Abstract
The presence of somatic driver mutations in endometriosis has previously been believed to
represent early events in transformation, however our group and others have described such
mutations in roughly one-third of cases of deep infiltrating or iatrogenic endometriosis. These
forms of endometriosis rarely progress to malignancy. Recent studies have also shown somatic
driver mutations in normal skin, blood, peritoneal washings, and esophageal epithelium. Such
findings prompt speculation on whether such mutations exist in the eutopic endometrium – the
likely tissue of origin of endometriosis. In the current study we investigated the presence of
somatic driver mutations in histologically normal endometrium from women lacking evidence of
gynecologic malignancy or endometrial hyperplasia. Twenty-five women who underwent
hysterectomies and 85 women who underwent endometrial biopsies were included in this study.
Formalin-fixed, paraffin-embedded tissue specimens were analyzed by means of targeted
sequencing followed by orthogonal validation with droplet digital PCR. PTEN and ARID1A
immunohistochemistry (IHC) was also performed as surrogates for inactivating mutations in the
respective genes. Overall, we observed somatic driver-like events in over 50% of histologically
normal endometrial samples analyzed, which included hotspot mutations in KRAS, PIK3CA, and
FGFR2 as well as PTEN-loss by IHC. Analysis of anterior and posterior samplings collected
from women who underwent hysterectomies is consistent with the presence of somatic driver
mutations within clonal pockets spread throughout the uterus. The prevalence of such oncogenic
mutations also increased with age (OR: 1.05 (95% CI: 1.00 – 1.10), p = 0.035). These findings
have implications on our understanding of aging and so-called “normal tissues”, thereby
necessitating caution in the utilization of mutation-based early detection tools for endometrial or
other cancers.
Keywords
somatic mutations; normal tissue; aging; endometrium; digital PCR
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Oncogenic Mutations in Eutopic Endometrium
3
Introduction
Endometriosis is a chronic disease affecting approximately 10 percent of reproductive-aged
women. It leads to a variety of clinical symptoms including chronic (often cyclical) pain,
dyspareunia, dysmenorrhea, and infertility[1,2]. Endometriosis is the major risk factor for clear
cell and endometrioid carcinomas of the ovary (endometriosis-associated ovarian cancers;
EAOCs) [3-5]. Observations of endometriotic lesions (consisting of endometrial-like glands and
stroma) contiguous with EAOCs combined with molecular findings from several sequencing
studies have further established endometriosis as the precursor of EAOCs[6-8]. In these studies,
oncogenic mutations in genes such as ARID1A and PIK3CA[7,8] have been traced back to
endometriotic lesions within the same patients, thereby implicating such alterations as early
events towards malignant transformation. However, we have found somatic driver mutations in
approximately one-third of deep infiltrating endometriosis and iatrogenic endometriosis cases
(forms of endometriosis with little malignant potential)[9,10]. These findings suggest that such
mutations may be an inherent feature of endometriosis itself, perhaps conferring survival
advantages that allow lesions to persist ectopically. However, in order to study this hypothesis, it
is important to clarify whether uterine epithelial mutations can pre-exist endometriosis and be
present in the cells prior to implantation at an ectopic site.
In the current study, we sought to explore the mutational landscape of the eutopic (uterine)
endometrium from women lacking evidence of gynecologic malignancy by means of targeted
sequencing and immunohistochemistry (IHC) studies. Although the origins of endometriosis
remain contentious, the concept of retrograde menstruation stands as a leading theory. Herein,
endometrial fragments (originating from the uterus) are refluxed upwards through the fallopian
tubes and are implanted within the pelvic cavity[11]. This theory is supported by several lines of
evidence including the high prevalence of endometriosis in females with congenital outflow
obstruction[12] and the successful generation of endometriotic lesions in primate models of
endometriosis via intrapelvic injection of menstrual endometrium[13] or cervical occlusion[14].
