Early Detection of High Grade Ovarian Cancer Using Uterine Lavage EHUD Study and Duplex Sequencing
Condition: Ovarian Epithelial Cancer; Carcinoma in Situ; Ovarian Cancer
MeSH terms: Carcinoma; Ovarian Neoplasms; Carcinoma, Ovarian Epithelial; Carcinoma in Situ
Study type: Interventional

Summary: 
      In Phase I the sponsor will systematically test conditions for lavage filtration that
      increase tumor cell fraction without reducing tumor mutation yield. The Sponsor will also
      transition all lavages to luteal phase timing, when endometrial shedding is least. In Phase
      II the Sponsor will examine our data in context of clinical characteristics, particularly
      age, to develop a multivariate model that determines optimal mutant allele frequency (MAF)
      diagnostic threshold by patient. Furthermore, the sponsor will explore a highly innovative
      idea, entailing empirically determining each individual's background mutation load, agnostic
      of the aging or mutagenic exposures responsible, and using this as a personalized calibrator
      to determine optimal MAF diagnostic threshold.
    

Detailed description: 
      APPROACH PHASE I The University of Washington has demonstrated diagnostic proof of principle;
      however, further optimization and validation is needed for industrial scale deployment. In
      Phase I the UtL filtration method will be optimized (Aim 1), analytical performance on the
      commercial workflow validated (Aim 2) and a sample collection milestone met (Aim 3). Aim 1.
      Determine utility of uterine lavage filtration to maximize enrichment for tumor derived DNA.
      Preliminary testing with two samples indicated that filtration of UtLs to remove clusters of
      endometrial cells could increase sensitivity for tumor mutations several folds. This data set
      will be expanded by analysing the filtration effect in 10 UtLs from patients with HGSC with
      known TP53 mutations. Each UtL will be divided in half: the first half will be filtered and
      the second will remain unfiltered. DNA will be extracted from the filtered, filtrate, and
      unfiltered fractions and analysed by TP53 DS (total of 30 samples). For each UtL, the DNA
      yield in each of the fractions and the MAF of the tumor mutation will be compared. It is
      anticipated that the filtered fraction will contain less DNA then the unfiltered fraction but
      the tumor mutation will be present at a higher frequency. If sensitivity is improved (i.e.
      more is gained by enrichment than is lost by reduction from less available DNA), filtration
      will be used on all future samples collected. Aim 2. Validation of optimized assay: accuracy,
      precision, limit of detection, and reproducibility. TwinStrand has developed a streamlined DS
      workflow using improved adapters, ligation chemistry and a high throughput 96 well
      plate-based format amenable to liquid handling robots and compatible with CLIA laboratory
      standards.

      TwinStrand has also developed an optimized cloud-based analysis pipeline that supports
      automated parallel processing of multiple samples. The optimized process for the detection of
      TP53 mutations in UtL samples will be validated. To assess accuracy, technical precision, and
      lower limit of detection, DNA samples from two individuals that differ in genotype at >5 SNP
      sites in or near TP53 will be mixed, in ratios from 1:100 1:5,000, two UtL. The mixtures will
      be sequenced at ~10,000x molecular depth in two independent experiments. SNP allele fraction
      (AF) will be compared at different dilutions to determine accuracy (expected AF vs. observed
      AF), precision (AF variation among replicates), and lowest limit of detection achievable. To
      test assay reproducibility in its intended clinical use, sequencing will be repeated on the
      30 samples used Aim 1, which will encompass a wide range of tumor MAFs. The Sponsor will
      calculate the coefficient of variation among replicates. Based on pilot studies The Sponsor
      anticipate excellent reproducibility (CV<5%). Aim 3. Sample collection. Collection of samples
      proposed in Phase II will be started under appropriate IRB/Ethic Committee approval at each
      participating institution.

      After collection, samples are shipped to the Institute for Cancer Research at the Medical
      University of Vienna who will perform UtL filtration and DNA extraction.

      Paired DNA from Pap smears and peripheral leukocytes will also be extracted. Isolated DNAs
      will be assigned a de identification number and shipped to TwinStrand for Duplex Sequencing.

