More than a third of women develop ovarian cysts during their lifetimes. The vast majority of these cysts are harmless, but a small number are caused by ovarian cancers. These cancers often produce no symptoms until the disease has spread throughout the abdomen or to other organs, so many women go undiagnosed until their chances of being successfully treated are low. Currently, there is no reliable way to determine whether an ovarian cyst is cancerous without performing surgery. As a result, many women undergo unnecessary, invasive surgeries for harmless ovarian cysts.

Tumors shed cells and cell fragments into any fluid that surrounds them. Fluids from cysts in the pancreas, kidney, and thyroid are routinely examined to identify whether they contain cancerous cells. Now, Wang, Sundfeldt et al. show that ovarian cancers also shed DNA into the surrounding cyst fluid. Furthermore, mutations found in this DNA can provide valuable information about whether the cysts are cancerous.

The study was performed by extracting DNA from the fluid in ovarian cysts that had been surgically removed from 77 women. Of these cysts, 10 were harmless cysts, 12 were benign tumors, 31 were invasive cancers, and 24 were so-called borderline tumors, which fall somewhere between the benign tumors and invasive cancers. Only cysts associated with the borderline tumors and invasive cancers need to be surgically removed. Here, Wang, Sundfeldt et al. report that DNA mutations that are characteristic of ovarian cancers were found in 87% of the cysts associated with borderline tumors and invasive cancers. In contrast, these mutations were not found in any of the cysts that do not require surgery.

Fluid can be extracted from an ovarian cyst with a needle during an outpatient visit. Therefore, the results presented by Wang, Sundfeldt et al. suggest a relatively straightforward way of testing the DNA from ovarian cysts before deciding whether surgery is really necessary. First, however, larger studies that follow women with cysts over time will be necessary to confirm that this type of testing is effective and safe.

Ovarian cancer is the most lethal gynecologic malignancy, with 21,290 estimated new cases and 14,180 estimated deaths in the United States in 2015. Approximately 1.3% of women will be diagnosed with ovarian cancer during their lifetime (Howlader et al., 2014). These cancers commonly present as an adnexal mass with cystic components, but are not associated with specific symptoms. As a result, two-thirds of ovarian cancers are diagnosed at late stage (Stage III or IV), when the 5-year survival is less than 30% (Howlader et al., 2014)

Complicating the diagnosis of ovarian cancer is the fact that ovarian cysts are common in women of all ages, with a prevalence of 35% and 17% in pre- and post-menopausal women, respectively (Pavlik et al., 2013). These cysts are frequently benign and found incidentally on routine imaging (Pavlik et al., 2013). Though malignancy is an unusual cause of the cysts, 30% of the cysts exhibit radiographic features suspicious for malignancy, such as solid areas or mass (Pavlik et al., 2013). In addition to the anxiety that such findings provoke, many women undergo unnecessary surgery for cysts that are not malignant and may not be responsible for the symptoms they have. For example, only 5% of 570 women in a large ovarian cancer screening randomized trial who underwent surgical evaluation actually had a malignancy (Buys et al., 2005). Similarly in another study of symptomatic women, only 4% of 197 women who had concerning features on transvaginal ultrasound were ultimately diagnosed with ovarian cancer (Gilbert et al., 2012). Compounding this issue is the fact that surgery for ovarian cysts requires general anesthesia and is associated with significant morbidity, causing complications in 15% of women (Buys et al., 2011). These complications include damage to nerves and ureters, bleeding, infection, and perforation of adjacent viscera. Furthermore, the procedure often results in hormonal and fertility loss (in the case of bilateral oophorectomy) (Buys et al., 2011). Even minimal procedures such as ovarian cystectomy can affect fertility in premenopausal women by decreasing follicular response and oocyte number (Loh et al., 1999; Demirol et al., 2006). If a preoperative test could help determine whether the cystic lesion was benign or malignant, unnecessary surgery and its associated complications could be avoided in many patients. This would be particularly helpful for women of reprodutive age who wish to preserve their fertility, as well as women whose medical comorbidities or functional status makes anesthesia and surgery hazardous.

Ovarian cysts and tumors are classified as non-neoplastic, benign, borderline, or malignant based on microscopic examination after surgical removal (Figure 1). Non-neoplastic cysts are by far the most common class of ovarian cysts. They are frequently found in pre-menopausal women, arising when an egg is not released properly from either the follicle or corpus luteum and usually resolve spontaneously within several months (Christensen et al., 2002). Benign cystic tumors, such as cystadenomas and cystadenofibromas, rarely progress to malignancy (Cheng et al., 2004; Levine et al., 2010). No genetic alterations have yet been identified in either non-neoplastic cysts or in benign cystic tumors (Cheng et al., 2004). Neither of these cyst types requires surgery unless they are symptomatic or large (Levine et al., 2010). These cysts can be easily sampled with ultrasound-guided fine-needle aspiration within minutes in an outpatient setting without the need for anesthesia (Duke et al., 2006).

Figure 1

Download asset Open asset

At the other end of the spectrum are epithelial ovarian cancers, which are potentially lethal and unequivocally require surgery. A dualistic model has been proposed to classify these neoplasms (Kurman and Shih, 2010). Type I tumors are composed of low-grade serous, low-grade endometrioid, clear cell, and mucinous carcinomas. They are generally indolent, frequently diagnosed at early stage (Stage I or II), and develop from well-established precursor lesions ('borderline' or 'atypical proliferative' tumors, as described below) (Kurman and Shih, 2011). Type I cancers commonly exhibit mutations in KRAS, BRAF, CTNNB1, PIK3CA, PTEN, ARID1A, or PPP2R1A (Kurman and Shih, 2010). In contrast, type II tumors are generally high-grade serous carcinomas. They are highly aggressive, most often diagnosed in late stage (Stage III or IV), and have suggested origins from the distal fallopian tube (Lee et al., 2007). Type II cancers are the most clinically important group of ovarian cancers, comprising 75% of all ovarian carcinomas and responsible for 90% of ovarian cancer deaths (Kurman and Shih, 2011). They almost always harbor TP53 mutations (Cancer Genome Atlas Research Network. 2011). Also unlike type I cancers, which are relatively chemo-resistant and more often treated only with surgical excision, type II cancers respond to conventional chemotherapy, particularly after maximal debulking to reduce tumor burden (Bristow et al., 2002; Schmeler et al., 2008).

'Borderline' or 'atypical proliferative' tumors lie in the middle of this spectrum, between the malignant cancers and the generally harmless non-neoplastic or benign lesions. They are distinguished from carcinomas by the absence of stromal invasion and are precursors of type I cancers. In light of their potential for malignancy, the standard of care for borderline tumors is surgical excision. Following surgery, the prognosis is excellent compared to ovarian cancers, with 10-year survival rates over 94% (Sherman et al., 2004). A minor but significant portion of borderline tumors recur after surgery, however, and a subset of the recurrences are found to have advanced to type I cancers (Shih et al., 2011). This progression is consistent with molecular findings: serous borderline tumors typically exhibit mutations in BRAF or KRAS, like their malignant counterparts (low-grade serous carcinoma) (Mayr et al., 2006; Jones et al., 2012). The presence of a BRAF mutation in a borderline tumor is associated with better prognosis and a low probability of progression to carcinoma (Grisham et al., 2013). In contrast, KRAS mutations are associated with the progression to type I cancers (Tsang et al., 2013).

