Plasma of cancer patients contains cell-free tumor DNA that carries information on tumor mutations and tumor burden. Individual mutations have been probed using allele-specific assays, but sequencing of entire genes to detect cancer mutations in circulating DNA has not been demonstrated. We developed a method for tagged-amplicon deep sequencing (TAm-Seq) and screened 5995 genomic bases for low-frequency mutations. Using this method, we identified cancer mutations present in circulating DNA at allele frequencies as low as 2%, with sensitivity and specificity of >97%. We identified mutations throughout the tumor suppressor gene TP53 in circulating DNA from 46 plasma samples of advanced ovarian cancer patients. We demonstrated use of TAm-Seq to noninvasively identify the origin of metastatic relapse in a patient with multiple primary tumors. In another case, we identified in plasma an EGFR mutation not found in an initial ovarian biopsy. We further used TAm-Seq to monitor tumor dynamics, and tracked 10 concomitant mutations in plasma of a metastatic breast cancer patient over 16 months. This low-cost, high-throughput method could facilitate analysis of circulating DNA as a noninvasive "liquid biopsy" for personalized cancer genomics.

Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on sensitivity for detecting genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for non-invasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 cancer patients using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90–150 bp, and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90–150 bp improved detection of tumor DNA, with more than 2-fold median enrichment in >95% of cases, and more than 4-fold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with AUC>0.99 compared to AUC<0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC>0.91, compared to AUC<0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cell-free DNA for clinical applications, earlier diagnosis and study of tumor biology.

Whole-transcriptome sequencing of four GCTs identified a single, recurrent somatic mutation (402C-->G) in FOXL2 that was present in almost all morphologically identified adult-type GCTs. Mutant FOXL2 is a potential driver in the pathogenesis of adult-type GCTs.

The peroxisome proliferator activated receptor (PPAR gamma) plays a key role in adipogenesis and adipocyte gene expression and is the receptor for the thiazolidinedione class of insulin-sensitizing drugs. The tissue expression and potential for regulation of human PPAR gamma gene expression in vivo are unknown. We have cloned a partial human PPAR gamma cDNA, and established an RNase protection assay that permits simultaneous measurements of both PPAR gamma1 and PPAR gamma2 splice variants. Both gamma1 and gamma2 mRNAs were abundantly expressed in adipose tissue. PPAR gamma1 was detected at lower levels in liver and heart, whereas both gamma1 and gamma2 mRNAs were expressed at low levels in skeletal muscle. To examine the hypothesis that obesity is associated with abnormal adipose tissue expression of PPAR gamma, we quantitated PPARgamma mRNA splice variants in subcutaneous adipose tissue of 14 lean and 24 obese subjects. Adipose expression of PPARgamma 2 mRNA was increased in human obesity (14.25 attomol PPAR gamma2/18S in obese females vs 9.9 in lean, P = 0.003). This increase was observed in both male and females. In contrast, no differences were observed in PPAR gamma1/18S mRNA expression. There was a strong positive correlation (r = 0.70, P < 0.001) between the ratio of PPAR gamma2/gamma1 and the body mass index of these patients. We also observed sexually dimorphic expression with increased expression of both PPAR gamma1 and PPAR gamma2 mRNAs in the subcutaneous adipose tissue of women compared with men. To determine the effect of weight loss on PPAR gamma mRNA expression, seven additional obese subjects were fed a low calorie diet (800 Kcal) until 10% weight loss was achieved. Mean expression of adipose PPAR gamma2 mRNA fell 25% (P = 0.0250 after a 10% reduction in body weight), but then increased to pretreatment levels after 4 wk of weight maintenance. Nutritional regulation of PPAR gamma1 was not seen. In vitro experiments revealed a synergistic effect of insulin and corticosteroids to induce PPAR gamma expression in isolated human adipocytes in culture. We conclude that: (a) human PPAR gamma mRNA expression is most abundant in adipose tissue, but lower level expression of both splice variants is seen in skeletal muscle; to an extent that is unlikely to be due to adipose contamination. (b) RNA derived from adipose tissue of obese humans has increased expression of PPAR gamma 2 mRNA, as well as an increased ratio of PPAR gamma2/gamma1 splice variants that is proportional to the BMI; (c) a low calorie diet specifically down-regulates the expression of PPAR gamma2 mRNA in adipose tissue of obese humans; (d) insulin and corticosteroids synergistically induce PPAR gamma mRNA after in vitro exposure to isolated human adipocytes; and (e) the in vivo modulation of PPAR gamma2 mRNA levels is an additional level of regulation for the control of adipocyte development and function, and could provide a molecular mechanism for alterations in adipocyte number and function in obesity.

