Copynumber: Efficient algorithms for single- and multi-track copy number segmentation

Ductal carcinoma in situ develops within clonal fields of mutant cells in morphologically normal ducts

Mutations are abundantly present in tissues of healthy individuals, including the breast epithelium. Yet it remains unknown whether mutant cells directly induce lesion formation or first spread, leading to a field of mutant cells that is predisposed towards lesion formation. To study the clonal and spatial relationships between morphologically normal breast epithelium adjacent to pre-cancerous lesions, we developed a three-dimensional (3D) imaging pipeline combined with spatially resolved genomics on archival, formalin-fixed breast tissue with the non-obligate breast cancer precursor ductal carcinoma in situ (DCIS). Using this 3D image-guided characterization method, we built high-resolution spatial maps of DNA copy number aberration (CNA) profiles within the DCIS lesion and the surrounding normal mammary ducts. We show that the local heterogeneity within a DCIS lesion is limited. However, by mapping the CNA profiles back onto the 3D reconstructed ductal subtree, we find that in eight out of 16 cases the healthy epithelium adjacent to the DCIS lesions has overlapping structural variations with the CNA profile of the DCIS. Together, our study indicates that pre-malignant breast transformations frequently develop within mutant clonal fields of morphologically normal-looking ducts. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

Paired Primary and Recurrent Rhabdoid Meningiomas: Cytogenetic Alterations, BAP1 Gene Expression Profile and Patient Outcome

Rhabdoid meningiomas (RM) are a rare meningioma subtype with a heterogeneous clinical course which is more frequently associated with recurrence, even among tumors undergoing-complete surgical removal. Here, we retrospectively analyzed the clinical-histopathological and cytogenetic features of 29 tumors, from patients with recurrent (seven primary and 14 recurrent tumors) vs. non-recurrent RM (n = 8). Recurrent RM showed one (29%), two (29%) or three (42%) recurrences. BAP1 loss of expression was found in one third of all RM at diagnosis and increased to 100% in subsequent tumor recurrences. Despite both recurrent and non-recurrent RM shared chromosome 22 losses, non-recurrent tumors more frequently displayed extensive losses of chromosome 19p (62%) and/or 19q (50%), together with gains of chromosomes 20 and 21 (38%, respectively), whereas recurrent RM (at diagnosis) displayed more complex genotypic profiles with extensive losses of chromosomes 1p, 14q, 18p, 18q (67% each) and 21p (50%), together with focal gains at chromosome 17q22 (67%). Compared to paired primary tumors, recurrent RM samples revealed additional losses at chromosomes 16q and 19p (50% each), together with gains at chromosomes 1q and 17q in most recurrent tumors (67%, each). All deceased recurrent RM patients corresponded to women with chromosome 17q gains, although no statistical significant differences were found vs. the other RM patients.

CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics

MOTIVATION

Copy number variations (CNVs) are common genetic alterations in tumour cells. The delineation of CNVs holds promise for enhancing our comprehension of cancer progression. Moreover, accurate inference of CNVs from single-cell sequencing data is essential for unravelling intratumoral heterogeneity. However, existing inference methods face limitations in resolution and sensitivity.

RESULTS

To address these challenges, we present CopyVAE, a deep learning framework based on a variational autoencoder architecture. Through experiments, we demonstrated that CopyVAE can accurately and reliably detect CNVs from data obtained using single-cell RNA sequencing. CopyVAE surpasses existing methods in terms of sensitivity and specificity. We also discussed CopyVAE's potential to advance our understanding of genetic alterations and their impact on disease advancement.

AVAILABILITY AND IMPLEMENTATION

CopyVAE is implemented and freely available under MIT license at https://github.com/kurtsemih/copyVAE.

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer

Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression-methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.

High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue

Somatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we perform multi-region, single-cell DNA sequencing to characterize the SCNA landscape across tumor-rich and normal tissue in two male patients with localized prostate cancer. We identify two distinct karyotypes: 'pseudo-diploid' cells harboring few SCNAs and highly aneuploid cells. Pseudo-diploid cells form numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones. In contrast, aneuploid cells do not form subclones and are detected throughout the prostate, including normal tissue regions. Highly localized pseudo-diploid subclones are confined within tumor-rich regions and carry deletions in multiple tumor-suppressor genes. Our study reveals that SCNAs are widespread in normal and tumor regions across the prostate in localized prostate cancer patients and suggests that a subset of pseudo-diploid cells drive tumorigenesis in the aging prostate.

Single cell analyses of cancer cells identified two regulatorily and functionally distinct categories in differentially expressed genes among tumor subclones

To explore the feature of cancer cells and tumor subclones, we analyzed 101,065 single-cell transcriptomes from 12 colorectal cancer (CRC) patients and 92 single cell genomes from one of these patients. We found cancer cells, endothelial cells and stromal cells in tumor tissue expressed much more genes and had stronger cell-cell interactions than their counterparts in normal tissue. We identified copy number variations (CNVs) in each cancer cell and found correlation between gene copy number and expression level in cancer cells at single cell resolution. Analysis of tumor subclones inferred by CNVs showed accumulation of mutations in each tumor subclone along lineage trajectories. We found differentially expressed genes (DEGs) between tumor subclones had two populations: DEGCNV and DEGreg. DEGCNV, showing high CNV-expression correlation and whose expression differences depend on the differences of CNV level, enriched in housekeeping genes and cell adhesion associated genes. DEGreg, showing low CNV-expression correlation and mainly in low CNV variation regions and regions without CNVs, enriched in cytokine signaling genes. Furthermore, cell-cell communication analyses showed that DEGCNV tends to involve in cell-cell contact while DEGreg tends to involve in secreted signaling, which further support that DEGCNV and DEGreg are two regulatorily and functionally distinct categories.

scCircle-seq unveils the diversity and complexity of extrachromosomal circular DNAs in single cells

Extrachromosomal circular DNAs (eccDNAs) have emerged as important intra-cellular mobile genetic elements that affect gene copy number and exert in trans regulatory roles within the cell nucleus. Here, we describe scCircle-seq, a method for profiling eccDNAs and unraveling their diversity and complexity in single cells. We implement and validate scCircle-seq in normal and cancer cell lines, demonstrating that most eccDNAs vary largely between cells and are stochastically inherited during cell division, although their genomic landscape is cell type-specific and can be used to accurately cluster cells of the same origin. eccDNAs are preferentially produced from chromatin regions enriched in H3K9me3 and H3K27me3 histone marks and are induced during replication stress conditions. Concomitant sequencing of eccDNAs and RNA from the same cell uncovers the absence of correlation between eccDNA copy number and gene expression levels, except for a few oncogenes, including MYC, contained within a large eccDNA in colorectal cancer cells. Lastly, we apply scCircle-seq to one prostate cancer and two breast cancer specimens, revealing cancer-specific eccDNA landscapes and a higher propensity of eccDNAs to form in amplified genomic regions. scCircle-seq is a scalable tool that can be used to dissect the complexity of eccDNAs across different cell and tissue types, and further expands the potential of eccDNAs for cancer diagnostics.