The examination of fluids from pancreatic, renal, and thyroid cysts is routinely used in clinical management (Frossard et al., 2003; Lin et al., 2005; Volpe et al., 2007). The fluids have historically been studied by cytology to identify malignant cysts. Ovarian cysts share many features with these other types of cysts, in that they are common, often diagnosed incidentally, and are nearly always benign. However, aspiration of ovarian cyst fluid for cytology is not standard-of-care. From a historical perspective, the difference in diagnostic management partly lies in the fact that cytology has not proven to be very informative for ovarian cysts, particularly for distinguishing benign vs. borderline tumors (Moran et al., 1993; Martínez-Onsurbe et al., 2001). There have also been concerns raised about the safety of ovarian cyst aspiration (see Discussion), and these concerns have not often been raised for other types of cysts.

More recently, genetic analysis of specific types of cyst fluids has been considered as an aid to cytology, given that conventional cytology often has limited sensitivity and specificity (Wu et al., 2011b). Based on the emerging success of the molecular genetic evaluation of other types of cysts, we reasoned that a similar approach could be applied to ovarian cysts. Evaluation of DNA from cells and cell fragments shed into the cyst fluid would presumably allow the identification of tumor-specific mutations. Unlike other, conventional markers of neoplasia such as CA-125, cancer gene mutations are exquisitely specific indicators of a neoplastic lesion (Vogelstein et al., 2013). Moreover, the type of mutation can in some cases indicate the type of neoplastic lesion present (Wu et al., 2011a). Yamada et al. have demonstrated that mutations can be detected in the cystic fluid of ovarian tumors by querying exons 4 to 9 of TP53, achieving sensitivities of 12.5% and 10%, for borderline and malignant tumors, respectively (Yamada et al., 2013). Recently developed, extremely sensitive methods for mutation detection, capable of identifying one mutant template allele among thousands of normal templates in a panel of genes, could potentially increase this sensitivity (Kinde et al., 2011; Murtaza et al., 2013; Newman et al., 2014). In this study, we have applied one of these technologies to assess mutations in ovarian cyst fluids and to inform the development of tests that could eventually be applied to patients.

Ovarian cancer is the most lethal gynecologic cancer in women. However screening is not recommended by the U.S. Preventive Services Task Force using current diagnostic approaches, which too frequently lead to “important harms, including major surgical interventions in women who do not have cancer” (Moyer and Force, 2012). Our study was driven by the underlying principle that clonal cancer driver gene mutations are causative agents of neoplasia and absent in non-neoplastic conditions (Vogelstein et al., 2013). We have demonstrated here that driver mutations in ovarian tumors are also present in their associated cyst fluids. Moreover, the mutant allele frequencies in the cyst fluids are relatively high (median 12.6%, IQR of 2.7% to 40.2%), facilitating their detection. There were no mutations detected in the cyst fluids that were not also present in the tumors, and vice versa. Also importantly, no mutation was identified in non-neoplastic cysts or cysts associated with benign tumors. Overall, mutations were detected in a major fraction (87%) of cysts requiring surgery but not in any cyst that did not require surgery (Table 1).

Although most (87%) of the 54 cysts requiring surgery had detectable mutations in their fluidic compartment, 7 did not. All of these seven cysts occurred in borderline tumors or type I cancers, while mutations were always (100%) detectable in type II cancers (Table 1). There are two potential explanations for our failure to detect mutations in these seven cysts. First, it is possible that the mutant DNA concentration in these cysts was below the level of technical sensitivity of our assay (~0.1% mutant allele fraction). We excluded this possibility by evaluating the tumors themselves: no mutations were detected in any of the tumors from these 7 patients. The second, and therefore more likely explanation, is that our panel of 133 amplicons, containing regions of 17 genes, was not adequate to capture the mutations that were present. Unlike type II cancers, which nearly always contain TP53 mutations (94% of the type II cancers we studied, for example), the genomic landscapes of type I cancers and borderline tumors are more heterogeneous and not as well studied (Kurman and Shih, 2010). Further genetic evaluation of these tumors should facilitate the incorporation of additional amplicons in the panel to reach higher sensitivities. Nevertheless, the 100% sensitivity for type II cancers in our study is highly encouraging, given that these cancers account for over 90% of ovarian cancer deaths.

One limitation of our study is the number of patients evaluated. Though excision of ovarian cysts is one of the most commonly performed surgical procedures, banking of cyst fluids is not common, even in academic centers. Thus, we only had relatively small numbers (n = 22) of non-neoplastic cysts and benign tumors available for study. Even so, the differences in genetic alterations among the various cyst types were striking (Table 1). Our study will hopefully stimulate collection and analyses of ovarian cyst fluids that will be able to establish smaller confidence limits around the sensitivities and specificities reported in the current study.

A potential clinical limitation of our approach is the concern by gynecologists that needle puncture of a malignant ovarian cyst leads to seeding of the peritoneum. This concern is based on inconclusive evidence about the dangers of cyst rupture during surgery and is, at best, controversial. A study of 235 patients who had pre-operative ovarian cyst aspirates reported no recurrence in all 7 malignant cases with a mean follow-up of two years (Mulvany, 1996). Furthermore, a meta-analysis found no difference in progression-free survival for 2382 early-stage ovarian cancer patients who had experienced intraoperative cyst rupture vs. no rupture (Kim et al., 2013). We acknowledge that, under current recommendations, a surgical spill could upstage a localized tumor (i.e. stage 1A to IC) and subject the patient to chemotherapy with its associated morbidity. However, the idea that malignant cysts might shed cancer cells if needle-punctured seems incongruent with the widespread practice of laparoscopic removal of ovarian cysts (Hilger et al., 2006). Laparoscopic removal of a cyst carries a significant risk of cyst rupture, conceivably higher than when a tiny needle is inserted under ultrasound-guidance (Havrilesky et al., 2003). Finally, malignant pancreatic cysts might be viewed to be as dangerous as malignant ovarian cysts (Howlader et al., 2014), yet the standard-of-care for pancreatic cysts involves repeated sampling of cyst fluid through endoscopic ultrasound over many years (Chang et al., 1997; Eloubeidi et al., 2003). Though pancreatic cysts and ovarian cysts lie in different anatomical compartments, it is encouraging that aspiration of pancreatic cysts is not associated with an increased risk of disease recurrence or mortality in patients with pancreatic cancer (Beane et al., 2011; Ngamruengphong et al., 2013; Kudo et al., 2014; Ngamruengphong et al., 2015). Recent advancements in methods of plugging biopsy tracts to prevent tumor cell dissemination, as well as the increased use of intraperitoneal chemotherapy, further lessen the concern of tumor cell dissemination following ovarian cyst aspiration (Armstrong et al., 2006; Tran et al., 2014; Tsang et al., 2014; Tewari et al., 2015). On the basis of these observations and recent developments, we believe that ultrasound-guided aspiration of ovarian cyst fluids would likely be a safe and well-tolerated procedure.

