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• Ovarian Cancer Organoid Biobank

  WGS of ovarian cancer organoids, tumor samples and blood references. Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004387

• THE GENOMIC LANDSCAPE OF ACTINIC KERATOSIS

  Actinic keratoses (AK) are lesions of epidermal keratinocyte dysplasia and are precursors for invasive cutaneous squamous cell carcinoma (CSCC). Identifying the specific genomic alterations driving progression from normal skin-AK-invasive CSCC is challenging due to the massive ultraviolet radiation-induced mutational burden characteristic at all stages of this progression. Here, we report the largest AK whole exome sequencing study to date and perform mutational signature and candidate driver gene analysis on these lesions. We demonstrate in 37 AK, from both immunosuppressed and immunocompetent patients, that there are significant similarities to CSCC in terms of mutational burden, copy number alterations, mutational signatures and patterns of driver gene mutations. We identify 44 significantly mutated AK driver genes and confirm that these genes are similarly altered in CSCC. We identify the azathioprine mutational signature in all AK from patients exposed to the drug, providing further evidence for its role in keratinocyte carcinogenesis. CSCC differ from AK in having higher levels of intra-sample heterogeneity. Alterations in signaling pathways also differ, with immune-related signaling and TGF-β signaling significantly more mutated in CSCC. Integrating our findings with independent gene expression datasets confirms that dysregulated TGF-β signaling may represent an important event in AK-CSCC progression.

  Dataset EGAD00001006894

• A110632A

  Whole genome sequencing for single cells for library A110632A 1151 cells; filetype=bam

  Dataset EGAD00001007094

• A110632B

  Whole genome sequencing for single cells for library A110632B 892 cells; filetype=bam

  Dataset EGAD00001007095

• A118833A

  Whole genome sequencing for single cells for library A118833A 919 cells; filetype=bam

  Dataset EGAD00001007096

• A118833B

  Whole genome sequencing for single cells for library A118833B 1147 cells; filetype=bam

  Dataset EGAD00001007097

• A118845B

  Whole genome sequencing for single cells for library A118845B 1209 cells; filetype=bam

  Dataset EGAD00001007098

• A118869A

  Whole genome sequencing for single cells for library A118869A 1165 cells; filetype=bam

  Dataset EGAD00001007099

• A118869B

  Whole genome sequencing for single cells for library A118869B 1124 cells; filetype=bam

  Dataset EGAD00001007100

• A95626A

  Whole genome sequencing for single cells for library A95626A 1040 cells; filetype=bam

  Dataset EGAD00001007103

• A95634B

  Whole genome sequencing for single cells for library A95634B 1335 cells; filetype=bam

  Dataset EGAD00001007105

• A95646A

  Whole genome sequencing for single cells for library A95646A 1071 cells; filetype=bam

  Dataset EGAD00001007106

• A95653B

  Whole genome sequencing for single cells for library A95653B 1342 cells; filetype=bam

  Dataset EGAD00001007107

• A95663B

  Whole genome sequencing for single cells for library A95663B 1364 cells; filetype=bam

  Dataset EGAD00001007108

• A95675A

  Whole genome sequencing for single cells for library A95675A 668 cells; filetype=bam

  Dataset EGAD00001007109

• A95731B

  Whole genome sequencing for single cells for library A95731B 1307 cells; filetype=bam

  Dataset EGAD00001007110

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

• A96118A

  Whole genome sequencing for single cells for library A96118A 1193 cells; filetype=bam

  Dataset EGAD00001007113

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• A96178A

  Whole genome sequencing for single cells for library A96178A 788 cells; filetype=bam

  Dataset EGAD00001007115

• A96178B

  Whole genome sequencing for single cells for library A96178B 846 cells; filetype=bam

  Dataset EGAD00001007116

• A96181C

  Whole genome sequencing for single cells for library A96181C 1216 cells; filetype=bam

  Dataset EGAD00001007117

• A96225B

  Whole genome sequencing for single cells for library A96225B 959 cells; filetype=bam

  Dataset EGAD00001007119

• A96225C

  Whole genome sequencing for single cells for library A96225C 1034 cells; filetype=bam

  Dataset EGAD00001007120

• A96240A

  Whole genome sequencing for single cells for library A96240A 1493 cells; filetype=bam

  Dataset EGAD00001007121