Mesonephric-like adenocarcinoma harbours characteristic copy number variations and a distinct DNA methylation signature closely related to mesonephric adenocarcinoma of the cervix

Mesonephric-like adenocarcinoma (MLA) of the female genital tract is an uncommon histotype that can arise in both the endometrium and the ovary. The exact cell of origin and histogenesis currently remain unknown. Here, we investigated whole genome DNA methylation patterns and copy number variations (CNVs) in a series of MLAs in the context of a large cohort of various gynaecological carcinoma types. CNV analysis of 19 MLAs uncovered gains of chromosomes 1q (18/19, 95%), 10 (15/19, 79%), 12 (14/19, 74%), and 2 (10/19, 53%), as well as loss of chromosome 1p (7/19, 37%). Gains of chromosomes 1q, 10, and 12 were also identified in the majority of mesonephric adenocarcinomas of the uterine cervix (MAs) as well as subsets of endometrioid carcinomas (ECs) and low-grade serous carcinomas of the ovary (LGSCs) but only in a minority of serous carcinomas of the uterine corpus (USCs), clear cell carcinomas (CCCs), and tubo-ovarian high-grade serous carcinomas (HGSCs). While losses of chromosome 1p together with gains of chromosome 1q were also identified in both MA and LGSC, gains of chromosome 2 were almost exclusively identified in MLA and MA. Unsupervised hierarchical clustering and t-SNE analysis of DNA methylation data (Illumina EPIC array) identified a co-clustering for MLAs and MAs, which was distinct from clusters of ECs, USCs, CCCs, LGSCs, and HGSCs. Group-wise comparisons confirmed a close epigenetic relationship between MLA and MA. These findings, in conjunction with the established histological and immunophenotypical overlap, suggest bona fide mesonephric differentiation, and support a more precise terminology of mesonephric-type adenocarcinoma instead of MLA in these tumours. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Emergence of replication timing during early mammalian development

DNA replication enables genetic inheritance across the kingdoms of life. Replication occurs with a defined temporal order known as the replication timing (RT) programme, leading to organization of the genome into early- or late-replicating regions. RT is cell-type specific, is tightly linked to the three-dimensional nuclear organization of the genome1,2 and is considered an epigenetic fingerprint3. In spite of its importance in maintaining the epigenome4, the developmental regulation of RT in mammals in vivo has not been explored. Here, using single-cell Repli-seq5, we generated genome-wide RT maps of mouse embryos from the zygote to the blastocyst stage. Our data show that RT is initially not well defined but becomes defined progressively from the 4-cell stage, coinciding with strengthening of the A and B compartments. We show that transcription contributes to the precision of the RT programme and that the difference in RT between the A and B compartments depends on RNA polymerase II at zygotic genome activation. Our data indicate that the establishment of nuclear organization precedes the acquisition of defined RT features and primes the partitioning of the genome into early- and late-replicating domains. Our work sheds light on the establishment of the epigenome at the beginning of mammalian development and reveals the organizing principles of genome organization.

Osteosarcomas With Few Chromosomal Alterations or Adult Onset Are Genetically Heterogeneous

Osteosarcoma is the most common primary bone malignancy, often detected in children and adolescents and commonly associated with TP53 alterations along with a high number of chromosomal rearrangements. However, osteosarcoma can affect patients of any age, and some tumors display less genetic complexity. Besides TP53 variants, data on key driving mutations are lacking for many osteosarcomas, particularly those affecting adults. To detect osteosarcoma-specific alterations, we screened transcriptomic and genomic sequencing and copy number data from 150 bone tumors originally diagnosed as osteosarcomas. To increase the precision in gene fusion detection, we developed a bioinformatic tool denoted as NAFuse, which extracts gene fusions that are verified at both the genomic and transcriptomic levels. Apart from the already reported genetic subgroups of osteosarcoma with TP53 structural variants, or MDM2 and/or CDK4 amplification, we did not identify any recurrent genetic driver that signifies the remaining cases. Among the plethora of mutations identified, we found genetic alterations characteristic of, or similar to, those of other bone and soft tissue tumors in 8 cases. These mutations were found in tumors with relatively few other genetic alterations or in adults. Due to the lack of clinical context and available tissue, we can question the diagnosis only on a genetic basis. However, our findings support the notion that osteosarcomas with few chromosomal alterations or adult onset seem genetically distinct from conventional osteosarcomas of children and adolescents.

Druggable growth dependencies and tumor evolution analysis in patient-derived organoids of neuroendocrine neoplasms from multiple body sites

Neuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Treatment options for patients with NENs are limited, in part due to lack of accurate models. We establish patient-derived tumor organoids (PDTOs) from pulmonary NETs and derive PDTOs from an understudied subtype of NEC, large cell neuroendocrine carcinoma (LCNEC), arising from multiple body sites. PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through hypothesis-driven drug sensitivity analyses, we identify ASCL1 as a potential biomarker for response of LCNEC to treatment with BCL-2 inhibitors. Additionally, we discover a dependency on EGF in pulmonary NET PDTOs. Consistent with these findings, we find that, in an independent cohort, approximately 50% of pulmonary NETs express EGFR. This study identifies an actionable vulnerability for a subset of pulmonary NETs, emphasizing the utility of these PDTO models.

Circulating tumor DNA-based copy-number profiles enable monitoring treatment effects during therapy in high-grade serous carcinoma

Circulating tumor DNA (ctDNA) analysis has emerged as a promising tool for detecting and profiling longitudinal genomics changes in cancer. While copy-number alterations (CNAs) play a major role in cancers, treatment effect monitoring using copy-number profiles has received limited attention as compared to mutations. A major reason for this is the insensitivity of CNA analysis for the real-life tumor-fraction ctDNA samples. We performed copy-number analysis on 152 plasma samples obtained from 29 patients with high-grade serous ovarian cancer (HGSC) using a sequencing panel targeting over 500 genes. Twenty-one patients had temporally matched tissue and plasma sample pairs, which enabled assessing concordance with tissues sequenced with the same panel or whole-genome sequencing and to evaluate sensitivity. Our approach could detect concordant CNA profiles in most plasma samples with as low as 5% tumor content and highly amplified regions in samples with ∼1% of tumor content. Longitudinal profiles showed changes in the CNA profiles in seven out of 11 patients with high tumor-content plasma samples at relapse. These changes included focal acquired or lost copy-numbers, even though most of the genome remained stable. Two patients displayed major copy-number profile changes during therapy. Our analysis revealed ctDNA-detectable subclonal selection resulting from both surgical operations and chemotherapy. Overall, longitudinal ctDNA data showed acquired and diminished CNAs at relapse when compared to pre-treatment samples. These results highlight the importance of genomic profiling during treatment as well as underline the usability of ctDNA.