As noted in the introduction, as many as twenty patients with benign ovarian cyst lesions undergo surgery for each case of ovarian cancer found (Buys et al., 2005). In addition to the psychological impact a potential diagnosis of cancer has on patients, surgery for benign lesions entails considerable cost and morbidity. With the ever increasing sensitivity and use of imaging modalities, the number of patients with incidentally found ovarian cysts is expected to rise. This urgently calls for a diagnostic method that reliably differentiates between the harmless cysts that can be managed expectantly and malignant cysts that require surgical resection. OVA-1 is the only FDA-cleared test to date that aims to distinguish benign versus malignant adenxal mass. It measures levels of five serum markers (CA-125, β-2 microglobulin, apolipoprotein A1, Prealbumin, and transferrin) and is used to stratify patients who should consult a gynecologic oncologist rather than a general gynecologist for surgery. However the test has a specificity of 43% for ovarian cancer, which is even lower than that of CA-125 alone (Ueland et al., 2011). While the test might encourage patients with suspected ovarian cancer to seek specialized care, it would not decrease the number of unnecessary surgeries for women with benign adnexal masses.

This study was driven by the need for a biomarker that would help distinguish malignant ovarian tumors from benign lesions and thereby reduce the number of unnecessary surgeries. Such distinction is often difficult based on symptoms and conventional diagnostic criteria. For example, in a large study of 48,053 asymptomatic postmenopausal women who underwent ultrasound examination by skilled sonographers, 8 (17%) of the 47 ovarian cancers that were identified occurred in women with persistently normal sonographic findings (Sharma et al., 2012). All eight cases were type II cancers, highlighting the potential utility of an additional assay to detect this highly lethal and aggressive type of ovarian cancer. On the other hand, of the 4367 women with abnormal sonographic findings, less than 1% of cases proved to have malignancy upon surgery. Furthermore, of the 32 women with borderline or Type I cancers diagnosed, 22 (69%) had a serum CA-125 level within the clinically accepted normal range (≤35 units/mL). In our study, 18 of 18 (100%) type II cancers were detectable by virtue of the mutations found in cyst fluid DNA while none of the 18 benign or non-neoplastic cyst fluid contained such mutations. It is also important to note that the readout of our assay is quantitative and not dependent on the skill level of the reader (in contrast to sonography). Finally, the procedure can be performed minimally invasively in an outpatient setting. The goal of our test is not to replace clinical, radiologic, or sonographic evaluation but to augment them with molecular genetic markers.

Our study, though only proof-of-principle, illustrates one route to improve the management of patients with ovarian cysts. Genetic analysis is not the only such route; proteomics could also provide clues to the correct diagnosis (Bandiera et al., 2013; Kristjansdottir et al., 2013). One can easily imagine how such additional information could be used to inform clinical practice in conjunction with current diagnostic approaches. For example, if a cyst contained low amounts of DNA, no detectable mutations, and if the patient had low CA-125 levels, our data suggest that it is very unlikely to be a borderline tumor or malignant lesion. Either no surgery, or laparoscopic rather than open surgery, could be recommended for that patient, even if there were some solid component upon imaging. The option to avoid surgery would be particularly valuable for pre-menopausal women who generally have a low risk of ovarian cancer and might wish to preserve their fertility, as well as patients who are poor surgical candidates. However, our assay in its current format cannot completely rule out malignancy because a fraction of early-stage cancer patients did not have detectable mutations in their cysts. Therefore, patients whose clinical and functional status allows them to undergo surgery and anesthesia might still choose to have a surgical procedure. On the other hand, a minimally invasive test that provides additional, orthogonal information to patients and surgeons could inform their decision about the advisability of surgery.

Our data suggest that a cyst without any solid component upon imaging, and thereby unlikely via conventional criteria to be malignant, should be removed promptly if the cyst fluid contained a TP53 mutation. Radical, rather than conservative, surgery might be appropriate due to the high likelihood of an aggressive type II cancer. In contrast, if a BRAF mutation is identified, the lesion is presumably a borderline or low-grade tumor; thus conservative rather than radical surgery might be sufficient. Furthermore, given that certain types of ovarian cancers (type II) tend to respond well to chemotherapy while others (type I) are relatively chemo-resistant, knowing the type of cancer present prior to surgery based on the mutation profile could help guide decisions regarding the use of neoadjuvant chemotherapy. Validation of the current data in a large, prospective trial will be required before the approach can be seriously considered for clinical implementation in a non-research setting.

1. 1. Armstrong DK
   2. Bundy B
   3. Wenzel L
   4. Huang HQ
   5. Baergen R
   6. Lele S
   7. Copeland LJ
   8. Walker JL
   9. Burger RA
   10. Gynecologic Oncology G
   11. Gynecologic Oncology Group

   (2006) Intraperitoneal cisplatin and paclitaxel in ovarian cancer

   New England Journal of Medicine 354:34–43.

   https://doi.org/10.1056/NEJMoa052985

   • Google Scholar
2. 1. Bandiera E
   2. Zanotti L
   3. Fabricio AS
   4. Bucca E
   5. Squarcina E
   6. Romani C
   7. Tassi R
   8. Bignotti E
   9. Todeschini P
   10. Tognon G
   11. Romagnolo C
   12. Gion M
   13. Sartori E
   14. Maggino T
   15. Pecorelli S
   16. Ravaggi A

   (2013) Cancer antigen 125, human epididymis 4, kallikrein 6, osteopontin and soluble mesothelin-related peptide immunocomplexed with immunoglobulin M in epithelial ovarian cancer diagnosis

   Clinical Chemistry and Laboratory Medicine 51:1815–1824.

   https://doi.org/10.1515/cclm-2013-0151

   • Google Scholar
3. 1. Barollo S
   2. Pezzani R
   3. Cristiani A
   4. Redaelli M
   5. Zambonin L
   6. Rubin B
   7. Bertazza L
   8. Zane M
   9. Mucignat-Caretta C
   10. Bulfone A
   11. Pennelli G
   12. Casal Ide E
   13. Pelizzo MR
   14. Mantero F
   15. Moro S
   16. Mian C

   (2014) Prevalence, tumorigenic role, and biochemical implications of rare BRAF alterations

   Thyroid 24:809–819.

   https://doi.org/10.1089/thy.2013.0403

   • Google Scholar
4. 1. Bast RC
   2. Klug TL
   3. St John E
   4. Jenison E
   5. Niloff JM
   6. Lazarus H
   7. Berkowitz RS
   8. Leavitt T
   9. Griffiths CT
   10. Parker L
   11. Zurawski VR
   12. Knapp RC