      Phase I Milestones:

        1. Confirm utility of UtL filtration on tumor mutation enrichment.

        2. Quantify streamlined assay's accuracy, precision, lower limit of detection, and
           reproducibility on UtLs.

        3. Start samples collection for Phase II.

      Phase I Products:

        1. DS workflow ready for application to UtL DNA at commercial scale in Phase II and Phase
           III.

        2. Sample bank for Phase II

      APPROACH PHASE II Phase II will validate the use of TP53 DS on UtLs for early ovarian cancer
      detection in expanded case control patient cohorts encompassing both average and high risk
      populations. Predefined parameters that may affect the sensitivity and specificity of TP53
      mutation frequency will be examine, and statistically modeled. Clinical sensitivity and
      specificity will be maximized by building personalized diagnostic threshold statistical
      models using multivariate clinical characteristics, as well as each individual's unique
      background mutation load based on leukocyte sequencing. In a subset of patients, the superior
      performance of UtL over Pap smear sampling will be confirmed. In addition, a proof of concept
      study will be conducted in a sub-set of included patients to study a set of 96 methylation
      markers relevant to HGSC in UtLs and corresponding tumor tissue/STICs.

      AIM 1. GENERAL POPULATION OVARIAN CANCER SCREENING This aim will develop a biomarker for HGSC
      detection in an average risk population. The Sponsor will conduct a case control study that
      integrates TP53 DS mutational data with clinic pathological information in order to identify
      women with HGSC with maximum sensitivity and specificity. More than 98% of HGSCs carry
      mutations in TP53, which means that ultra-deep DS can be cost effectively focused on just a
      small genomic region. The product of this aim will be a 200 patient biomarker data set that
      demonstrates the cost effective, commercially robust performance of this critically needed
      ovarian cancer diagnostic.

      Aim 1A: To assess the test performance of TP53 DS on UtLs for HGSC detection in average risk
      patients.

      Methods: UtL samples from 200 subjects from average risk population will be analyzed via DS:
      100 subjects with HGSC (cases) and 100 subjects with lesions that were ultimately found to be
      benign after resection, i.e., without cancer (controls). In all patients UtL will be
      collected prior surgical intervention for an ovarian mass. Lavage will be carried out during
      the luteal phase of the menstrual cycle if pre-menopausal. Surgical specimens will be
      pathologically assessed, and a patient will be counted a HGSC positive or a control depending
      on the histological results. For cancer patients, the primary tumor will be sequenced via
      conventional methods by the Medical University of Vienna for a panel of genes that includes
      TP53, BRCA1 and BRCA2. For all de-identified patient samples, collected clinical information
      will include: age, smoking history, prior chemotherapy exposure, parity, age-of-menopause,
      age-of-menarche, history of oral contraceptive use, cancer family history, and seven-gene
      mutation status of the primary tumor. Cases and controls will be aged matched and as wide an
      age range as possible will be included to assess the effect of age on sensitivity and
      specificity.

      Statistical Analysis: A detailed mutation profile for each sample will be generated from the
      duplex sequencing output files including: mutant allele frequency (MAF) for all mutated
      positions, mutation spectrum, predicted pathogenicity to protein function, relationship to
      known hotspots, and overall mutation load (number of mutant nucleotides divided by the total
      number of nucleotides sequenced). Following this, samples will be unblinded for
      cases-controls status. TP53 MAF from DNA collected by UtLs will be used as predictor for
      differentiating between average risk patients (AIM I) with and without HGSC by logistic
      regression modelling. Age, smoking history, prior chemotherapy exposure, parity,
      age-of-menopause, age-of-menarche, history of oral contraceptive use, cancer family history
      and germline mutation status will be considered as potential confounders. Model prediction
      will be assessed by cross-validation. An analogous analysis will be applied to the group of
      high risk patients (AIM II) where presence and absence of STIC is defining the outcome
      variable. Cut off values for mutant allele frequency will be suggested in both cases and
      specificity and sensitivity will be estimated including appropriate confidence intervals.

      Aim 1B: Improving diagnostic performance with personalized calibration by background mutation
      load.