Gene expression and copy number profiling of follicular lymphoma biopsies from patients treated with first-line rituximab without chemotherapy

The Nordic Lymphoma Study Group has performed two randomized clinical trials with chemotherapy-free first-line treatment (rituximab +/- interferon) in follicular lymphoma (FL), with 73% of patients alive and 38% without any need of chemotherapy after 10.6 years median follow-up. In order to identify predictive markers, that may also serve as therapeutic targets, gene expression- and copy number profiles were obtained from 97 FL patients using whole genome microarrays. Copy number alterations (CNAs) were identified, e.g. by GISTIC. Cox Lasso Regression and Lasso logistic regression were used to determine molecular features predictive of time to next therapy (TTNT). A few molecular changes were associated with TTNT (e.g. increased expression of INPP5B, gains in 12q23/q24), but were not significant after adjusting for multiple testing. Our findings suggest that there are no strong determinants of patient outcome with respect to GE data and CNAs in FL patients treated with a chemotherapy-free regimen (i.e. rituximab +/- interferon).

Expressed Barcoding Enables High-Resolution Tracking of the Evolution of Drug Tolerance

For a majority of patients with non-small cell lung cancer with EGFR mutations, treatment with EGFR inhibitors (EGFRi) induces a clinical response. Despite this initial reduction in tumor size, residual disease persists that leads to disease relapse. Elucidating the preexisting biological differences between sensitive cells and surviving drug-tolerant persister cells and deciphering how drug-tolerant cells evolve in response to treatment could help identify strategies to improve the efficacy of EGFRi. In this study, we tracked the origins and clonal evolution of drug-tolerant cells at a high resolution by using an expressed barcoding system coupled with single-cell RNA sequencing. This platform enabled longitudinal profiling of gene expression and drug sensitivity in response to EGFRi across a large number of clones. Drug-tolerant cells had higher expression of key survival pathways such as YAP and EMT at baseline and could also differentially adapt their gene expression following EGFRi treatment compared with sensitive cells. In addition, drug combinations targeting common downstream components (MAPK) or orthogonal factors (chemotherapy) showed greater efficacy than EGFRi alone, which is attributable to broader targeting of the heterogeneous EGFRi-tolerance mechanisms present in tumors. Overall, this approach facilitates thorough examination of clonal evolution in response to therapy that could inform the development of improved diagnostic approaches and treatment strategies for targeting drug-tolerant cells.

SIGNIFICANCE

The evolution and heterogeneity of EGFR inhibitor tolerance are identified in a large number of clones at enhanced cellular and temporal resolution using an expressed barcode technology coupled with single-cell RNA sequencing.

Transcriptomic subtyping of malignant peripheral nerve sheath tumours highlights immune signatures, genomic profiles, patient survival and therapeutic targets

BACKGROUND

Malignant peripheral nerve sheath tumour (MPNST) is an aggressive orphan disease commonly affecting adolescents or young adults. Current knowledge of molecular tumour biology has been insufficient for development of rational treatment strategies. We aimed to discover molecular subtypes of potential clinical relevance.

METHODS

Fresh frozen samples of MPNSTs (n = 94) and benign neurofibromas (n = 28) from 115 patients in a European multicentre study were analysed by DNA copy number and/or transcriptomic profiling. Unsupervised transcriptomic subtyping was performed and the subtypes characterized for genomic aberrations, clinicopathological associations and patient survival.

FINDINGS

MPNSTs were classified into two transcriptomic subtypes defined primarily by immune signatures and proliferative processes. "Immune active" MPNSTs (44%) had sustained immune signals relative to neurofibromas, were more frequently low-grade (P = 0.01) and had favourable prognostic associations in a multivariable model of disease-specific survival with clinicopathological factors (hazard ratio 0.25, P = 0.003). "Immune deficient" MPNSTs were more aggressive and characterized by proliferative signatures, high genomic complexity, aberrant TP53 and PRC2 loss, as well as high relative expression of several potential actionable targets (EGFR, ERBB2, EZH2, KIF11, PLK1, RRM2). Integrated gene-wise analyses suggested a DNA copy number-basis for proliferative transcriptomic signatures in particular, and the tumour copy number burden further stratified the transcriptomic subtypes according to patient prognosis (P < 0.01).

INTERPRETATION

Approximately half of MPNSTs belong to an "immune deficient" transcriptomic subtype associated with an aggressive disease course, PRC2 loss and expression of several potential therapeutic targets, providing a rationale for molecularly-guided intervention trials.

FUNDING

Research grants from non-profit organizations, as stated in the Acknowledgements.

Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches

Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.

WCRC-25: A novel luminal Invasive Lobular Carcinoma cell line model

Breast cancer is categorized by the molecular and histologic presentation of the tumor, with the major histologic subtypes being No Special Type (NST) and Invasive Lobular Carcinoma (ILC). ILC are characterized by growth in a single file discohesive manner with stromal infiltration attributed to their hallmark pathognomonic loss of E-cadherin ( CDH1 ). Few ILC cell line models are available to researchers. Here we report the successful establishment and characterization of a novel ILC cell line, WCRC-25, from a metastatic pleural effusion from a postmenopausal Caucasian woman with metastatic ILC. WCRC-25 is an ER-negative luminal epithelial ILC cell line with both luminal and Her2-like features. It exhibits anchorage independent growth and haptotactic migration towards Collagen I. Sequencing revealed a CDH1 Q706* truncating mutation, together with mutations in FOXA1, CTCF, BRCA2 and TP53 , which were also seen in a series of metastatic lesions from the patient. Copy number analyses revealed amplification and deletion of genes frequently altered in ILC while optical genome mapping revealed novel structural rearrangements. RNA-seq analysis comparing the primary tumor, metastases and the cell line revealed signatures for cell cycle progression and receptor tyrosine kinase signaling. To assess targetability, we treated WCRC-25 with AZD5363 and Alpelisib confirming WCRC-25 as susceptible to PI3K/AKT signaling inhibition as predicted by our RNA sequencing analysis. In conclusion, we report WCRC-25 as a novel ILC cell line with promise as a valuable research tool to advance our understanding of ILC and its therapeutic vulnerabilities.

Financial support

The work was in part supported by a Susan G Komen Leadership Grant to SO (SAC160073) and NCI R01 CA252378 (SO/AVL). AVL and SO are Komen Scholars, Hillman Foundation Fellows and supported by BCRF. This project used the UPMC Hillman Cancer Center and Tissue and Research Pathology/Pitt Biospecimen Core shared resource which is supported in part by award P30CA047904. This research was also supported in part by the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483. Finally, partial support was provided by the Magee-Womens Research Institute and Foundation, The Shear Family Foundation, and The Metastatic Breast Cancer Network.

