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• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 230 samples; filetype=bam

  Dataset EGAD00001004724

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 232 samples; filetype=bam

  Dataset EGAD00001004725

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 239 samples; filetype=bam

  Dataset EGAD00001004726

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75617A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 692 samples; filetype=bam

  Dataset EGAD00001004727

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 612 samples; filetype=bam

  Dataset EGAD00001004728

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1700 samples; filetype=bam

  Dataset EGAD00001004729

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam

  Dataset EGAD00001004752

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam

  Dataset EGAD00001004753

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 636 samples; filetype=bam

  Dataset EGAD00001004754

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95722A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam

  Dataset EGAD00001004755

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 480 samples; filetype=bam

  Dataset EGAD00001004756

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam

  Dataset EGAD00001004757

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

  Dataset EGAD00001004759

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples

  Dataset EGAD00001004760

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

  Dataset EGAD00001004761

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96139A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam

  Dataset EGAD00001004762

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

  Dataset EGAD00001004763

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96150A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam

  Dataset EGAD00001004764

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

  Dataset EGAD00001004765

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam

  Dataset EGAD00001004766

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

  Dataset EGAD00001004767

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96171A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam

  Dataset EGAD00001004768

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96187A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

  Dataset EGAD00001004770

• Tobacco exposure and somatic mutations in normal human bronchial epithelium

  That tobacco smoking causes lung cancer is well-established, but we lack quantitative understanding of its effects on genomes of normal bronchial epithelium. We sequenced whole genomes of 632 colonies derived from single bronchial epithelial cells across 16 subjects. Tobacco smoking is the major influence on mutation burden, adding 1000-10,000+ mutations/cell, massively increasing both between-subject and within-subject variance, and generating several distinct signatures of substitutions and indels. A population of cells in subjects with smoking history had mutation burdens equivalent to that expected for never-smokers: these cells lacked tobacco-specific mutational signatures, were four-fold more frequent in ex-smokers than current smokers, and had significantly longer telomeres than their more mutated counterparts. Driver mutations increased in frequency with age, affecting 4-14% of cells in middle-aged never-smokers. In current smokers, ≥25% of cells carried driver mutations and 0-6% cells had 2 or even 3 drivers. Thus, tobacco smoking increases mutation burden, cell-to-cell heterogeneity and driver mutations, but quitting promotes replenishment of bronchial epithelium from mitotically quiescent cells that have avoided tobacco mutagenesis.

  Dataset EGAD00001005193

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-010

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006026