising from autosomal dominant polycystic kidney disease.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is an inherited cystic kidney disease associated with a spectrum of various renal and extrarenal manifestations, including increased risk of kidney cancers. Here, we present the initial molecular description of sarcomatoid renal cell carcinoma (sRCC) arising in the setting of ADPKD. METHODS: Multiregion whole-exome sequencing and whole transcriptomic sequencing were used to examine intratumoral molecular heterogeneity among histologically-distinct spindle (sarcomatoid), epithelioid, or biphasic compartments within the tumor and compared with the non-malignant ADPKD component. RESULTS: Spindle and biphasic components harbored several overlapping driver gene mutations, but do not share any with the epithelioid component. Mutations in ATM, CTNNB1, and NF2 were present only in the biphasic and spindle components, while mutations in BID, FLT3, ARID1B, and SMARCA2 were present only in the epithelioid component. We observed dichotomous evolutionary pathways in the development of epithelioid and spindle compartments, involving early mutations in TP53 and ATM/CTNNB1/NF2 respectively. Wnt, PI3K-mTOR, and MAPK signaling pathways, known key mechanisms involved in ADPKD development, featured prominently in the sarcomatoid component. CONCLUSION: This highlights that common pro-oncogenic signals are present between ADPKD and sRCC providing insights into their shared pathobiology.

A Tumor Suppressor Enhancer of PTEN in T-cell development and leukemia.

Long-range oncogenic enhancers play an important role in cancer. Yet, whether similar regulation of tumor suppressor genes is relevant remains unclear. Loss of expression of PTEN is associated with the pathogenesis of various cancers, including T-cell leukemia (T-ALL). Here, we identify a highly conserved distal enhancer (PE) that interacts with the PTEN promoter in multiple hematopoietic populations, including T-cells, and acts as a hub of relevant transcription factors in T-ALL. Consistently, loss of PE leads to reduced PTEN levels in T-ALL cells. Moreover, PE-null mice show reduced Pten levels in thymocytes and accelerated development of NOTCH1-induced T-ALL. Furthermore, secondary loss of PE in established leukemias leads to accelerated progression and a gene expression signature driven by Pten loss. Finally, we uncovered recurrent deletions encompassing PE in T-ALL, which are associated with decreased PTEN levels. Altogether, our results identify PE as the first long-range tumor suppressor enhancer directly implicated in cancer.

Integrated Mobile Element Scanning (ME-Scan) method for identifying multiple types of polymorphic mobile element insertions.

BACKGROUND: Mobile elements are ubiquitous components of mammalian genomes and constitute more than half of the human genome. Polymorphic mobile element insertions (pMEIs) are a major source of human genomic variation and are gaining research interest because of their involvement in gene expression regulation, genome integrity, and disease. RESULTS: Building on our previous Mobile Element Scanning (ME-Scan) protocols, we developed an integrated ME-Scan protocol to identify three major active families of human mobile elements, AluYb, L1HS, and SVA. This approach selectively amplifies insertion sites of currently active retrotransposons for Illumina sequencing. By pooling the libraries together, we can identify pMEIs from all three mobile element families in one sequencing run. To demonstrate the utility of the new ME-Scan protocol, we sequenced 12 human parent-offspring trios. Our results showed high sensitivity (> 90%) and accuracy (> 95%) of the protocol for identifying pMEIs in the human genome. In addition, we also tested the feasibility of identifying somatic insertions using the protocol. CONCLUSIONS: The integrated ME-Scan protocol is a cost-effective way to identify novel pMEIs in the human genome. In addition, by developing the protocol to detect three mobile element families, we demonstrate the flexibility of the ME-Scan protocol. We present instructions for the library design, a sequencing protocol, and a computational pipeline for downstream analyses as a complete framework that will allow researchers to easily adapt the ME-Scan protocol to their own projects in other genomes.

Subclonal NT5C2 mutations are associated with poor outcomes after relapse of pediatric acute lymphoblastic leukemia.

Activating mutations in cytosolic 5'-nucleotidase II (NT5C2) are considered to drive relapse formation in acute lymphoblastic leukemia (ALL) by conferring purine analog resistance. To examine the clinical effects of NT5C2 mutations in relapsed ALL, we analyzed NT5C2 in 455 relapsed B-cell precursor ALL patients treated within the ALL-REZ BFM 2002 relapse trial using sequencing and sensitive allele-specific real-time polymerase chain reaction. We detected 110 NT5C2 mutations in 75 (16.5%) of 455 B-cell precursor ALL relapses. Two-thirds of relapses harbored subclonal mutations and only one-third harbored clonal mutations. Event-free survival after relapse was inferior in patients with relapses with clonal and subclonal NT5C2 mutations compared with those without (19% and 25% vs 53%, P < .001). However, subclonal, but not clonal, NT5C2 mutations were associated with reduced event-free survival in multivariable analysis (hazard ratio, 1.89; 95% confidence interval, 1.28-2.69; P = .001) and with an increased rate of nonresponse to relapse treatment (subclonal 32%, clonal 12%, wild type 9%, P < .001). Nevertheless, 27 (82%) of 33 subclonal NT5C2 mutations became undetectable at the time of nonresponse or second relapse, and in 10 (71%) of 14 patients subclonal NT5C2 mutations were undetectable already after relapse induction treatment. These results show that subclonal NT5C2 mutations define relapses associated with high risk of treatment failure in patients and at the same time emphasize that their role in outcome is complex and goes beyond mutant NT5C2 acting as a targetable driver during relapse progression. Sensitive, prospective identification of NT5C2 mutations is warranted to improve the understanding and treatment of this aggressive ALL relapse subtype.