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

The evolution of two transmissible cancers in Tasmanian devils

Tasmanian devils have spawned two transmissible cancer lineages, named devil facial tumor 1 (DFT1) and devil facial tumor 2 (DFT2). We investigated the genetic diversity and evolution of these clones by analyzing 78 DFT1 and 41 DFT2 genomes relative to a newly assembled, chromosome-level reference. Time-resolved phylogenetic trees reveal that DFT1 first emerged in 1986 (1982 to 1989) and DFT2 in 2011 (2009 to 2012). Subclone analysis documents transmission of heterogeneous cell populations. DFT2 has faster mutation rates than DFT1 across all variant classes, including substitutions, indels, rearrangements, transposable element insertions, and copy number alterations, and we identify a hypermutated DFT1 lineage with defective DNA mismatch repair. Several loci show plausible evidence of positive selection in DFT1 or DFT2, including loss of chromosome Y and inactivation of MGA, but none are common to both cancers. This study reveals the parallel long-term evolution of two transmissible cancers inhabiting a common niche in Tasmanian devils.

Genomic characterization of DICER1-associated neoplasms uncovers molecular classes

DICER1 syndrome is a tumor predisposition syndrome that is associated with up to 30 different neoplastic lesions, usually affecting children and adolescents. Here we identify a group of mesenchymal tumors which is highly associated with DICER1 syndrome, and molecularly distinct from other DICER1-associated tumors. This group of DICER1-associated mesenchymal tumors encompasses multiple well-established clinicopathological tumor entities and can be further divided into three clinically meaningful classes designated "low-grade mesenchymal tumor with DICER1 alteration" (LGMT DICER1), "sarcoma with DICER1 alteration" (SARC DICER1), and primary intracranial sarcoma with DICER1 alteration (PIS DICER1). Our study not only provides a combined approach to classify DICER1-associated neoplasms for improved clinical management but also suggests a role for global hypomethylation and other recurrent molecular events in sarcomatous differentiation in mesenchymal tumors with DICER1 alteration. Our results will facilitate future investigations into prognostication and therapeutic approaches for affected patients.

High-Grade Endometrial Stromal Sarcomas With YWHAE::NUTM2 Gene Fusion Exhibit Recurrent CDKN2A Alterations and Absence of p16 Staining is a Poor Prognostic Marker

High-grade endometrial stromal sarcomas (HGESSs) are aggressive uterine tumors harboring oncogenic fusion proteins. We performed a molecular study of 36 HGESSs with YWHAE::NUTM2 gene fusion, assessing co-occurring genetic events, and showed that these tumors frequently harbor recurrent events involving the CDKN2A locus on chromosome 9p. Using array-based copy number profiling and CDKN2A fluorescence in situ hybridization, we identified homozygous and hemizygous deletions of CDKN2A in 18% and 14% of tumors (n = 22 analyzed), respectively. While all YWHAE-rearranged HGESSs with retained disomy for CDKN2A were immunohistochemically positive for p16INK4 (p16), all tumors with homozygous deletion of CDKN2A showed complete absence of p16 staining. Of the 2 tumors with a hemizygous deletion of CDKN2A, 1 showed diffuse and strong p16 positivity, whereas the other showed complete absence of staining. In the p16-negative case, we did not find intragenic mutations or DNA promoter methylation to explain the p16 protein loss, implicating other mechanisms in the regulation of protein expression. In our cohort, subclonal or complete absence of p16 staining was associated with worse overall survival compared with positive p16 staining (1-year overall survival: 28.6% vs 90.7%, respectively; n = 32; P < .001), with all 7 patients in the p16-negative group having succumbed to their disease within 2 years of diagnosis. Our results suggested CDKN2A alterations as a cooperative driver of tumorigenesis in a subset of HGESSs with the YWHAE::NUTM2 gene fusion and showed p16 to be a potential prognostic marker.

Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes

Genome instability and aberrant alterations of transcriptional programs both play important roles in cancer. Single-cell RNA sequencing (scRNA-seq) has the potential to investigate both genetic and nongenetic sources of tumor heterogeneity in a single assay. Here we present a computational method, Numbat, that integrates haplotype information obtained from population-based phasing with allele and expression signals to enhance detection of copy number variations from scRNA-seq. Numbat exploits the evolutionary relationships between subclones to iteratively infer single-cell copy number profiles and tumor clonal phylogeny. Analysis of 22 tumor samples, including multiple myeloma, gastric, breast and thyroid cancers, shows that Numbat can reconstruct the tumor copy number profile and precisely identify malignant cells in the tumor microenvironment. We identify genetic subpopulations with transcriptional signatures relevant to tumor progression and therapy resistance. Numbat requires neither sample-matched DNA data nor a priori genotyping, and is applicable to a wide range of experimental settings and cancer types.

Clinical, Histopathologic and Genetic Features of Rhabdoid Meningiomas

Rhabdoid meningiomas (RM) shows heterogeneous histological findings, and a wide variety of chromosomal copy number alterations (CNA) are associated with an unpredictable course of the disease. In this study, we analyzed a series of 305 RM samples from patients previously reported in the literature and 33 samples from 23 patients studied in our laboratory. Monosomy 22-involving the minimal but most common recurrent region loss of the 22q11.23 chromosomal region was the most observed chromosomal alteration, followed by losses of chromosomes 14, 1, 6, and 19, polysomies of chromosomes 17, 1q, and 20, and gains of 13q14.2, 10p13, and 21q21.2 chromosomal regions. Based on their CNA profile, RM could be classified into two genetic subgroups with distinct clinicopathologic features characterized by the presence of (1) chromosomal losses only and (2) combined losses and gains of several chromosomes. The latter displays a higher frequency of WHO grade 3 tumors and poorer clinical outcomes.

scONE-seq: A single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors

Single-cell multi-omics can provide a unique perspective on tumor cellular heterogeneity. Most previous single-cell whole-genome RNA sequencing (scWGS-RNA-seq) methods demonstrate utility with intact cells from fresh samples. Among them, many are not applicable to frozen samples that cannot produce intact single-cell suspensions. We have developed scONE-seq, a versatile scWGS-RNA-seq method that amplifies single-cell DNA and RNA without separating them from each other and hence is compatible with frozen biobanked samples. We benchmarked scONE-seq against existing methods using fresh and frozen samples to demonstrate its performance in various aspects. We identified a unique transcriptionally normal-like tumor clone by analyzing a 2-year frozen astrocytoma sample, demonstrating that performing single-cell multi-omics interrogation on biobanked tissue by scONE-seq could enable previously unidentified discoveries in tumor biology.

The first comprehensive genomic characterization of rectal squamous cell carcinoma

BACKGROUND

Rectal cancers represent 35% of colorectal cancers; 90% are adenocarcinomas, while squamous cell carcinoma accounts for 0.3% of them. Given its rarity, little is known concerning its pathogenesis, molecular profile and therapeutic management. The current treatment trend is to treat rectal squamous cell carcinoma by analogy to anal squamous cell carcinoma with definitive chemo-radiotherapy, setting aside surgery in case of local recurrence.

METHODS

We performed an in-depth genomic analysis (next-generation sequencing, copy number variation, and human papilloma virus characterization) on 10 rectal squamous cell carcinoma samples and compared them in silico to those of anal squamous cell carcinoma and rectal adenocarcinoma.

