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.
Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA ...sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.
Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and ...temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. We conducted longitudinal whole-genome sequencing of 37 tumor samples from 8 patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. Subclonal copy-number alterations were identified in all patients except one. In 5 patients, subclones from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clones in 6 of 7 patients with multiple clones. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy-number clones. A chromosomal duplication timing analysis revealed that complex genomic rearrangements typically occurred prior to diagnosis, supporting a macroevolutionary model of evolution, where a large number of genomic aberrations are acquired over a short period of time followed by clonal selection, as opposed to ongoing evolution. A mutational signature analysis of recurrent tumors revealed that homologous repair deficiency (HRD)-related SBS3 increases at each time point in patients with recurrent disease, suggesting that HRD continues to be an active mutagenic process after diagnosis. Overall, by examining the clonal relationships between temporally and spatially separated samples from patients with relapsed/refractory osteosarcoma, this study sheds light on the intratumor heterogeneity and potential drivers of treatment resistance in this disease.
The chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.
Abstract Numerous next-generation sequencing studies have provided an overview pancreatic ductal adenocarcinoma (PDAC)’s genomic evolution. But how its genome evolves through treatment and metastasis ...has not been extensively studied due to lack of samples and technical limitation of bulk sequencing on low-tumor purity samples. Herein we applied targeted single-nucleus DNA sequencing (snDNA-seq) to a cohort of 18 patients, each with >= 2 multiregional/longitudinal samples, totaling 65 samples. These included 5 early-stage resections, 11 stage IV autopsies and 2 biopsy-derived organoids taken pre- and post-treatment. We also developed a set of computational methods for this new datatype to delineate genomic evolution at high resolution. Despite higher sensitivity than bulk, snDNA-seq did not uncover significant subclonal single-nucleotide variations (SNVs) on our panel targeting 253 select genes for PDAC. But it detected a higher frequency of CDKN2A (72% against 30%) and SMAD4 (56% against 32%) alterations, mostly attributed to chromosomal deletions. Many were subclonal or only affected a few hundred base-pairs of the gene, making them elusive to bulk sequencing. Except for one case driven by BRCA2 mutations rather than the canonical KRAS oncogene, other patients had mostly linear phylogenies with more SNVs occurring before the most recent common ancestor (MRCA) of clones, for early/late-stage and longitudinal cases alike. This early fixation of drivers and rapid clonal sweep afterwards likely correlates with the particular aggressiveness of PDAC. Metastatic clones almost always fell towards the end of phylogenies and were shared among spatially separated sites, indicating late metastatic dissemination in molecular evolution time. Metastases to the liver and diaphragm appeared to be more genetically evolved than other sites, likely due to harsher selective pressure cast by the metastatic routes/distal microenvironments. 16 of 18 PDACs were observed to converge towards tumor cell-intrinsic TGF-β unresponsiveness by mutating various components of the pathway. Such convergent evolution usually happened at the primary site, indicating a strong selective advantage of the phenotype in the desmoplastic, nutrient-poor pancreas microenvironment. Continuous evolution was seen through treatment and metastasis, driven by seemingly random genome-scale copy number variations (CNVs) and focal amplification/deletions to genes such as KRAS, CDKN2A, SMAD4, MYC. These insights on PDAC’s genomic evolution inform more precision medicine efforts to come. Early fixation of driver SNVs sculpts a largely homogeneous disease that could be uniformly targeted. But special care should be taken to obviate resistance mechanisms conferred by continuously evolving CNV events- compared to SNVs, these mechanisms provide faster remodeling of the genome, and thus faster generation of new phenotypes and adaptation. Citation Format: Haochen Zhang, Palash Sashittal, Elias-Ramzey Karnoub, Akhil Jakatdar, Shigeaki Umeda, Nicolas Lecomte, Jungeui Hong, Katelyn Mullen, Akimasa Hayashi, Caitlin A. McIntyre, Benjamin J. Raphael, Christine A. Iacobuzio-Donahue. A refined view of pancreatic cancer genomic evolution through single-nucleus DNA sequencing abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6927.