      The unprecedented sensitivity of DS led us then others to the novel discovery that cancer
      like mutations accumulate at very low levels with age in multiple human tissues. In a pilot
      study the sponsor discovered that the average BB mutation load is somewhat higher in UtLs
      than other tissues, potentially because of DNA contribution from endometrial tissue, which
      replicates extensively prior to menopause. While this did not compromise specificity in the
      pilot study, the sponsor recognize that BB could pose an obstacle with some very early tumors
      where MAF signal is low, or with very elderly women where background is high. The Sponsor
      expect that lavage filtration and luteal phase collection in premenopausal women will reduce
      BB signal, but as an added measure the sponsor will examine whether performance can be
      further improved by normalizing for an individual's background mutation load. The sponsor
      hypothesize that the level of TP53 mutations in circulating leukocytes can serve as an
      empirically measured personal calibrator that captures, not only known factors that increase
      BB, such as age, but also unknown mutagenic exposures or other factors occurring during a
      person's life. Although DNA from leukocytes probably only contributes a minimal amount to the
      total pool of BB mutations in UtLs, the sponsor posit that they may serve as a proverbial
      "canary in a coal mine" that will be proportionally representative of BB mutations elsewhere
      in the body. The BB mutation load in a lavage, itself, cannot be directly measured in a real
      world setting when the mutation(s) contributed by a tumor are unknown. The plausibility of
      this concept was shown by our initial study of TP53 mutations in peritoneal fluid, which
      included a subset of matching blood samples and indicated a strong association between BB and
      age.

      Methods: DNA from the peripheral blood mononuclear cells (PBMC) component - collected
      immediately prior to a surgery - of randomly chosen 50 from 100 HGSC cases and 50 from 100
      controls from Aim 1A will be extracted and subjected to TP53 DS at ~10,000x molecular depth.
      TP53 mutations from PBMCs will be subtracted from TP53 mutations found in the UtL.

      Statistical Analysis: The Sponsor will examine the association between TP53 mutation
      frequencies in UtL and leukocytes and will determine whether false negatives in Aim 1A
      correspond to cases with increased BB in leukocytes. In addition, the sponsor will analyze
      TP53 mutation frequencies in leukocytes as a predictor of case control status, again using
      the leave out 10% procedure. This innovative calibration method will be compared with the
      simple ROC metrics achieved with the univariate model using a fixed mutation fraction as well
      as the adjusted multivariate model developed based on other patient characteristics such as
      age. As a scientific question unrelated to the present aims, the sponsor are eager to see
      whether leukocyte TP53 mutation load will serve as an independent predictor of patient age,
      overall health or history of mutagenic exposures.

      Aim 1C. Comparison of diagnostic performance of uterine lavage vs. Pap smear collected DNA.

      The first report of using NGS for ovarian cancer detection from a trans vaginal liquid biopsy
      relied on Pap smear collection and SafeSeqS as the sequencing technology. The cited
      sensitivity of 41% provided an important proof of principle, but also ample room for
      improvement. The sponsor have definitively demonstrated the superior accuracy of DS over
      SafeSeqS like methods and ongoing studies in our lab indicate limited sensitivity of Pap
      smears compared to UtL. However, a direct comparison of the two collection methods on the
      same patients remains to be performed. Formally demonstrating the degree of superiority of
      UtL over Pap smears will help with commercial market entry (the sponsor note that a related
      NCI SBIR has been awarded to PapGene Inc, a company founded by the above-mentioned study's
      authors). The superiority of UtL is expected based on the fact that the lavages reach the
      fallopian tubes and ovarian surfaces whereas Pap smears rely on disseminated cancer cells
      reaching the cervical canal. Nevertheless, in the event that TP53 DS on Pap smears does not
      drastically underperform UtL, the sponsor would further explore this complementary collection
      method. Because Pap smears are routinely performed by primary care providers, the ability to
      use these could help accelerate market adoption. However, current evidence points to the
      probable inferiority of Pap smears.

      Methods: The sponsor will carry out TP53 DS as above but using DNA from Pap smears collected
      prior to surgery of randomly selected, age matched subset of 25 cancer cases and 25 controls
      from Aim 1A.

      Statistical Analysis: Data on TP53 MAF from DNA collected by conventional pap smear tests
      from a subsample of average risk patients will be considered as additional predictor in
      models developed within aim 1A and 1B.The sponsor will investigate if any additional power to
      discriminate cases from controls can be gained by combining information from Pap smears and
      UtLs.