RESULTS

Rectal squamous cell carcinoma shows 100% HPV positivity. It has a mutational (PIK3CA, PTEN, TP53, ATM, BCL6, SOX2) and copy number variation profile (3p, 10p, 10q, 16q deletion and 1q, 3q, 5p, 8q, 20p gain) similar to anal squamous cell carcinoma. PI3K/Akt/mTOR is the most commonly affected signaling pathway similarly to anal squamous cell carcinoma. Most commonly gained or lost genes seen in rectal adenocarcinoma (FLT3, CDX2, GNAS, BCL2, SMAD4, MALT1) are not found in rectal squamous cell carcinoma.

CONCLUSION

This study presents the first comprehensive genomic characterization of rectal squamous cell carcinoma. We confirm the existence of this rare histology and its molecular similarity with anal squamous cell carcinoma. This molecular proximity confirms the adequacy of therapeutic management based on histology and not localization, suggesting that rectal squamous cell carcinoma should be treated like anal squamous cell carcinoma and not as a rectal adenocarcinoma.

The co-evolution of the genome and epigenome in colorectal cancer

Colorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4-7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Tangent normalization for somatic copy-number inference in cancer genome analysis

MOTIVATION

Somatic copy-number alterations (SCNAs) play an important role in cancer development. Systematic noise in sequencing and array data present a significant challenge to the inference of SCNAs for cancer genome analyses. As part of The Cancer Genome Atlas, the Broad Institute Genome Characterization Center developed the Tangent normalization method to generate copy-number profiles using data from single-nucleotide polymorphism (SNP) arrays and whole-exome sequencing (WES) technologies for over 10 000 pairs of tumors and matched normal samples. Here, we describe the Tangent method, which uses a unique linear combination of normal samples as a reference for each tumor sample, to subtract systematic errors that vary across samples. We also describe a modification of Tangent, called Pseudo-Tangent, which enables denoising through comparisons between tumor profiles when few normal samples are available.

RESULTS

Tangent normalization substantially increases signal-to-noise ratios (SNRs) compared to conventional normalization methods in both SNP array and WES analyses. Tangent and Pseudo-Tangent normalizations improve the SNR by reducing noise with minimal effect on signal and exceed the contribution of other steps in the analysis such as choice of segmentation algorithm. Tangent and Pseudo-Tangent are broadly applicable and enable more accurate inference of SCNAs from DNA sequencing and array data.

AVAILABILITY AND IMPLEMENTATION

Tangent is available at https://github.com/broadinstitute/tangent and as a Docker image (https://hub.docker.com/r/broadinstitute/tangent). Tangent is also the normalization method for the copy-number pipeline in Genome Analysis Toolkit 4 (GATK4).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA-binding protein ELAVL4/HuD ameliorates Alzheimer's disease-related molecular changes in human iPSC-derived neurons

The RNA binding protein ELAVL4/HuD regulates the translation and splicing of multiple Alzheimer's disease (AD) candidate genes. We generated ELAVL4 knockout (KO) human induced pluripotent stem cell-derived neurons to study the effect that ELAVL4 has on AD-related cellular phenotypes. ELAVL4 KO significantly increased the levels of specific APP isoforms and intracellular phosphorylated tau, molecular changes that are related to the pathological hallmarks of AD. Overexpression of ELAVL4 in wild-type neurons and rescue experiments in ELAVL4 KO cells showed opposite effects and also led to a reduction of the extracellular amyloid-beta (Aβ)42/40 ratio. All these observations were made in familial AD (fAD) and fAD-corrected neurons. To gain insight into the molecular cascades involved in neuronal ELAVL4 signaling, we conducted pathway and upstream regulator analyses of transcriptomic and proteomic data from the generated neurons. These analyses revealed that ELAVL4 affects multiple biological pathways linked to AD, including those involved in synaptic function, as well as gene expression downstream of APP and tau signaling. The analyses also suggest that ELAVL4 expression is regulated by insulin receptor-FOXO1 signaling in neurons. Taken together, ELAVL4 expression ameliorates AD-related molecular changes in neurons and affects multiple synaptic pathways, making it a promising target for novel drug development.

Two subtypes of cutaneous melanoma with distinct mutational signatures and clinico-genomic characteristics

Background: To decipher mutational signatures and their associations with biological implications in cutaneous melanomas (CMs), including those with a low ultraviolet (UV) signature.

Materials and Methods: We applied non-negative matrix factorization (NMF) and unsupervised clustering to the 96-class mutational context of The Cancer Genome Atlas (TCGA) cohort (N = 466) as well as other publicly available datasets (N = 527). To explore the feasibility of mutational signature-based classification using panel sequencing data, independent panel sequencing data were analyzed.

Results: NMF decomposition of the TCGA cohort and other publicly available datasets consistently found two mutational signatures: UV (SBS7a/7b dominant) and non-UV (SBS1/5 dominant) signatures. Based on mutational signatures, TCGA CMs were classified into two clusters: UV-high and UV-low. CMs belonging to the UV-low cluster showed significantly worse overall survival and landmark survival at 1-year than those in the UV-high cluster; low or high UV signature remained the most significant prognostic factor in multivariate analysis. The UV-low cluster showed distinct genomic and functional characteristic patterns: low mutation counts, increased proportion of triple wild-type and KIT mutations, high burden of copy number alteration, expression of genes related to keratinocyte differentiation, and low activation of tumor immunity. We verified that UV-high and UV-low clusters can be distinguished by panel sequencing.

Conclusion: Our study revealed two mutational signatures of CMs that divide CMs into two clusters with distinct clinico-genomic characteristics. Our results will be helpful for the clinical application of mutational signature-based classification of CMs.

Proteogenomic analysis of cancer aneuploidy and normal tissues reveals divergent modes of gene regulation across cellular pathways

How cells control gene expression is a fundamental question. The relative contribution of protein-level and RNA-level regulation to this process remains unclear. Here, we perform a proteogenomic analysis of tumors and untransformed cells containing somatic copy number alterations (SCNAs). By revealing how cells regulate RNA and protein abundances of genes with SCNAs, we provide insights into the rules of gene regulation. Protein complex genes have a strong protein-level regulation while non-complex genes have a strong RNA-level regulation. Notable exceptions are plasma membrane protein complex genes, which show a weak protein-level regulation and a stronger RNA-level regulation. Strikingly, we find a strong negative association between the degree of RNA-level and protein-level regulation across genes and cellular pathways. Moreover, genes participating in the same pathway show a similar degree of RNA- and protein-level regulation. Pathways including translation, splicing, RNA processing, and mitochondrial function show a stronger protein-level regulation while cell adhesion and migration pathways show a stronger RNA-level regulation. These results suggest that the evolution of gene regulation is shaped by functional constraints and that many cellular pathways tend to evolve one predominant mechanism of gene regulation at the protein level or at the RNA level.