All-FIT: allele-frequency-based imputation of tumor purity from high-depth sequencing data.

SUMMARY: Clinical sequencing aims to identify somatic mutations in cancer cells for accurate diagnosis and treatment. However, most widely used clinical assays lack patient-matched control DNA and additional analysis is needed to distinguish somatic and unfiltered germline variants. Such computational analyses require accurate assessment of tumor cell content in individual specimens. Histological estimates often do not corroborate with results from computational methods that are primarily designed for normal-tumor matched data and can be confounded by genomic heterogeneity and presence of sub-clonal mutations. Allele-frequency-based imputation of tumor (All-FIT) is an iterative weighted least square method to estimate specimen tumor purity based on the allele frequencies of variants detected in high-depth, targeted, clinical sequencing data. Using simulated and clinical data, we demonstrate All-FIT's accuracy and improved performance against leading computational approaches, highlighting the importance of interpreting purity estimates based on expected biology of tumors. AVAILABILITY AND IMPLEMENTATION: Freely available at http://software.khiabanian-lab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Using whole-exome sequencing to investigate the genetic bases of lysosomal storage diseases of unknown etiology.

Lysosomes are membrane-bound, acidic eukaryotic cellular organelles that play important roles in the degradation of macromolecules. Mutations that cause the loss of lysosomal protein function can lead to a group of disorders categorized as the lysosomal storage diseases (LSDs). Suspicion of LSD is frequently based on clinical and pathologic findings, but in some cases, the underlying genetic and biochemical defects remain unknown. Here, we performed whole-exome sequencing (WES) on 14 suspected LSD cases to evaluate the feasibility of using WES for identifying causal mutations. By examining 2,157 candidate genes potentially associated with lysosomal function, we identified eight variants in five genes as candidate disease-causing variants in four individuals. These included both known and novel mutations. Variants were corroborated by targeted sequencing and, when possible, functional assays. In addition, we identified nonsense mutations in two individuals in genes that are not known to have lysosomal function. However, mutations in these genes could have resulted in phenotypes that were diagnosed as LSDs. This study demonstrates that WES can be used to identify causal mutations in suspected LSD cases. We also demonstrate cases where a confounding clinical phenotype may potentially reflect more than one lysosomal protein defect.

Identification of polymorphic SVA retrotransposons using a mobile element scanning method for SVA (ME-Scan-SVA).

BACKGROUND: Mobile element insertions are a major source of human genomic variation. SVA (SINE-R/VNTR/Alu) is the youngest retrotransposon family in the human genome and a number of diseases are known to be caused by SVA insertions. However, inter-individual genomic variations generated by SVA insertions and their impacts have not been studied extensively due to the difficulty in identifying polymorphic SVA insertions. RESULTS: To systematically identify SVA insertions at the population level and assess their genomic impact, we developed a mobile element scanning (ME-Scan) protocol we called ME-Scan-SVA. Using a nested SVA-specific PCR enrichment method, ME-Scan-SVA selectively amplify the 5' end of SVA elements and their flanking genomic regions. To demonstrate the utility of the protocol, we constructed and sequenced a ME-Scan-SVA library of 21 individuals and analyzed the data using a new analysis pipeline designed for the protocol. Overall, the method achieved high SVA-specificity and over >90 % of the sequenced reads are from SVA insertions. The method also had high sensitivity (>90 %) for fixed SVA insertions that contain the SVA-specific primer-binding sites in the reference genome. Using candidate locus selection criteria that are expected to have a 90 % sensitivity, we identified 151 and 29 novel polymorphic SVA candidates under relaxed and stringent cutoffs, respectively (average 12 and 2 per individual). For six polymorphic SVAs that we were able to validate by PCR, the average individual genotype accuracy is 92 %, demonstrating a high accuracy of the computational genotype calling pipeline. CONCLUSIONS: The new approach allows identifying novel SVA insertions using high-throughput sequencing. It is cost-effective and can be applied in large-scale population study. It also can be applied for detecting potential active SVA elements, and somatic SVA retrotransposition events in different tissues or developmental stages.