      AIM 2. HIGH RISK POPULATION OVARIAN CANCER SCREENING This aim will take a similar approach to
      that of Aim 1 but will focus on women at high risk for ovarian cancer due to hereditary
      breast and ovarian cancer (HBOC) mutations. HBOC women will have been identified by a strong
      family history of breast or ovarian cancer and found to carry mutations in cancer
      susceptibility genes, usually BRCA1 and BRCA2, which confer a lifetime HGSC risk of 35%, 46%
      and 13%, 23%, respectively. Standard of care is risk reducing salpingo oophorectomy (RRSO) at
      an early age, typically after completion of child bearing. Although this approach does
      decrease mortality, it is imperfect: approximately 10% of ovarian cancers in this population
      develop before age 40. In the Vienna case series, cancers have been seen at as young an age
      as 20, which is well before a prophylactic surgery would normally have been undertaken. Thus,
      even with standard of care, HBOC women in their reproductive years are at a significantly
      elevated risk of ovarian cancer relative to other women their need for an effective screening
      tool is even greater. At present, affected women must make the decision to either accept the
      increased risk of a highly lethal cancer or elect to forgot (or prematurely end)
      childbearing. This is an excruciatingly challenging decision faced by hundreds of thousands
      of women in the US alone. In certain ethnic groups, particularly Ashkenazi Jews, the risk of
      being a carrier is as high as 1 in 40. Yet the majority of BRCA carriers, even those who do
      not have surgery, will never develop HGSC. There is an urgent need for early detection
      diagnostic tools in women at high risk of HGCS in order to save lives and preserve the choice
      of fertility. The product of this aim will be a 115 patient biomarker data set that
      demonstrates commercially robust performance of such an assay.

      Aim 2A. To assess the test performance of TP53 DS on UtLs for HGSC detection in high risk
      patients.

      The sponsor will approach this study per the general methods of Aim 1A. One significant
      difference is that UtL will be collected from HBOC women undergoing RRSO, rather than from
      women with known ovarian masses. After RRSO, the ovaries and fallopian tubes undergo a
      meticulous sectioning protocol known as SEE-FIM to carefully examine the tissues,
      particularly the fimbriae, for STICs and occult cancers. Among this high risk population,
      such lesions are found in roughly 5% of resections. The cancer group will encompass women
      where STICs or occult tumors were found during SEE-FIM the control group will include women
      with no lesions. This study design is innovative in that it focuses, not only on high risk
      women, but specifically on the ability of our assay to detect very early stage, potentially
      even microscopic, cancers when they remain surgically curable.

      Methods: UtL samples from up to 115 women with hereditary high risk ovarian cancer syndromes
      will be analyzed via DS: 15 with STICs or occult cancer (cases) and up to 100 cancer free
      (controls). Case and control will be matched by age. UtLs will be performed immediately prior
      to RRSO. Surgical specimens will be pathologically assessed by a centrally standardized
      SEE-FIM protocol. After RRSO, the ovaries and fallopian tubes undergo a meticulous sectioning
      protocol known as SEE-FIM to carefully examine the tissues, particularly the fimbriae, for
      STICs and occult cancers. The sponsor expects to have identified 5 to 15 women with STIC or
      occult cancers in this cohort, 100 age matched women will have no detected lesions. The
      smaller number of cancer cases than controls reflects the low percentage of lesion positive
      surgeries and the sample number the sponsor project realistically being able to achieve.
      Although a larger number would be optimal, such samples are extremely limited. The cancer
      group will encompass women where STICs or occult HGSC were found during SEE-FIM the control
      group will include women with no lesions Statistical analysis: This will be as per Aim 1A.

      Aim 2B. Diagnostic threshold calibration in high risk women by background mutation load.

      This sub-aim will use the same protocol and statistical methods of aim 1B and apply them to
      the high- r i s k population of Aim 2.

      Methods:Leukocyte DNA from all available cancer cases and a randomly chosen 30-woman subset
      of the control group will be evaluated. It is well-established that the risk of malignancy in
      HBOC women is elevated relative to others by virtue of defects in DNA repair that increase
      the probability of oncogenic mutations arising. As such, the sponsor anticipate that the
      non-cancer-derived background mutation load measured in UtLs as well as in peripheral blood
      may be proportionally elevated as well. Adjusting for the high background mutation load
      measured in blood may be particularly important to increase specificity in this group.

      Statistical analysis: This will be as per Aim 1B.

