3292 results for "ovarian cancer"

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• Exploiting evolutionary steering in cancer therapy

  Drug resistance, mediated by intra-tumour heterogeneity and clonal evolution, is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at the cost of increased sensitivity to another due to so-called evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, model systems able to recapitulate cancer evolution experimentally are lacking and current in vitro techniques based on small populations, re-plating and escalating dose, are unsuitable to develop evolutionary herding strategies. We present a novel methodology for evolutionary herding in vitro and ex vivo using patient-derived organoids. Our approach is based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, realistic high drug doses, time-course monitoring of cancer clones, and mathematical modelling of tumour evolutionary dynamics. We demonstrate evolutionary herding in non-small cell lung cancer in vitro and in patient-derived colorectal cancer organoids (PDO). We show that herding causes controlled evolutionary bottlenecks that lead to collateral sensitivity. Through genomic analysis, we were also able to determine the mechanisms that drive such sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can be translated into the clinic to control treatment resistance.

  Study EGAS00001003200

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• Genetic Basis of Breast Cancer Resistance in BRCA1 Mutation Carrier

  Our study addressed a specific question in NCI RFA-CA-12-022: "What underlying causal events - e.g., genetic, epigenetic, biologic, behavioral, or environmental - allow certain individuals to survive beyond the expected limits of otherwise highly lethal cancers?". A germline mutation in BRCA1 (BRCA1+) is the most penetrant genetic predisposition for breast cancer. Nevertheless, a portion of BRCA1+ carriers does not develop breast cancer in their lifetime, suggesting that the genetic predisposition can be antagonized by resistant factors. BRCA1+ was inherited from an ancestor of the carrier family thousand years ago. We hypothesize that evolution could select certain genetic components to suppress oncogenesis caused by the predisposition. We compared germline variants in all genes in 27 pairs of breast cancer-unaffected and -affected BRCA1+ carriers, each pair inherited the same BRCA1+. We identified 12 deleterious variants enriched in breast cancer-unaffected carriers, all are common variants. A variant rs3735400 is located in ANLN, a cytokinesis-essential gene. Overexpression of variant-containing ANLN and suppressed expression of endogenous ANLN decrease ANLN nuclear localization and delay cell growth. Our findings suggest that common variants can be selected to resist oncogenesis imposed by BRCA1+.

  Study phs001243

• The Somatic Mutational Landscape of Thyroid Cancer in Patients with Germline PTEN Mutations

  PTEN hamartoma tumor syndrome (PHTS) is associated with a high rate of thyroid cancer and benign thyroid disease, yet nothing is known of the genomic landscape of PHTS-associated thyroid tumors. In this study, exome sequencing was performed on 58 thyroid tumors (28 cancers, 30 benign nodules) from 19 patients with PHTS, sequenced in tumor-normal pairs. Somatic variant calling was utilized to determine the somatic mutational landscape of thyroid tumors in this population. This was then compared to the known mutational landscape of sporadic thyroid cancer in the general population using sequencing data from The Cancer Genome Atlas. The primary finding of the study was that PHTS-associated thyroid tumors had a unique genomic landscape, including a high frequency of second-hit somatic PTEN alterations compared to the sporadic thyroid tumors. Additionally, PHTS-associated thyroid cancers were found to have somatic alterations in BRAF, RAS family members, and genes associated with DNA double stranded break repair. Data available through dbGAP will include tumor BAM files for each tumor, normal BAM files for each patient, and MAF files for PHTS-associated thyroid cancer and PHTS associated benign thyroid nodules.

  Study phs003640

• Whole Mitochondrial Sequencing of Gingivo-buccal Cancer: ICGC-India Project

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Whole genome and other sequencing experiments are being performed at the National Institute of Biomedical Genomics, Kalyani. Whole mitochondria sequencing of 89 patients was performed in this study. The mean depth of sequencing was at least 2500X, but variable across platforms, 2689X and 9894X for amplicon sequencing in Ion Torrent PGM (Tumor-blood pairs=16) and Illumina HiSeq 2500 (Tumor-blood pairs =48), respectively; and, 14,190X for whole genome sequencing in Illumina HiSeq 2500 (Tumor-blood pairs =25). Associations of mutation data with important clinical aspects have been found.

  Study EGAS00001002425

• Evolutionary analysis of primary tumors and metastatic lesions from 20 breast cancer patients (99 samples in total) using exome sequencing data.

  Metastatic breast cancers are still incurable. Characterizing their evolutionary landscape including the role of metastatic axillary lymph nodes to seed distant organ metastasis can provide rational basis for effective treatments. Here, we describe the genomic analyses of the primary tumors and metastatic lesions from 20 breast cancer patients (99 samples). Our evolutionary analyses revealed diverse spreading and seeding patterns governing tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, where multiple metastatic subclones originated from primary tumor and/or other distant metastases. Synchronous axillary lymph node metastasis, a well-established prognosticator of breast cancer, was not involved in seeding distant metastasis, suggesting haematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably a significant increase in apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) associated mutagenesis. Our data provide the first genomic evidence regarding the role of axillary lymph node metastasis in seeding distant organ metastasis and elucidates the evolving mutational landscape during cancer progression.

  Study EGAS00001002737

• Polygenic Risk Score for the Prediction of Breast Cancer Is Related to Lesser Terminal Duct Lobular Unit Involution of the Breast

  The Susan G. Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center is an annotated biobank, which has recruited healthy women who provided demographic, lifestyle, and cancer-related information via self-administered questionnaire, blood samples and normal breast tissues. H&E slides of the normal breast tissues were scanned for image analysis and a pathologist measured the number of terminal duct lobular units (TDLUs) ("TDLU count"). The acini count per TDLU was quantified using the TDLU analyzer software. In this analysis, we computed the recently developed polygenic risk score (PRS) based on 313 common variants for the prediction of breast cancer and related this PRS to TDLU count and acini count per TDLU. We did this for the overall PRS, the ER-positive PRS and the ER-negative PRS.

  Study phs002062

• Notch Signaling and Efficacy PD-1/PD-L1 Blockade in Relapsed Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer that accounts for approximately 15% of all lung cancer, with an annual incidence of more than 34,000 in the United States alone. SCLC is characterized by loss of function of p53 and RB and high tumor mutational burden, which suggests that these tumors could be immunogenic and respond to immune checkpoint blockade (ICB). However, the benefit from ICB in an unselected SCLC population is modest. In this study, we evaluated the genomic features associated with clinical outcomes in relapsed SCLC to gain insight into the underlying mechanisms of ICB response. Exome, RNA and TCR sequencing data from a prospective clinical trial of relapsed SCLC treated with durvalumab and olaparib and RNA-sequencing data for second cohort of relapsed SCLC cohort treated with nivolumab are included.   

  Study phs002176

• A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. In this single arm, multi-institutional open label phase 2 clinical trial of alisertib, sixty men were treated with alisertib 50mg twice daily for 7 days every 21-days. Eligibility included metastatic prostate cancer and at least one: small cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; elevated serum neuroendocrine markers. The primary endpoint was six-month radiographic progression free survival. Pre-treatment biopsies were evaluated by whole exome and RNA-seq.

  Study phs001666