   (1983) A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer

   New England Journal of Medicine 309:883–887.

   https://doi.org/10.1056/NEJM198310133091503

   • Google Scholar
5. 1. Beane JD
   2. House MG
   3. Coté GA
   4. DeWitt JM
   5. Al-Haddad M
   6. LeBlanc JK
   7. McHenry L
   8. Sherman S
   9. Schmidt CM
   10. Zyromski NJ
   11. Nakeeb A
   12. Pitt HA
   13. Lillemoe KD

   (2011) Outcomes after preoperative endoscopic ultrasonography and biopsy in patients undergoing distal pancreatectomy

   Surgery 150:844–853.

   https://doi.org/10.1016/j.surg.2011.07.068

   • Google Scholar
6. 1. Bettegowda C
   2. Sausen M
   3. Leary RJ
   4. Kinde I
   5. Wang Y
   6. Agrawal N
   7. Bartlett BR
   8. Wang H
   9. Luber B
   10. Alani RM
   11. Antonarakis ES
   12. Azad NS
   13. Bardelli A
   14. Brem H
   15. Cameron JL
   16. Lee CC
   17. Fecher LA
   18. Gallia GL
   19. Gibbs P
   20. Le D
   21. Giuntoli RL
   22. Goggins M
   23. Hogarty MD
   24. Holdhoff M
   25. Hong SM
   26. Jiao Y
   27. Juhl HH
   28. Kim JJ
   29. Siravegna G
   30. Laheru DA
   31. Lauricella C
   32. Lim M
   33. Lipson EJ
   34. Marie SK
   35. Netto GJ
   36. Oliner KS
   37. Olivi A
   38. Olsson L
   39. Riggins GJ
   40. Sartore-Bianchi A
   41. Schmidt K
   42. Oba-Shinjo SM
   43. Siena S
   44. Theodorescu D
   45. Tie J
   46. Antonarakis ES
   47. Veronese S
   48. Wang Y
   49. Weingart JD
   50. Wolfgang CL
   51. Wood LD
   52. Xing D
   53. Hruban RH
   54. Wu J
   55. Allen PJ
   56. Schmidt CM
   57. Choti MA
   58. Velculescu VE
   59. Oliner KS
   60. Vogelstein B
   61. Papadopoulos N
   62. Diaz LA
   63. lM S

   (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies

   Science Translational Medicine 6:224ra24.

   https://doi.org/10.1126/scitranslmed.3007094

   • Google Scholar
7. 1. Bristow RE
   2. Tomacruz RS
   3. Armstrong DK
   4. Trimble EL
   5. Montz FJ

   (2002) Survival effect of maximal cytoreductive surgery for advanced ovarian carcinoma during the platinum era: a meta-analysis

   Journal of Clinical Oncology 20:1248–1259.

   https://doi.org/10.1200/JCO.20.5.1248

   • Google Scholar
8. 1. Buys SS
   2. Partridge E
   3. Greene MH
   4. Prorok PC
   5. Reding D
   6. Riley TL
   7. Hartge P
   8. Fagerstrom RM
   9. Ragard LR
   10. Chia D
   11. Izmirlian G
   12. Fouad M
   13. Johnson CC
   14. Gohagan JK
   15. Team PP
   16. PLCO Project Team

   (2005) Ovarian cancer screening in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial: findings from the initial screen of a randomized trial

   American Journal of Obstetrics and Gynecology 193:1630–1639.

   https://doi.org/10.1016/j.ajog.2005.05.005

   • Google Scholar
9. 1. Buys SS
   2. Partridge E
   3. Black A
   4. Johnson CC
   5. Lamerato L
   6. Isaacs C
   7. Reding DJ
   8. Greenlee RT
   9. Yokochi LA
   10. Kessel B
   11. Crawford ED
   12. Church TR
   13. Andriole GL
   14. Weissfeld JL
   15. Fouad MN
   16. Chia D
   17. O'Brien B
   18. Ragard LR
   19. Clapp JD
   20. Rathmell JM
   21. Riley TL
   22. Hartge P
   23. Pinsky PF
   24. Zhu CS
   25. Izmirlian G
   26. Kramer BS
   27. Miller AB
   28. Xu JL
   29. Prorok PC
   30. Gohagan JK
   31. Berg CD
   32. Xu PC
   33. Gohagan CDB
   34. Team PP
   35. PLCO Project Team

   (2011) Effect of screening on ovarian cancer mortality: the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening randomized controlled trial

   Journal of the American Medical Association 305:2295–2303.

   https://doi.org/10.1001/jama.2011.766

   • Google Scholar
10. 1. Cancer Genome Atlas Research Network

    (2011) Integrated genomic analyses of ovarian carcinoma

    Nature 474:609–615.

    https://doi.org/10.1038/nature10166

    • Google Scholar
11. 1. Chang KJ
    2. Nguyen P
    3. Erickson RA
    4. Durbin TE
    5. Katz KD

    (1997) The clinical utility of endoscopic ultrasound-guided fine-needle aspiration in the diagnosis and staging of pancreatic carcinoma

    Gastrointestinal Endoscopy 45:387–393.

    https://doi.org/10.1016/S0016-5107(97)70149-4

    • Google Scholar
12. 1. Cheng EJ
    2. Kurman RJ
    3. Wang M
    4. Oldt R
    5. Wang BG
    6. Berman DM
    7. Shih I

    (2004) Molecular genetic analysis of ovarian serous cystadenomas

    Laboratory Investigation 84:778–784.

    https://doi.org/10.1038/labinvest.3700103

    • Google Scholar
13. 1. Christensen JT
    2. Boldsen JL
    3. Westergaard JG

    (2002) Functional ovarian cysts in premenopausal and gynecologically healthy women

    Contraception 66:153–157.

    https://doi.org/10.1016/S0010-7824(02)00353-0

    • Google Scholar
14. 1. Cruz F
    2. Rubin BP
    3. Wilson D
    4. Town A
    5. Schroeder A
    6. Haley A
    7. Bainbridge T
    8. Heinrich MC
    9. Corless CL

    (2003)

    Absence of BRAF and NRAS mutations in uveal melanoma

    Cancer Research 63:5761–5766.