      AIM III To define a methylation signature for HGSC detection in UtLs. Over the last 15 years,
      the value of DNA methylation analysis for the detection of epigenetic, tumour-specific
      changes has been demonstrated, particularly in cancer diagnostics. Studies of DNA-methylation
      in ovarian cancer (OC) focused on detecting DNA fragments shed by OC cells into the
      bloodstream (i.e. cell-free DNA - cfDNA) suggest that DNA methylation patterns in cfDNA have
      the potential to detect a proportion of OCs up to two years in advance of diagnosis. This
      study also clearly shows the limitation of this approach because only 50% of all patients who
      finally developed high-grade serous ovarian cancer (HGSC) within two years could be detected.
      The underlying problem is that due to the low concentration of cfDNA in the blood stream a
      very weak signal needs to be detected. With the aim of potentially increasing the sensitivity
      of HGSC detection the sponsor will in cooperation with Prof. Andreas Weinhäusel, Austrian
      Institute of Technology (AIT), Competence Unit Molecular Diagnostics, perform a proof of
      concept study in a sub-set of patients included in this project. Prof. Andreas Weinhäusel,
      identified 96 methylation markers relevant to HGSC. Only a very small amount of DNA is
      required for DNA methylation. It is therefore advisable to use the already available DNA from
      the lavages and the corresponding tumor tissue, which has been extracted in the course of
      this study, for the further development of the specificity and sensitivity of the test
      procedure. The product of AIM3 will be a 140 patient methylation markers data set that
      demonstrates high sensitive performance of such an assay.

      Methods: Genomic DNA from UtLs and corresponding tumor tissue from 30 HGSC patients and 10
      STICs/occult cancers will get enriched for methylated DNA with the aid of methylation
      sensitive restriction enzymes. This DNA will be analyzed by performing a highthrough put-qPCR
      in which 5 x 96 marker x 96 DNA will be analyzed in parallel. The most informative markers
      will be combined to a methylation signature. To proof the specificity of the signature DNA
      from UtLs from 60 controls will be analyzed (30 average risk and 30 high risk cases).
      Assessment of DNA methylation pattern will be carried out on the pre-resection lavages and on
      up to 10 STIC lesions/occult cancers. When local pathology results identify STICs or occult
      cancer cells (FFPE tissue), laser microdissection and DNA isolation will be performed.
      Subsequently applying standard NGS TP53 sequencing will be performed as described in AIM 1
      and AIM 2. In this pilot sub-study, high-through put-qPCR will be applied to remaining DNA
      material for assessment of methylation status.

      Statistical analysis: Aiming to evaluate the potential for defining a DNA-Methylation
      signature for simple PCR testing, dCT-PCR values from 96-plexed high-throughput MSREqPCR
      analysis will be analysed by bioinformatics & biostatistics to conduct 1) class comparison
      between the relevant clinical subtypes and classes for defining significantly differentially
      methylated genes; 2) multivariate class prediction analysis using different feature selection
      approaches based on single-marker p-values. Different classification algorithms (e.g.
      k-nearest neighbor, support vector machines, linear discrimination analyses etc.) will be
      applied, using 10-fold cross validation and/or leave-one-out cross validation for selecting
      best candidate methylation markers - and algorithms; in addition, the top-AUC values of
      single candidate methylation-marker's will be defined in ROC analysis and considered for
      marker selection.

      A subset of 48 candidate markers will be selected for confirmation in a separate sample set.
      The methylation data derived thereof will be analyzed using class comparison and class
      prediction analysis in a similar manner as the first set of data derived from 480plexed
      analysis. Best performing single markers and combinations of markers from multivariate
      analysis will be defined. Classification results and methylation data will be compared with
      p53 mutation test-results to evaluate potential of methylation-based diagnostic
      classification, as a sole and in combination with p53 mutation analysis. This will be
      conducted applying different class-prediction approaches integrating both p53 and methylation
      data in multivariate models.
    

Intervention name(s): Speiser-catheter for uterine and tubal lavage
Intervention type(s): Procedure
Intervention description(s): Procedure/Surgery: Lavage of the Cavum uteri and proximal Fallopian tubes, performed in the luteal phase of the female cycle
Allocation: Non-Randomized
Intervention model: Parallel Assignment
Intervention model description: Case control study in two patient population (AIM 1 in average risk population, AIM 2 in high risk population)
Masking: None (Open Label)
Primary purpose: Diagnostic
Keywords: Ovarian Epithelial Cancer f; Serous Intraepithelial Carcinoma (STIC); BRCA1 gene Mutation; BRCA2 gene Mutation; Neoplasms; Glandular and Epithelial; Ovarian Neoplasms; Ovarian cancer; Carcinoma in situ; Family history breast cancer and ovarian cancer