SCONCE2: jointly inferring single cell copy number profiles and tumor evolutionary distances

Background

Single cell whole genome tumor sequencing can yield novel insights into the evolutionary history of somatic copy number alterations. Existing single cell copy number calling methods do not explicitly model the shared evolutionary process of multiple cells, and generally analyze cells independently. Additionally, existing methods for estimating tumor cell phylogenies using copy number profiles are sensitive to profile estimation errors.

Results

We present SCONCE2, a method for jointly calling copy number alterations and estimating pairwise distances for single cell sequencing data. Using simulations, we show that SCONCE2 has higher accuracy in copy number calling and phylogeny estimation than competing methods. We apply SCONCE2 to previously published single cell sequencing data to illustrate the utility of the method.

Conclusions

SCONCE2 jointly estimates copy number profiles and a distance metric for inferring tumor phylogenies in single cell whole genome tumor sequencing across multiple cells, enabling deeper understandings of tumor evolution.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04890-w.

Clonal evolution in primary breast cancers under sequential epirubicin and docetaxel monotherapy

Background

Subclonal evolution during primary breast cancer treatment is largely unexplored. We aimed to assess the dynamic changes in subclonal composition of treatment-naïve breast cancers during neoadjuvant chemotherapy.

Methods

We performed whole exome sequencing of tumor biopsies collected before, at therapy switch, and after treatment with sequential epirubicin and docetaxel monotherapy in 51 out of 109 patients with primary breast cancer, who were included in a prospectively registered, neoadjuvant single-arm phase II trial.

Results

There was a profound and differential redistribution of subclones during epirubicin and docetaxel treatment, regardless of therapy response. While truncal mutations and main subclones persisted, smaller subclones frequently appeared or disappeared. Reassessment of raw data, beyond formal mutation calling, indicated that the majority of subclones seemingly appearing during treatment were in fact present in pretreatment breast cancers, below conventional detection limits. Likewise, subclones which seemingly disappeared were still present, below detection limits, in most cases where tumor tissue remained. Tumor mutational burden (TMB) dropped during neoadjuvant therapy, and copy number analysis demonstrated specific genomic regions to be systematically lost or gained for each of the two chemotherapeutics.

Conclusions

Sequential epirubicin and docetaxel monotherapy caused profound redistribution of smaller subclones in primary breast cancer, while early truncal mutations and major subclones generally persisted through treatment.

Trial registration

ClinicalTrials.gov, NCT00496795, registered on July 4, 2007.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01090-2.

Dynamic and adaptive cancer stem cell population admixture in colorectal neoplasia

Intestinal homeostasis is underpinned by LGR5+ve crypt-base columnar stem cells (CBCs), but following injury, dedifferentiation results in the emergence of LGR5-ve regenerative stem cell populations (RSCs), characterized by fetal transcriptional profiles. Neoplasia hijacks regenerative signaling, so we assessed the distribution of CBCs and RSCs in mouse and human intestinal tumors. Using combined molecular-morphological analysis, we demonstrate variable expression of stem cell markers across a range of lesions. The degree of CBC-RSC admixture was associated with both epithelial mutation and microenvironmental signaling disruption and could be mapped across disease molecular subtypes. The CBC-RSC equilibrium was adaptive, with a dynamic response to acute selective pressure, and adaptability was associated with chemoresistance. We propose a fitness landscape model where individual tumors have equilibrated stem cell population distributions along a CBC-RSC phenotypic axis. Cellular plasticity is represented by position shift along this axis and is influenced by cell-intrinsic, extrinsic, and therapeutic selective pressures.

Identification of metastasis-related long non-coding RNAs in lung cancer through a novel tumor mesenchymal score

Long non-coding RNAs (lncRNAs) have been proven to play critical roles in epithelial-mesenchymal transition (EMT) and metastasis of lung cancer. However, the biological functions and related mechanisms of lncRNAs are unclear. In addition, the EMT-based prognosis prediction in lung cancer still lacks investigation. Here, we established the methodology of identifying critical metastasis-related lncRNAs using comprehensive datasets of cancer transcriptome, genome and epigenome, and also provided tools for prognosis prediction in lung cancer. Initially, important mesenchymal marker genes were identified to compose the tumor mesenchymal score, which predicted patient prognosis in lung cancer, especially lung adenocarcinoma (LUAD). The score was also correlated with several crucial biological and physiological processes, such as tumor immune and hypoxia. Based on the score, lung cancer patients was classified into epithelial and mesenchymal subtypes, and lncRNAs which exhibited expressional dysregulation, promotor methylation alteration and copy number variation between the two subtypes in LUAD were identified and underwent further prognostic analyses. Finally, we identified 14 lncRNAs as EMT-related and significant biomarkers in prognosis prediction of LUAD. As validation, lncRNA RBPMS-AS1 was proven to be co-expressed with epithelial biomarkers, suppressive for A549 cell migration, invasion and EMT, and also significantly associated with better outcomes of LUAD patients, suggesting the potential of RBPMS-AS1 to serve as a lncRNA epithelial biomarker in metastasis of LUAD. Based on the identified lncRNAs, an EMT-linked lncRNA prognostic signature was further established. Taken together, our study provides robust predictive tools, potential lncRNA targets and feasible screening strategies for future study of lung cancer metastasis.

Resolving single-cell copy number profiling for large datasets

The advances of single-cell DNA sequencing (scDNA-seq) enable us to characterize the genetic heterogeneity of cancer cells. However, the high noise and low coverage of scDNA-seq impede the estimation of copy number variations (CNVs). In addition, existing tools suffer from intensive execution time and often fail on large datasets. Here, we propose SeCNV, an efficient method that leverages structural entropy, to profile the copy numbers. SeCNV adopts a local Gaussian kernel to construct a matrix, depth congruent map (DCM), capturing the similarities between any two bins along the genome. Then, SeCNV partitions the genome into segments by minimizing the structural entropy from the DCM. With the partition, SeCNV estimates the copy numbers within each segment for cells. We simulate nine datasets with various breakpoint distributions and amplitudes of noise to benchmark SeCNV. SeCNV achieves a robust performance, i.e. the F1-scores are higher than 0.95 for breakpoint detections, significantly outperforming state-of-the-art methods. SeCNV successfully processes large datasets (>50 000 cells) within 4 min, while other tools fail to finish within the time limit, i.e. 120 h. We apply SeCNV to single-nucleus sequencing datasets from two breast cancer patients and acoustic cell tagmentation sequencing datasets from eight breast cancer patients. SeCNV successfully reproduces the distinct subclones and infers tumor heterogeneity. SeCNV is available at https://github.com/deepomicslab/SeCNV.