    • Google Scholar
15. 1. Davies H
    2. Bignell GR
    3. Cox C
    4. Stephens P
    5. Edkins S
    6. Clegg S
    7. Teague J
    8. Woffendin H
    9. Garnett MJ
    10. Bottomley W
    11. Davis N
    12. Dicks E
    13. Ewing R
    14. Floyd Y
    15. Gray K
    16. Hall S
    17. Hawes R
    18. Hughes J
    19. Kosmidou V
    20. Menzies A
    21. Mould C
    22. Parker A
    23. Stevens C
    24. Watt S
    25. Hooper S
    26. Wilson R
    27. Jayatilake H
    28. Gusterson BA
    29. Cooper C
    30. Shipley J
    31. Hargrave D
    32. Pritchard-Jones K
    33. Maitland N
    34. Chenevix-Trench G
    35. Riggins GJ
    36. Bigner DD
    37. Palmieri G
    38. Cossu A
    39. Flanagan A
    40. Nicholson A
    41. Ho JW
    42. Leung SY
    43. Yuen ST
    44. Weber BL
    45. Seigler HF
    46. Darrow TL
    47. Paterson H
    48. Marais R
    49. Marshall CJ
    50. Wooster R
    51. Stratton MR
    52. Futreal PA

    (2002) Mutations of the BRAF gene in human cancer

    Nature 417:949–954.

    https://doi.org/10.1038/nature00766

    • Google Scholar
16. 1. Demirol A
    2. Guven S
    3. Baykal C
    4. Gurgan T

    (2006) Effect of endometrioma cystectomy on IVF outcome: a prospective randomized study

    Reproductive Biomedicine Online 12:639–643.

    https://doi.org/10.1016/S1472-6483(10)61192-3

    • Google Scholar
17. 1. Duke D
    2. Colville J
    3. Keeling A
    4. Broe D
    5. Fotheringham T
    6. Lee MJ

    (2006) Transvaginal aspiration of ovarian cysts: long-term follow-up

    Cardiovascular and Interventional Radiology 29:401–405.

    https://doi.org/10.1007/s00270-005-0167-0

    • Google Scholar
18. 1. Eloubeidi MA
    2. Chen VK
    3. Eltoum IA
    4. Jhala D
    5. Chhieng DC
    6. Jhala N
    7. Vickers SM
    8. Wilcox CM

    (2003) Endoscopic ultrasound-guided fine needle aspiration biopsy of patients with suspected pancreatic cancer: diagnostic accuracy and acute and 30-day complications

    American Journal of Gastroenterology 98:2663–2668.

    https://doi.org/10.1111/j.1572-0241.2003.08666.x

    • Google Scholar
19. 1. Frossard JL
    2. Amouyal P
    3. Amouyal G
    4. Palazzo L
    5. Amaris J
    6. Soldan M
    7. Giostra E
    8. Spahr L
    9. Hadengue A
    10. Fabre M

    (2003) Performance of endosonography-guided fine needle aspiration and biopsy in the diagnosis of pancreatic cystic lesions

    American Journal of Gastroenterology 98:1516–1524.

    https://doi.org/10.1111/j.1572-0241.2003.07530.x

    • Google Scholar
20. 1. Gilbert L
    2. Basso O
    3. Sampalis J
    4. Karp I
    5. Martins C
    6. Feng J
    7. Piedimonte S
    8. Quintal L
    9. Ramanakumar AV
    10. Takefman J
    11. Grigorie MS
    12. Artho G
    13. Krishnamurthy S
    14. Group DOS
    15. DOvE Study Group

    (2012) Assessment of symptomatic women for early diagnosis of ovarian cancer: results from the prospective DOvE pilot project

    Lancet. Oncology 13:285–291.

    https://doi.org/10.1016/S1470-2045(11)70333-3

    • Google Scholar
21. 1. Grisham RN
    2. Iyer G
    3. Garg K
    4. DeLair D
    5. Hyman DM
    6. Zhou Q
    7. Iasonos A
    8. Berger MF
    9. Dao F
    10. Spriggs DR
    11. Levine DA
    12. Aghajanian C
    13. Solit DB

    (2013) BRAF mutation is associated with early stage disease and improved outcome in patients with low-grade serous ovarian cancer

    Cancer 119:548–554.

    https://doi.org/10.1002/cncr.27782

    • Google Scholar
22. 1. Havrilesky LJ
    2. Peterson BL
    3. Dryden DK
    4. Soper JT
    5. Clarke-Pearson DL
    6. Berchuck A

    (2003) Predictors of clinical outcomes in the laparoscopic management of adnexal masses

    Obstetrics and Gynecology 102:243–251.

    https://doi.org/10.1097/00006250-200308000-00008

    • Google Scholar
23. 1. Hellström I
    2. Raycraft J
    3. Hayden-Ledbetter M
    4. Ledbetter JA
    5. Schummer M
    6. McIntosh M
    7. Drescher C
    8. Urban N
    9. Hellström KE

    (2003)

    The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma

    Cancer Research 63:3695–3700.

    • Google Scholar
24. 1. Hilger WS
    2. Magrina JF
    3. Magtibay PM

    (2006) Laparoscopic management of the adnexal mass

    Clinical Obstetrics and Gynecology 49:535–548.

    https://doi.org/10.1097/00003081-200609000-00013

    • Google Scholar
25. Book

    1. Howlader N
    2. Krapcho M
    3. Garshell J
    4. Miller D
    5. Altekruse SF
    6. Kosary CL
    7. Yu M
    8. Ruhl J
    9. Tatalovich Z
    10. Mariotto A
    11. Lewis DR
    12. Chen HS
    13. Feuer EJ
    14. Cronin KA

    (2014)

    SEER Cancer Statistics Review, 1975-2011

    Bethesda, MD: National Cancer Institute.

    • Google Scholar
26. 1. Jones S
    2. Wang TL
    3. Kurman RJ
    4. Nakayama K
    5. Velculescu VE
    6. Vogelstein B
    7. Kinzler KW
    8. Papadopoulos N
    9. Shih I

    (2012) Low-grade serous carcinomas of the ovary contain very few point mutations

    Journal of Pathology 226:413–420.

    https://doi.org/10.1002/path.3967

    • Google Scholar
27. 1. Kim HS
    2. Ahn JH
    3. Chung HH
    4. Kim JW
    5. Park NH
    6. Song YS
    7. Lee HP
    8. Kim YB

    (2013) Impact of intraoperative rupture of the ovarian capsule on prognosis in patients with early-stage epithelial ovarian cancer: a meta-analysis

    European Journal of Surgical Oncology 39:279–289.

    https://doi.org/10.1016/j.ejso.2012.12.003

    • Google Scholar
28. 1. Kinde I
    2. Wu J
    3. Papadopoulos N
    4. Kinzler KW
    5. Vogelstein B

    (2011) Detection and quantification of rare mutations with massively parallel sequencing

    Proceedings of the National Academy of Sciences of the United States of America 108:9530–9535.

    https://doi.org/10.1073/pnas.1105422108

    • Google Scholar
29. 1. Kinde I
    2. Bettegowda C
    3. Wang Y
    4. Wu J
    5. Agrawal N
    6. Shih I
    7. Kurman R
    8. Dao F
    9. Levine DA
    10. Giuntoli R
    11. Roden R
    12. Eshleman JR
    13. Carvalho JP
    14. Marie SK
    15. Papadopoulos N
    16. Kinzler KW
    17. Vogelstein B
    18. Diaz LA

    (2013) Evaluation of DNA from the Papanicolaou test to detect ovarian and endometrial cancers

    Science Translational Medicine 5:167ra4.