The orphan nuclear receptor, peroxisome proliferator-activated receptor (PPAR) ␥ , is implicated in mediating expression of fat-specific genes and in activating the program of adipocyte differentiation. The potential for regulation of PPAR ␥ gene expression in vivo is unknown. We cloned a partial mouse PPAR ␥ cDNA and developed an RNase protection assay that permits simultaneous quantitation of mRNAs for both ␥ 1 and ␥ 2 isoforms encoded by the PPAR ␥ gene. Probes for detection of adipocyte P2, the obese gene product, leptin, and 18S mRNAs were also employed. Both ␥ 1 and ␥ 2 mRNAs were abundantly expressed in adipose tissue. PPAR ␥ 1 expression was also detected at lower levels in liver, spleen, and heart; whereas, ␥ 1 and ␥ 2 mRNA were expressed at low levels in skeletal muscle. Adipose tissue levels of ␥ 1 and ␥ 2 were not altered in two murine models of obesity (gold thioglucose and ob/ob), but were modestly increased in mice with toxigene-induced brown fat ablation uncoupling protein diphtheria toxin A mice. Fasting (12-48 h) was associated with an 80% fall in PPAR ␥ 2 and a 50% fall in PPAR ␥ 1 mRNA levels in adipose tissue. Western blot analysis demonstrated a marked effect of fasting to reduce PPAR ␥ protein levels in adipose tissue. Similar effects of fasting on PPAR ␥ mRNAs were noted in all three models of obesity. Insulin-deficient (streptozotocin) diabetes suppressed adipose tissue ␥ 1 and ␥ 2 expression by 75% in normal mice with partial restoration during insulin treatment. Levels of adipose tissue PPAR ␥ 2 mRNA were increased by 50% in normal mice exposed to a high fat diet. In obese uncoupling protein diphtheria toxin A mice, high fat feeding resulted in de novo induction of PPAR ␥ 2 expression in liver. We conclude (

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.

Background Ovarian cancer is a lethal disease comprised of distinct histopathological types. There are few established biomarkers of ovarian cancer prognosis, in part because subtype-specific associations may have been obscured in studies combining all subtypes. We examined whether progesterone receptor (PR) and estrogen receptor (ER) protein expression were associated with subtype-specific survival in the international Ovarian Tumor Tissue Analysis (OTTA) consortium. Methods PR and ER were assessed by central immunohistochemical analysis of tissue microarrays for 2933 women with invasive epithelial ovarian cancer from 12 study sites. Negative, weak, and strong expression were defined as positive staining in <1%, 1–50%, and ≥50% of tumor cell nuclei, respectively. Hazard ratios (HRs) for ovarian cancer death were estimated using Cox regression stratified by site and adjusted for age, stage, and grade. Results PR expression was associated with improved survival for endometrioid (EC; p<0·0001) and high-grade serous carcinoma (HGSC; p=0·0006), and ER expression was associated with improved EC survival (p<0·0001); no significant associations were found for mucinous, clear cell, or low-grade serous carcinoma. EC patients with hormone receptor (PR and/or ER) positive (weak or strong) versus negative tumors had significantly reduced risk of dying from their disease, independent of clinical factors (HR, 0·33; 95% CI, 0·21–0·51; p<0·0001). HGSC patients with strong versus weak or negative tumor PR expression had significantly reduced risk of dying from their disease, independent of clinical factors (HR, 0·71; 95% CI, 0·55–0·91; p=0·0061). Interpretation PR and ER are prognostic biomarkers for endometrioid and high-grade serous ovarian cancers. Clinical trials, stratified by subtype and biomarker status, are needed to determine whether hormone receptor status predicts response to endocrine therapy, and can guide personalized treatment for ovarian cancer. Funding Carraressi Foundation, US National Institutes of Health, National Health and Medical Research Council of Australia, UK National Institute for Health Research, and others.

The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated dense single-cell and spatial reference maps of the human uterus and three-dimensional endometrial organoid cultures. We dissect the signaling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids reveals the pathways and cell states regulating differentiation of the secretory and ciliated lineages both in vivo and in vitro. In vitro downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. We utilize our cellular maps to deconvolute bulk data from endometrial cancers and endometriotic lesions, illuminating the cell types dominating in each of these disorders. These mechanistic insights provide a platform for future development of treatments for common conditions including endometriosis and endometrial carcinoma.