Dissecting the treatment-naive ecosystem of human melanoma brain metastasis

Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma; yet, our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBMs and 10 extracranial melanoma metastases (ECMs) and matched spatial single-cell transcriptomics and T cell receptor (TCR)-seq. Cancer cells from MBM were more chromosomally unstable, adopted a neuronal-like cell state, and enriched for spatially variably expressed metabolic pathways. Key observations were validated in independent patient cohorts, patient-derived MBM/ECM xenograft models, RNA/ATAC-seq, proteomics, and multiplexed imaging. Integrated spatial analyses revealed distinct geography of putative cancer immune evasion and evidence for more abundant intra-tumoral B to plasma cell differentiation in lymphoid aggregates in MBM. MBM harbored larger fractions of monocyte-derived macrophages and dysfunctional TOX+CD8+ T cells with distinct expression of immune checkpoints. This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.

Increased Tumor Intrinsic Growth Potential and Decreased Immune Function Orchestrate the Progression of Lung Adenocarcinoma

Background

The overall 5-year survival of lung cancer was reported to be only ~15%, with lung adenocarcinoma (LUAD) as the main pathological subtype. Before developing into invasive stages, LUAD undergoes pre-invasive stages of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), where surgical resection gives an excellent 5-year survival rate. Given the dramatic decline of prognosis from pre-invasive to invasive stages, a deeper understanding of key molecular changes driving the progression of LUAD is highly needed.

Methods

In this study, we performed whole-exome sequencing and RNA sequencing on surgically resected 24 AIS, 74 MIA, 99 LUAD specimens, and their adjacent paired normal tissues. Survival data were obtained by follow-up after surgery. Key molecular events were found by comparing the gene expression profiles of tumors with different stages. Finally, to measure the level of imbalance between tumor intrinsic growth potential and immune microenvironment, a tumor progressive (TP) index was developed to predict tumor progression and patients’ survival outcome and validated by external datasets.

Results

As tumors progressed to more invasive stages, they acquired higher growth potential, mutational frequency of tumor suppressor genes, somatic copy number alterations, and tumor mutation burden, along with suppressed immune function. To better predict tumor progression and patients’ outcome, TP index were built to measure the imbalance between tumor intrinsic growth potential and immune microenvironment. Patients with a higher TP index had significantly worse recurrence-free survival [Hazard ratio (HR), 10.47; 95% CI, 3.21–34.14; p < 0.0001] and overall survival (OS) [Hazard ratio (HR), 4.83e8; 95% CI, 0–Inf; p = 0.0013]. We used The Cancer Genome Atlas (TCGA)-LUAD dataset for validation and found that patients with a higher TP index had significantly worse OS (HR, 1.10; 95% CI, 0.83–1.45; p = 0.048), demonstrating the prognostic value of the TP index for patients with LUAD.

Conclusions

The imbalance of tumor intrinsic growth potential and immune function orchestrate the progression of LUAD, which can be measured by TP index. Our study provided new insights into predicting survival of patients with LUAD and new target discovery for LUAD through assessing the imbalance between tumor intrinsic growth potential and immune function.

CONET: copy number event tree model of evolutionary tumor history for single-cell data

Copy number alterations constitute important phenomena in tumor evolution. Whole genome single-cell sequencing gives insight into copy number profiles of individual cells, but is highly noisy. Here, we propose CONET, a probabilistic model for joint inference of the evolutionary tree on copy number events and copy number calling. CONET employs an efficient, regularized MCMC procedure to search the space of possible model structures and parameters. We introduce a range of model priors and penalties for efficient regularization. CONET reveals copy number evolution in two breast cancer samples, and outperforms other methods in tree reconstruction, breakpoint identification and copy number calling.

Signatures of copy number alterations in human cancer

Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage-fusion-bridge cycles, among others, which may lead to chromosomal instability and aneuploidy1,2. These copy number alterations contribute to cancer initiation, progression and therapeutic resistance3-5. Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas6 revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2. In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations.

An integrative in-silico analysis discloses a novel molecular subset of colorectal cancer possibly eligible for immune checkpoint immunotherapy

BACKGROUND

Historically, the molecular classification of colorectal cancer (CRC) was based on the global genomic status, which identified microsatellite instability in mismatch repair (MMR) deficient CRC, and chromosomal instability in MMR proficient CRC. With the introduction of immune checkpoint inhibitors, the microsatellite and chromosomal instability classification regained momentum as the microsatellite instability condition predicted sensitivity to immune checkpoint inhibitors, possibly due to both high tumor mutation burden (TMB) and high levels of infiltrating lymphocytes. Conversely, proficient MMR CRC are mostly resistant to immunotherapy. To better understand the relationship between the microsatellite and chromosomal instability classification, and eventually discover additional CRC subgroups relevant for therapeutic decisions, we developed a computational pipeline that include molecular integrative analysis of genomic, epigenomic and transcriptomic data.

RESULTS

The first step of the pipeline was based on unsupervised hierarchical clustering analysis of copy number variations (CNVs) versus hypermutation status that identified a first CRC cluster with few CNVs enriched in Hypermutated and microsatellite instability samples, a second CRC cluster with a high number of CNVs mostly including non-HM and microsatellite stable samples, and a third cluster (7.8% of the entire dataset) with low CNVs and low TMB, which shared clinical-pathological features with Hypermutated CRCs and thus defined Hypermutated-like CRCs. The mutational features, DNA methylation profile and base substitution fingerprints of these tumors revealed that Hypermutated-like patients are molecularly distinct from Hypermutated and non-Hypermutated tumors and are likely to develop and progress through different genetic events. Transcriptomic analysis highlighted further differences amongst the three groups and revealed an inflamed tumor microenvironment and modulation Immune Checkpoint Genes in Hypermutated-like CRCs.

CONCLUSION

Therefore, our work highlights Hypermutated-like tumors as a distinct and previously unidentified CRC subgroup possibly responsive to immune checkpoint inhibitors. If further validated, these findings can lead to expanding the fraction of patients eligible to immunotherapy.

FGFR1 is a potential therapeutic target in neuroblastoma

BACKGROUND

FGFR1 regulates cell-cell adhesion and extracellular matrix architecture and acts as oncogene in several cancers. Potential cancer driver mutations of FGFR1 occur in neuroblastoma (NB), a neural crest-derived pediatric tumor arising in sympathetic nervous system, but so far they have not been studied experimentally. We investigated the driver-oncogene role of FGFR1 and the implication of N546K mutation in therapy-resistance in NB cells.

METHODS

Public datasets were used to predict the correlation of FGFR1 expression with NB clinical outcomes. Whole genome sequencing data of 19 paired diagnostic and relapse NB samples were used to find somatic mutations. In NB cell lines, silencing by short hairpin RNA and transient overexpression of FGFR1 were performed to evaluate the effect of the identified mutation by cell growth, invasion and cologenicity assays. HEK293, SHSY5Y and SKNBE2 were selected to investigate subcellular wild-type and mutated protein localization. FGFR1 inhibitor (AZD4547), alone or in combination with PI3K inhibitor (GDC0941), was used to rescue malignant phenotypes induced by overexpression of FGFR1 wild-type and mutated protein.