Considering the dynamic nature of the endometrium as it undergoes many cycles of regeneration
and tissue breakdown throughout a woman’s reproductive years[15] as well as the recent
description of somatic mutations in normal tissues including the skin[16], blood[17], peritoneal
washings[18], and the esophageal epithelium[19], it is plausible that somatic mutations may pre-
exist in the eutopic endometrium. Moreover, a series of previous studies have described “latent
precancers” (alterations in otherwise normal tissue with unknown contribution to long-term
cancer risk) in the form of PTEN-null and PAX2-null glands within histologically normal
endometrium[20-22]. Application of next-generation sequencing techniques will broaden our
understanding of latent precancers, or pre-existing somatic alterations, in the eutopic
endometrium. This is particularly important since these tissues often serves as a reference for
molecular studies on endometriosis, endometrial cancer, and EAOCs.
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Oncogenic Mutations in Eutopic Endometrium
4
Materials and methods
Patient Identification and Specimen Collection
We obtained formalin-fixed and paraffin-embedded (FFPE) endometrial tissue specimens from
25 women who underwent hysterectomies (Supplementary Table S1) and 85 women who
underwent either dilation and curettage (D&C) or endometrial biopsies (Supplementary Table
S2). As confirmed by pathologist review, all women lacked evidence of gynecologic malignancy
or endometrial hyperplasia and all tissue specimens were obtained from the Department of
Anatomical Pathology at the Vancouver General Hospital in Vancouver, Canada. For
hysterectomy patients (Hx cohort), we collected and subsequently analyzed two blocks to
represent endometrial tissue from the posterior uterus and anterior uterus from each patient. For
D&C or endometrial biopsy patients (Bx cohort), we targeted collection of endometrial tissue
specimens to represent women of various ages (ranging from 20 – 61 years of age). Specimen,
data collection and experiments were approved by the UBC BC Cancer Agency Research Ethics
Board [H05-60119, H02-61375 and H08-01411].
Sample Processing and DNA Extraction
Hysterectomy specimens were sectioned at 8µm onto glass slides, deparaffinized with xylene
and stained with 10% diluted hematoxylin and eosin (H&E). Specimens were manually
macrodissected to enrich the epithelial layer using the tip of a 20-guage needle under a stereo
microscope. DNA from hysterectomy specimens was extracted using the ARCTURUS®
PicoPure® DNA Extraction Kit (ThermoFisher Scientific, USA). D&C and endometrial biopsy
specimens were cut into 3 – 6 10µm tissue scrolls. DNA from D&C and endometrial biopsy
specimens was extracted using the QIAamp® DNA FFPE Tissue Kit (QIAGEN, USA). All
DNA was quantitated using the Qubit 2.0 Fluorometer (ThermoFisher Scientific, USA).
Targeted Sequencing
All specimens were sequenced using FIND IT
TM version 3.4 (Contextual Genomics, Canada), a
proprietary hypersensitive cancer hotspot assay which covers over 120 hotspots and 17 exons
spanning 33 genes (Supplementary Table S3)[23]. Libraries were constructed using 75ng of total
DNA input. Candidate somatic variants for orthogonal validation were selected from defined
cancer hotspots reported in the Catalogue of Somatic Mutations in Cancer (COSMIC)[24], with
probability scores
≥ 0.8 (indicating the likelihood that a variant belongs to the mutation class as
opposed to the artifact class) and variant allele frequency (VAF) ≥ 0.8%.
Orthogonal Validation via ddPCR
Droplet digital polymerase-chain-reaction (ddPCR) was used to orthogonally validate hotspot
mutations. DNA from each specimen was pre-amplified for 10 cycles before subsequent droplet
generation using the QX200 Droplet Generator (Bio-Rad Laboratories, USA)[25]. In most cases,
the same aliquot of extracted DNA used for targeted sequencing was also used for ddPCR
validation (Supplementary Table S5 and S6). After thermal cycling, the QX200 Droplet Reader
(Bio-Rad Laboratories, USA) was used to quantify droplets. See Supplementary Table S7 for a
list of primers used and Supplementary Table S8 for ddPCR assay conditions.
PTEN and ARID1A Immunohistochemistry
Loss of PTEN immunoreactivity was used as a surrogate for PTEN loss-of-function mutations.
Following the protocol outlined in our previous study[10], specimens were stained on the
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Oncogenic Mutations in Eutopic Endometrium
5
Ventana Discovery Ultra (Ventana Medical Systems, USA) immunostainer using a 1:25 dilution
of rabbit monoclonal antibody, 138G6 (Cell Signaling, USA). Similarly, loss of nuclear ARID1A
immunoreactivity was used as a surrogate for ARID1A loss-of-function mutations[10,26,27].