    https://doi.org/10.1126/scitranslmed.3004952

    • Google Scholar
30. 1. Kristjansdottir B
    2. Levan K
    3. Partheen K
    4. Carlsohn E
    5. Sundfeldt K

    (2013) Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis, iTRAQ

    Clinical Proteomics 10:4.

    https://doi.org/10.1186/1559-0275-10-4

    • Google Scholar
31. 1. Kudo T
    2. Kawakami H
    3. Kuwatani M
    4. Eto K
    5. Kawahata S
    6. Abe Y
    7. Onodera M
    8. Ehira N
    9. Yamato H
    10. Haba S
    11. Kawakubo K
    12. Sakamoto N

    (2014) Influence of the safety and diagnostic accuracy of preoperative endoscopic ultrasound-guided fine-needle aspiration for resectable pancreatic cancer on clinical performance

    World Journal of Gastroenterology 20:3620–3627.

    https://doi.org/10.3748/wjg.v20.i13.3620

    • Google Scholar
32. 1. Kurman RJ
    2. Shih I

    (2010) The origin and pathogenesis of epithelial ovarian cancer: a proposed unifying theory

    American Journal of Surgical Pathology 34:433–443.

    https://doi.org/10.1097/PAS.0b013e3181cf3d79

    • Google Scholar
33. 1. Kurman RJ
    2. Shih I

    (2011) Molecular pathogenesis and extraovarian origin of epithelial ovarian cancer--shifting the paradigm

    Human Pathology 42:918–931.

    https://doi.org/10.1016/j.humpath.2011.03.003

    • Google Scholar
34. 1. Lee Y
    2. Miron A
    3. Drapkin R
    4. Nucci MR
    5. Medeiros F
    6. Saleemuddin A
    7. Garber J
    8. Birch C
    9. Mou H
    10. Gordon RW
    11. Cramer DW
    12. McKeon FD
    13. Crum CP

    (2007) A candidate precursor to serous carcinoma that originates in the distal fallopian tube

    Journal of Pathology 211:26–35.

    https://doi.org/10.1002/path.2091

    • Google Scholar
35. 1. Levine D
    2. Brown DL
    3. Andreotti RF
    4. Benacerraf B
    5. Benson CB
    6. Brewster WR
    7. Coleman B
    8. Depriest P
    9. Doubilet PM
    10. Goldstein SR
    11. Hamper UM
    12. Hecht JL
    13. Horrow M
    14. Hur HC
    15. Marnach M
    16. Patel MD
    17. Platt LD
    18. Puscheck E
    19. Smith-Bindman R

    (2010) Management of asymptomatic ovarian and other adnexal cysts imaged at US: society of radiologists in ultrasound consensus conference statement

    Radiology 256:943–954.

    https://doi.org/10.1148/radiol.10100213

    • Google Scholar
36. 1. Lin JD
    2. Chao TC
    3. Huang BY
    4. Chen ST
    5. Chang HY
    6. Hsueh C

    (2005) Thyroid cancer in the thyroid nodules evaluated by ultrasonography and fine-needle aspiration cytology

    Thyroid 15:708–717.

    https://doi.org/10.1089/thy.2005.15.708

    • Google Scholar
37. 1. Loh FH
    2. Tan AT
    3. Kumar J
    4. Ng SC

    (1999) Ovarian response after laparoscopic ovarian cystectomy for endometriotic cysts in 132 monitored cycles

    Fertility and Sterility 72:316–321.

    https://doi.org/10.1016/S0015-0282(99)00207-1

    • Google Scholar
38. 1. Martínez-Onsurbe P
    2. Ruiz Villaespesa A
    3. Sanz Anquela JM
    4. Valenzuela Ruiz PL

    (2001) Aspiration cytology of 147 adnexal cysts with histologic correlation

    Acta Cytologica 45:941–947.

    https://doi.org/10.1159/000328368

    • Google Scholar
39. 1. Mayr D
    2. Hirschmann A
    3. Löhrs U
    4. Diebold J

    (2006) KRAS and BRAF mutations in ovarian tumors: a comprehensive study of invasive carcinomas, borderline tumors and extraovarian implants

    Gynecologic Oncology 103:883–887.

    https://doi.org/10.1016/j.ygyno.2006.05.029

    • Google Scholar
40. 1. Moran O
    2. Menczer J
    3. Ben-Baruch G
    4. Lipitz S
    5. Goor E
    6. . Lipitz S
    7. Ben-Baruch S

    (1993)

    Cytologic examination of ovarian cyst fluid for the distinction between benign and malignant tumors

    Obstetrics and Gynecology 82:444–446.

    • Google Scholar
41. 1. Moyer VA
    2. S. T. Force USP
    3. U.S. Preventive Services Task Force

    (2012) Screening for ovarian cancer: U.S. preventive services task force reaffirmation recommendation statement

    Annals of Internal Medicine 157:900–904.

    https://doi.org/10.7326/0003-4819-157-11-201212040-00539

    • Google Scholar
42. 1. Mulvany NJ

    (1996) Aspiration cytology of ovarian cysts and cystic neoplasms. A study of 235 aspirates

    Acta Cytologica 40:911–920.

    https://doi.org/10.1159/000334002

    • Google Scholar
43. 1. Murtaza M
    2. Dawson SJ
    3. Tsui DW
    4. Gale D
    5. Forshew T
    6. Piskorz AM
    7. Parkinson C
    8. Chin SF
    9. Kingsbury Z
    10. Wong AS
    11. Marass F
    12. Humphray S
    13. Hadfield J
    14. Bentley D
    15. Chin TM
    16. Brenton JD
    17. Caldas C
    18. Rosenfeld N

    (2013) Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA

    Nature 497:108–112.

    https://doi.org/10.1038/nature12065

    • Google Scholar
44. 1. Newman AM
    2. Bratman SV
    3. To J
    4. Wynne JF
    5. Eclov NC
    6. Modlin LA
    7. Liu CL
    8. Neal JW
    9. Wakelee HA
    10. Merritt RE
    11. Shrager JB
    12. Loo BW
    13. Alizadeh AA
    14. Diehn M
    15. Loo, Jr BW

    (2014) An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage

    Nature Medicine 20:548–554.

    https://doi.org/10.1038/nm.3519

    • Google Scholar
45. 1. Ngamruengphong S
    2. Xu C
    3. Woodward TA
    4. Raimondo M
    5. Stauffer JA
    6. Asbun HJ
    7. Wallace MB

    (2013) Risk of gastric or peritoneal recurrence, and long-term outcomes, following pancreatic cancer resection with preoperative endosonographically guided fine needle aspiration

    Endoscopy 45:619–626.

    https://doi.org/10.1055/s-0033-1344216

    • Google Scholar
46. 1. Ngamruengphong S
    2. Swanson KM
    3. Shah ND
    4. Wallace MB

    (2015) Preoperative endoscopic ultrasound-guided fine needle aspiration does not impair survival of patients with resected pancreatic cancer