RESULTS

High FGFR1 expression correlated with low relapse-free survival in two independent NB gene expression datasets. In addition, we found the somatic mutation N546K, the most recurrent point mutation of FGFR1 in all cancers and already reported in NB, in one out of 19 matched primary and recurrent tumors. Loss of FGFR1 function attenuated invasion and cologenicity in NB cells, whereas FGFR1 overexpression enhanced oncogenicity. The overexpression of FGFR1^N546K protein showed a higher nuclear localization compared to wild-type protein and increased cellular invasion and cologenicity. Moreover, N546K mutation caused the failure in response to treatment with FGFR1 inhibitor by activation of ERK, STAT3 and AKT pathways. The combination of FGFR1 and PI3K pathway inhibitors was effective in reducing the invasive and colonigenic ability of cells overexpressing FGFR1 mutated protein.

CONCLUSIONS

FGFR1 is an actionable driver oncogene in NB and a promising therapy may consist in targeting FGFR1 mutations in patients with therapy-resistant NB.

Neoantigen-specific CD8 T cell responses in the peripheral blood following PD-L1 blockade might predict therapy outcome in metastatic urothelial carcinoma

CD8⁺ T cell reactivity towards tumor mutation-derived neoantigens is widely believed to facilitate the antitumor immunity induced by immune checkpoint blockade (ICB). Here we show that broadening in the number of neoantigen-reactive CD8⁺ T cell (NART) populations between pre-treatment to 3-weeks post-treatment distinguishes patients with controlled disease compared to patients with progressive disease in metastatic urothelial carcinoma (mUC) treated with PD-L1-blockade. The longitudinal analysis of peripheral CD8⁺ T cell recognition of patient-specific neopeptide libraries consisting of DNA barcode-labelled pMHC multimers in a cohort of 24 patients from the clinical trial NCT02108652 also shows that peripheral NARTs derived from patients with disease control are characterised by a PD1⁺ Ki67⁺ effector phenotype and increased CD39 levels compared to bystander bulk- and virus-antigen reactive CD8⁺ T cells. The study provides insights into NART characteristics following ICB and suggests that early-stage NART expansion and activation are associated with response to ICB in patients with mUC.

Immune checkpoint blockade therapy is successful in a high proportion of cancer patients, but others remain unresponsive. Authors here show that therapeutic success might be predictable in metastatic bladder cancer by longitudinal analysis of the early neoantigen-specific CD8 T cell response in peripheral blood.

SCONCE: a method for profiling copy number alterations in cancer evolution using single-cell whole genome sequencing

MOTIVATION

Copy number alterations (CNAs) are a significant driver in cancer growth and development, but remain poorly characterized on the single cell level. Although genome evolution in cancer cells is Markovian through evolutionary time, CNAs are not Markovian along the genome. However, existing methods call copy number profiles with Hidden Markov Models or change point detection algorithms based on changes in observed read depth, corrected by genome content and do not account for the stochastic evolutionary process.

RESULTS

We present a theoretical framework to use tumor evolutionary history to accurately call CNAs in a principled manner. To model the tumor evolutionary process and account for technical noise from low coverage single-cell whole genome sequencing data, we developed SCONCE, a method based on a Hidden Markov Model to analyze read depth data from tumor cells using matched normal cells as negative controls. Using a combination of public data sets and simulations, we show SCONCE accurately decodes copy number profiles, and provides a useful tool for understanding tumor evolution.

AVAILABILITYAND IMPLEMENTATION

SCONCE is implemented in C++11 and is freely available from https://github.com/NielsenBerkeleyLab/sconce.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic consequences of domestication of the Siamese fighting fish

Siamese fighting (betta) fish are among the most popular and morphologically diverse pet fish, but the genetic bases of their domestication and phenotypic diversification are largely unknown. We assembled de novo the genome of a wild Betta splendens and whole-genome sequenced 98 individuals across five closely related species. We find evidence of bidirectional hybridization between domesticated ornamental betta and other wild Betta species. We discover dmrt1 as the main sex determination gene in ornamental betta and that it has lower penetrance in wild B. splendens. Furthermore, we find genes with signatures of recent, strong selection that have large effects on color in specific parts of the body or on the shape of individual fins and that most are unlinked. Our results demonstrate how simple genetic architectures paired with anatomical modularity can lead to vast phenotypic diversity generated during animal domestication and launch betta as a powerful new system for evolutionary genetics.

Prioritization of putatively detrimental variants in euploid miscarriages

Miscarriage is the spontaneous termination of a pregnancy before 24 weeks of gestation. We studied the genome of euploid miscarried embryos from mothers in the range of healthy adult individuals to understand genetic susceptibility to miscarriage not caused by chromosomal aneuploidies. We developed GP , a pipeline that we used to prioritize 439 unique variants in 399 genes, including genes known to be associated with miscarriages. Among the prioritized genes we found STAG2 coding for the cohesin complex subunit, for which inactivation in mouse is lethal, and TLE4 a target of Notch and Wnt, physically interacting with a region on chromosome 9 associated to miscarriages.

The breast pre-cancer atlas illustrates the molecular and micro-environmental diversity of ductal carcinoma in situ

Microenvironmental and molecular factors mediating the progression of Breast Ductal Carcinoma In Situ (DCIS) are not well understood, impeding the development of prevention strategies and the safe testing of treatment de-escalation. We addressed methodological barriers and characterized the mutational, transcriptional, histological, and microenvironmental landscape across 85 multiple microdissected regions from 39 cases. Most somatic alterations, including whole-genome duplications, were clonal, but genetic divergence increased with physical distance. Phenotypic and subtype heterogeneity was frequently associated with underlying genetic heterogeneity and regions with low-risk features preceded those with high-risk features according to the inferred phylogeny. B- and T-lymphocytes spatial analysis identified three immune states, including an epithelial excluded state located preferentially at DCIS regions, and characterized by histological and molecular features of immune escape, independently from molecular subtypes. Such breast pre-cancer atlas with uniquely integrated observations will help scope future expansion studies and build finer models of outcomes and progression risk.

Stem-like breast cancer cells in the activated state resist genetic stress via TGFBI-ZEB1

Breast cancer cells with stem-like properties are critical for tumor progression, yet much about these cells remains unknown. Here, we characterize a population of stem-like breast cancer cells expressing the integrin αvβ3 as transcriptionally related to activated stem/basal cells in the normal human mammary gland. An unbiased functional screen of genes unique to these cells identified the matrix protein TGFBI (BIG-H3) and the transcription factor ZEB1 as necessary for tumorsphere formation. Surprisingly, these genes were not required for cell proliferation or survival, but instead maintained chromosomal stability. Consistent with this finding, CRISPR deletion of either gene synergized with PARP inhibition to deplete αvβ3⁺ stem-like cells, which are normally resistant to this therapy. Our findings highlight a critical role for TGFBI-ZEB1 protection against genetic stress as a key attribute of activated stem-like cells and suggest that disrupting this ability may enhance their "BRCAness" by increasing sensitivity to PARP inhibitors.