Specimens were stained on the Dako Omnis (Agilent Technologies, USA) automated
immunostainer using a 1:2000 dilution of ARID1A rabbit monoclonal antibody EPR13501
(ab182560, Abcam, USA). TMN and BT-C. scored all ARID1A and PTEN immunostained
slides.
Results
Somatic Driver Mutation Frequencies in Normal Endometrium
As shown in Figure 1, we found that 16 of 25 women (64%) who underwent hysterectomy and
43 of 85 women (51%) who underwent D&C or endometrial biopsy harbored at least one
somatic alteration within their endometrial tissue samplings. Given our sample sizes, the
prevalence of these alterations (whether specifically or overall) did not significantly differ
between Hx and Bx cohorts (Supplementary Table S9). The most common somatic alterations
were hotspot KRAS and PIK3CA mutations (affecting 31 of 110 and 14 of 110 total patients
respectively), and focal loss of PTEN expression (defined by absence of staining in a small
cluster of glands among normally expressing glands) (30 of 110 total patients) (Supplementary
Figure S1). No patients exhibited loss of ARID1A either focally or globally.
Anatomical Distribution of Oncogenic Changes
For each woman in the Hx cohort, we independently collected and sequenced DNA from two
tissue blocks representing endometrial tissue from the anterior and posterior uterus within the
same patient. Somatic hotspot mutations were either completely absent (15 of 25 patients) or
dissimilar (9 of 25 patients) between anterior and posterior samplings (Supplementary Figure
S2). A single patient (Hx_25) harbored a KRAS G12A mutation in both samplings, however
anatomical distortion of the uterus in this patient resulted in an inability to determine the spatial
distinction between the two blocks of endometrial tissue (Table 1).
Driver Mutations Across Age
Accumulation of somatic alteration with increasing age has previously been suggested even in
the context of normal tissues[16-19]. To assess the relationship between age and presence of
somatic cancer-driver alterations, we generated a logistic regression model based on the
sequencing and IHC findings for the 25 women in the Hx cohort and 85 women in the Bx cohort
(Figure 2). Based on our model, the likelihood of a woman harbouring a somatic alteration in her
endometrial tissue increases by 5% per year (OR = 1.05, 95% CI = 1.00 – 1.10, p = 0.035, Wald
test). Moreover, a model incorporating both age and menstrual phase (proliferative versus
secretory phase) indicates that the prevalence of mutation is independent of menstrual phase (p =
0.6309, Wald test) (Supplementary Figure S3).
Comparison of Normal Endometrium Findings with Endometrial Cancer
We compared our data with endometrial cancer data from The Cancer Genome Atlas
(TCGA)[28] to better interpret mutational findings within the normal endometrium. Because our
analysis is restricted to the hotspot regions in the 33 genes covered by the FIND IT
TM assay
(Supplemental Table S3), we limited our comparison to oncogenic mutations within these
regions for the TCGA dataset. For our normal endometrial tissue cohort, we pooled our data
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Oncogenic Mutations in Eutopic Endometrium
6
from both the Hx cohort (n=25) and Bx cohort (n=85). Overall, endometrial cancer samples
more frequently harbored oncogenic mutations compared to the patients examined in our study
(96% vs 54%, p < 0.0001, Student’s t-test) (Figure 3A; Supplementary Table S10). Women with
endometrial cancer were far more likely to harbor a somatic mutation at a given age (OR: 10.8,
95% CI: 3.83 – 33.3, p = 1.5 e-05, Wald test) (Supplementary Figure S4).
Gene-specific analysis mutation frequencies were either indistinguishable or higher in cancer
specimens, except for KRAS driver mutations. We found a distinct trend (p = 0.0728) suggesting
a greater proportion of non-cancer patients harbored KRAS driver mutations in their endometrial
tissue, 31 of 110 (28%), compared with endometrial cancer patients, 48 of 248 (19%) (Figure
3A; Supplementary Table S10). Indeed, in a model that incorporates age and KRAS mutation,
whilst mutation rates in normal samples clearly increase with age (OR = 1.06, 95% CI = 1.01 –
1.11, p = 0.01953, Wald test), in the cancer samples the opposite trend is seen (OR = 0.96, 95%
CI = 0.94 – 0.99, p = 0.0164, Wald test) (Figure 3B).