    Gut 64:1105–1110.

    https://doi.org/10.1136/gutjnl-2014-307475

    • Google Scholar
47. 1. Pavlik EJ
    2. Ueland FR
    3. Miller RW
    4. Ubellacker JM
    5. DeSimone CP
    6. Elder J
    7. Hoff J
    8. Baldwin L
    9. Kryscio RJ
    10. van Nagell JR

    (2013) Frequency and disposition of ovarian abnormalities followed with serial transvaginal ultrasonography

    Obstetrics and Gynecology 122:210–217.

    https://doi.org/10.1097/AOG.0b013e318298def5

    • Google Scholar
48. 1. Rago C
    2. Huso DL
    3. Diehl F
    4. Karim B
    5. Liu G
    6. Papadopoulos N
    7. Samuels Y
    8. Velculescu VE
    9. Vogelstein B
    10. Kinzler KW
    11. Diaz LA

    (2007) Serial assessment of human tumor burdens in mice by the analysis of circulating DNA

    Cancer Research 67:9364–9370.

    https://doi.org/10.1158/0008-5472.CAN-07-0605

    • Google Scholar
49. 1. Schmeler KM
    2. Sun CC
    3. Bodurka DC
    4. Deavers MT
    5. Malpica A
    6. Coleman RL
    7. Ramirez PT
    8. Gershenson DM

    (2008) Neoadjuvant chemotherapy for low-grade serous carcinoma of the ovary or peritoneum

    Gynecologic Oncology 108:510–514.

    https://doi.org/10.1016/j.ygyno.2007.11.013

    • Google Scholar
50. 1. Sharma A
    2. Apostolidou S
    3. Burnell M
    4. Campbell S
    5. Habib M
    6. Gentry-Maharaj A
    7. Amso N
    8. Seif MW
    9. Fletcher G
    10. Singh N
    11. Benjamin E
    12. Brunell C
    13. Turner G
    14. Rangar R
    15. Godfrey K
    16. Oram D
    17. Herod J
    18. Williamson K
    19. Jenkins H
    20. Mould T
    21. Woolas R
    22. Murdoch J
    23. Dobbs S
    24. Leeson S
    25. Cruickshank D
    26. Fourkala EO
    27. Ryan A
    28. Parmar M
    29. Jacobs I
    30. Menon U

    (2012) Risk of epithelial ovarian cancer in asymptomatic women with ultrasound-detected ovarian masses: a prospective cohort study within the UK collaborative trial of ovarian cancer screening (UKCTOCS)

    Ultrasound in Obstetrics & Gynecology 40:338–344.

    https://doi.org/10.1002/uog.12270

    • Google Scholar
51. 1. Sherman ME
    2. Mink PJ
    3. Curtis R
    4. Cote TR
    5. Brooks S
    6. Hartge P
    7. Devesa S

    (2004) Survival among women with borderline ovarian tumors and ovarian carcinoma: a population-based analysis

    Cancer 100:1045–1052.

    https://doi.org/10.1002/cncr.20080

    • Google Scholar
52. 1. Shih KK
    2. Zhou Q
    3. Huh J
    4. Morgan JC
    5. Iasonos A
    6. Aghajanian C
    7. Chi DS
    8. Barakat RR
    9. Abu-Rustum NR

    (2011) Risk factors for recurrence of ovarian borderline tumors

    Gynecologic Oncology 120:480–484.

    https://doi.org/10.1016/j.ygyno.2010.11.016

    • Google Scholar
53. 1. Tewari D
    2. Java JJ
    3. Salani R
    4. Armstrong DK
    5. Markman M
    6. Herzog T
    7. Monk BJ
    8. Chan JK

    (2015) Long-term survival advantage and prognostic factors associated with intraperitoneal chemotherapy treatment in advanced ovarian cancer: a gynecologic oncology group study

    Journal of Clinical Oncology 33:1460–1466.

    https://doi.org/10.1200/JCO.2014.55.9898

    • Google Scholar
54. 1. Tran AA
    2. Brown SB
    3. Rosenberg J
    4. Hovsepian DM

    (2014) Tract embolization with gelatin sponge slurry for prevention of pneumothorax after percutaneous computed tomography-guided lung biopsy

    Cardiovascular and Interventional Radiology 37:1546–1553.

    https://doi.org/10.1007/s00270-013-0823-8

    • Google Scholar
55. 1. Tsang YT
    2. Deavers MT
    3. Sun CC
    4. Kwan SY
    5. Kuo E
    6. Malpica A
    7. Mok SC
    8. Gershenson DM
    9. Wong KK

    (2013) KRAS (but not BRAF) mutations in ovarian serous borderline tumour are associated with recurrent low-grade serous carcinoma

    Journal of Pathology 231:449–456.

    https://doi.org/10.1002/path.4252

    • Google Scholar
56. 1. Tsang WK
    2. Luk WH
    3. Lo A

    (2014) Ultrasound-guided plugged percutaneous biopsy of solid organs in patients with bleeding tendencies

    Hong Kong Medical Journal 20:107–112.

    https://doi.org/10.12809/hkmj133972

    • Google Scholar
57. 1. Ueland FR
    2. Desimone CP
    3. Seamon LG
    4. Miller RA
    5. Goodrich S
    6. Podzielinski I
    7. Sokoll L
    8. Smith A
    9. van Nagell JR
    10. Zhang Z

    (2011) Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors

    Obstetrics and Gynecology 117:1289–1297.

    https://doi.org/10.1097/AOG.0b013e31821b5118

    • Google Scholar
58. 1. Vogelstein B
    2. Papadopoulos N
    3. Velculescu VE
    4. Zhou S
    5. Diaz LA
    6. Kinzler KW

    (2013) Cancer genome landscapes

    Science 339:1546–1558.

    https://doi.org/10.1126/science.1235122

    • Google Scholar
59. 1. Volpe A
    2. Kachura JR
    3. Geddie WR
    4. Evans AJ
    5. Gharajeh A
    6. Saravanan A
    7. Jewett MA

    (2007) Techniques, safety and accuracy of sampling of renal tumors by fine needle aspiration and core biopsy

    Journal of Urology 178:379–386.

    https://doi.org/10.1016/j.juro.2007.03.131

    • Google Scholar
60. 1. Wu J
    2. Jiao Y
    3. Dal Molin M
    4. Maitra A
    5. de Wilde RF
    6. Wood LD
    7. Eshleman JR
    8. Goggins MG
    9. Wolfgang CL
    10. Canto MI
    11. Schulick RD
    12. Edil BH
    13. Choti MA
    14. Adsay V
    15. Klimstra DS
    16. Offerhaus GJ
    17. Klein AP
    18. Kopelovich L
    19. Carter H
    20. Karchin R
    21. Allen PJ
    22. Schmidt CM
    23. Naito Y
    24. Diaz LA
    25. Kinzler KW
    26. Papadopoulos N
    27. Hruban RH
    28. Vogelstein B
    29. Wood JR
    30. Edil MA
    31. Allen CM
    32. Diaz, Jr. KW