Abstract
Late-stage disease consists of more than half of pancreatic ductal adenocarcinoma (PDAC) at diagnosis, but most samples have low tumor purity that limits bulk DNA sequencing. Additionally, ...as clonal evolution happens at single-cell level, bulk sequencing misses many insights such as subclones, colocalization of events etc. Thus, we aim to refine our understanding of PDAC clonal evolution and heterogeneity with single-cell DNA sequencing. Previously we developed a scalable, high-throughput single-nucleus DNA-seq (snDNA-seq) method (doi.org/10.1038/s41467-023-36344-z) for archival primary solid tumor samples. Here we used it to sequence over 100,000 single nuclei from 70 archival primary samples of 18 PDAC patients, with a targeted panel covering 254 most relevant genes for PDAC. The cohort included 5 early- and 10 late-stage diagnoses whose primary tumors and metastases were multiregionally sampled, as well as 3 longitudinal cases whose tumors were collected before and after treatment. We also developed a set of computational tools to call short variant (SNV) and copy number variation (CNV) events and use both signals to infer phylogenies from this dataset. Owing to snDNA-seq’s sensitivity to detect subclonal, small-scale genomic events, we found that alterations to SMAD4 and CDKN2A were more frequent than previously shown and enriched in late-stage disease. Many manifested as focal (<1kbp) homozygous deletions difficult to detect by bulk. TGF-β signaling pathway was convergently targeted for inactivation two late-stage cases, which were wildtype for SMAD4, but had homozygous deletions of TGFBR2 and ACVR1B and a nonsense mutation to ARID2 respectively. With single cell phylogenies, we observed that PDAC generally displayed linear rather than bifurcating clonal evolution, which could be linked to its aggressiveness that does not permit time for significant clonal branching. Driver SNVs were mostly truncal (present in all tumor cells) irrespective of stage. High spatial homogeneity with respect to all (driver and passenger) SNVs was seen across both primary tumors and metastases, suggesting that PDAC invasion and metastasis were late events in its course of genetic evolution. The major source of spatial and temporal heterogeneity was CNV. Although most were large-scale and appeared random, some focally targeted important genes, such as step-wise deletion of the CDKN2A and SMAD4 gene and focal amplification of MTOR and GATA6 genes, suggesting continuous evolution towards the most fit genotype. In sum, snDNA-seq revealed more PDAC driver gene alterations than previously estimated. Rather than SNVs, CNVs caused by increased chromosomal instability generated the genetic diversity for selection to operate on as disease progress. Equally important is we demonstrate a single-cell analysis framework that can reveal high-resolution clonal evolution patterns which can be useful for many further studies of cancer evolution.
Citation Format: Haochen Zhang, Palash Sashittal, Elias-Ramzey Karnoub, Shigeaki Umeda, Nicolas Lecomte, Jungeui Hong, Akhil Jakatdar, Katelyn Mullen, Akimasa Hayashi, Caitlin A. McIntyre, Benjamin J. Raphael, Christine A. Iacobuzio-Donahue. Genomic evolution of pancreatic cancer at single-cell resolution abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C115.
The effects of self directed video feedback was examined in the current study with therapists of home based ABA programs working with children with a pervasive developmental disorder. A multiple ...baseline design was used to systematically implement the intervention which consisted of the therapists watching a self recorded video of implementing a prompting procedure, completing a questionnaire and setting a goal for the next therapy session. Results of the intervention showed that the intervention was effective for one participant, while the other participant's prompting behavior only increased after further instruction and modeling of the behavior by the author. Implications for the current study as well as possibilities for future research are discussed.
The effects of self directed video feedback was examined in the current study with therapists of home based ABA programs working with children with a pervasive developmental disorder. A multiple ...baseline design was used to systematically implement the intervention which consisted of the therapists watching a self recorded video of implementing a prompting procedure, completing a questionnaire and setting a goal for the next therapy session. Results of the intervention showed that the intervention was effective for one participant, while the other participant's prompting behavior only increased after further instruction and modeling of the behavior by the author. Implications for the current study as well as possibilities for future research are discussed.
PDF