    (2011a) Whole-exome sequencing of neoplastic cysts of the pancreas reveals recurrent mutations in components of ubiquitin-dependent pathways

    Proceedings of the National Academy of Sciences of the United States of America 108:21188–21193.

    https://doi.org/10.1073/pnas.1118046108

    • Google Scholar
61. 1. Wu J
    2. Matthaei H
    3. Maitra A
    4. Dal Molin M
    5. Wood LD
    6. Eshleman JR
    7. Goggins M
    8. Canto MI
    9. Schulick RD
    10. Edil BH
    11. Wolfgang CL
    12. Klein AP
    13. Diaz LA
    14. Allen PJ
    15. Schmidt CM
    16. Kinzler KW
    17. Papadopoulos N
    18. Hruban RH
    19. Vogelstein B

    (2011b) Recurrent GNAS mutations define an unexpected pathway for pancreatic cyst development

    Science Translational Medicine 3:92ra66.

    https://doi.org/10.1126/scitranslmed.3002543

    • Google Scholar
62. 1. Yamada R
    2. Maeda N
    3. Oguri H
    4. Adachi Y
    5. Takeuchi T
    6. Furihata M
    7. Fukaya T

    (2013) Is it possible to diagnose malignancy from fluid in cystic ovarian tumors?

    European Journal of Obstetrics, Gynecology, and Reproductive Biology 171:96–100.

    https://doi.org/10.1016/j.ejogrb.2013.08.003

    • Google Scholar

Author details

1. Yuxuan Wang

   1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
   2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   YW, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Karin Sundfeldt

   Competing interests

   No competing interests declared.

   "This ORCID iD identifies the author of this article:" 0000-0002-2932-6042

2. Karin Sundfeldt

   Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Cancer Center, University of Gothenburg, Gothenburg, Sweden

   Contribution

   KS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Yuxuan Wang

   Competing interests

   No competing interests declared.

3. Constantina Mateoiu

   Department of Pathology, Institute of Biomedicine, University of Gothenburg, Gothenburg, Sweden

   Contribution

   CM, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

4. Ie-Ming Shih

   1. Department of Pathology, The Johns Hopkins Medical Institutes, Baltimore, United States
   2. Department of Gynecology and Obstetrics, The Johns Hopkins Medical Institutions, Baltimore, United States

   Contribution

   I-MS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

5. Robert J Kurman

   1. Department of Pathology, The Johns Hopkins Medical Institutes, Baltimore, United States
   2. Department of Gynecology and Obstetrics, The Johns Hopkins Medical Institutions, Baltimore, United States

   Contribution

   RJK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

6. Joy Schaefer

   1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
   2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   JS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

7. Natalie Silliman

   1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
   2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   NS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

8. Isaac Kinde

   1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
   2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   IK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   IK: is affliated with the PapGene Inc

9. Simeon Springer

   1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
   2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   SS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

10. Michael Foote

    1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    3. Swim Across America Laboratory, Baltimore, United States

    Contribution

    MF, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    No competing interests declared.

11. Björg Kristjansdottir

    Department of Obstetrics and Gynecology, Institute of Clinical Sciences, Sahlgrenska Cancer Center, University of Gothenburg, Gothenburg, Sweden

    Contribution

    BK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    No competing interests declared.

12. Nathan James

    1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

    Contribution

    NJ, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    NJ: is affiliated with the Emmes Corporation

13. Kenneth W Kinzler

    1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

    Contribution

    KWK, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    KWK: under agreements between the JHU, Genzyme, Sysmex-Inostics, Qiagen, Invitrogen, and Personal Genome Diagnostics, KWK is entitled to a share of the royalties received by the University on sales of products related to genes and technologies described in this manuscript. KWK is a co-founder of, Personal Genome Diagnostics and PapGene Inc, is a member of the Scientific Advisory Boards of Sysmex-Inostics, Personal Genome Diagnostics, and PapGene, Inc, and owns Personal Genome Diagnostics and PapGene, Inc stock, which is subject to certain restrictions under Johns Hopkins University policy. The terms of these arrangements are managed by the Johns Hopkins University in accordance with its conflict-of-interest policies. Additionally, KWK is on the Scientific Advisory Board of Morphotek Inc

14. Nickolas Papadopoulos

    1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

    Contribution

    NP, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    NP: under agreements between the JHU, Genzyme, Sysmex-Inostics, Qiagen, Invitrogen, and Personal Genome Diagnostics, NP is entitled to a share of the royalties received by the University on sales of products related to genes and technologies described in this manuscript. NP is also a co-founder of, Personal Genome Diagnostics and PapGene Inc., is a member of the Scientific Advisory Boards of Sysmex-Inostics, Personal Genome Diagnostics, and PapGene, Inc., and owns Personal Genome Diagnostics and PapGene, Inc. stock, which is subject to certain restrictions under Johns Hopkins University policy. The terms of these arrangements are managed by the Johns Hopkins University in accordance with its conflict-of-interest policies.

15. Luis A Diaz

    1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    3. Swim Across America Laboratory, Baltimore, United States

    Contribution

    LAD, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    LAD: under agreements between the JHU, Genzyme, Sysmex-Inostics, Qiagen, Invitrogen, and Personal Genome Diagnostics, LAD is entitled to a share of the royalties received by the University on sales of products related to genes and technologies described in this manuscript. LAD is a co-founder of, Personal Genome Diagnostics and PapGene Inc., is a member of the Scientific Advisory Boards of Sysmex-Inostics, Personal Genome Diagnostics, and PapGene, Inc., and owns Personal Genome Diagnostics and PapGene, Inc. stock, which is subject to certain restrictions under Johns Hopkins University policy. The terms of these arrangements are managed by the Johns Hopkins University in accordance with its conflict-of-interest policies.

16. Bert Vogelstein

    1. Ludwig Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    2. Sidney Kimmel Comprehensive Cancer Center, Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States

    Contribution

    BV, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article, Contributed unpublished essential data or reagents

    For correspondence

    bertvog@gmail.com

    Competing interests

    BV: under agreements between the JHU, Genzyme, Sysmex-Inostics, Qiagen, Invitrogen, and Personal Genome Diagnostics, BV is entitled to a share of the royalties received by the University on sales of products related to genes and technologies described in this manuscript. BV is a co-founder of, Personal Genome Diagnostics and PapGene Inc, is a member of the Scientific Advisory Boards of Sysmex-Inostics, Personal Genome Diagnostics, and PapGene, Inc, and owns Personal Genome Diagnostics and PapGene, Inc stock, which is subject to certain restrictions under Johns Hopkins University policy. The terms of these arrangements are managed by the Johns Hopkins University in accordance with its conflict-of-interest policies. Additionally, BV is on the Scientific Advisory Board of Morphotek Inc.

    "This ORCID iD identifies the author of this article:" 0000-0003-0766-3854

• 5,263

  views

• 511

  downloads

• 30

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.