Discussion
In many cancers, tumor progression is largely dependent on the accumulation of so-called
“driver mutations” that confer selective growth advantages on affected subclones compared to
surrounding cells[29-31]. EAOCs, in fact are characterized by mutations affecting PIK3CA,
PPP2R1A, ARID1A, KRAS, CTNNB1, and PTEN[32]. Sporadic endometrial cancers also have a
similar driver mutation landscape characterized by mutations affecting PIK3CA, PIK3R1,
ARID1A, KRAS, CTNNB1, PTEN, FGFR2, and alterations in mismatch repair proteins[33]. The
eutopic endometrium, an extremely dynamic tissue over the course of a woman’s reproductive
years, is both the tissue of origin for endometrial cancer and the presumed origin of EAOCs[6-8].
Therefore, it serves as an important reference for the studies of these cancers as well as
endometriosis. In the current study, we have described (with orthogonal validation) the presence
of somatic, driver mutations within histologically unremarkable, eutopic endometrium of over
half of women lacking evidence of gynecologic malignancy.
Our findings are consistent with oncogenic mutations existing in small clonal pockets throughout
the endometrium. Amongst informative patients, oncogenic mutations were dissimilar between
the anterior and posterior samplings (i.e. if a particular point mutation were found in one
sampling, it was not detected in the other sampling) – these findings were confirmed by ddPCR
testing of both samplings for any mutation found in either block (Table 1; Supplementary Table
S5). The VAFs of reported somatic mutations were generally low (between 0.8 – 11.9% in
hysterectomy or D&C/biopsy cases – see Table 1; Supplementary Table S5, S6), despite some
enrichment of the glandular epithelial layer. This suggests that oncogenic mutations may be
gland-level restricted, affecting only single (or a small number of) endometrial glands across a
breadth of many glands from a given tissue specimen. This hypothesis seems well supported by
two recent studies wherein individual endometrial glands were laser-captured from different
areas within the endometrium of the same patient. Both studies suggest that different glands
harbored different mutations[34,35]. These studies and our own results are also consistent with
the findings by Mutter et al. (2014)[20],where PTEN-loss appears zonally in single, or small
clusters of, glands (Supplementary Figure S1). Therefore, although our study represents broader
sampling of the endometrium and mutations, our observations and those of others[34,35] are
consistent with driver mutations, such as KRAS G12 mutations, occurring in small, clonal
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Oncogenic Mutations in Eutopic Endometrium
7
pockets throughout the uterus. Furthermore, it seems likely that acquisition of these mutations
provides sufficient selective advantages to expand within an entire gland of affected endometrial
cells, allowing this population to be detectable by our methods.
Somatic mutations have been previously described to accumulate with age in a variety of non-
cancerous tissues[18,19,36] and thus we sought to determine the relationship between age and
prevalence of somatic mutation in the normal endometrium. Overall, we found that the
prevalence of oncogenic mutations in normal endometrium indeed increases by age; the risk of
harboring such a mutation increases by approximately 5% per year. Moreover, the influence of
age on mutation prevalence is independent of the phase of the menstrual cycle (Supplementary
Figure S3). Comparing our data to the TCGA endometrial cancer dataset reveals that the
prevalence of driver mutations is higher across age in endometrial cancer (or comparably as
uncommon) in all genes except for KRAS. In our study, KRAS driver mutations occurred in over
one-quarter of eutopic endometrium cases, illustrating a trend to greater prevalence in non-
cancerous vs endometrial cancer samples. Although the KRAS mutation rates in normal
endometrial samplings increased with age the opposite was seen in the TCGA cancer samples.
The latter observation is likely due to distinct KRAS mutation rates in endometrial cancer
subtypes that, themselves, have distinct age distributions[28]. Since patients in our study
underwent hysterectomies, D&Cs, or endometrial biopsies for benign uterine-related pathologies
or related concerns, it is plausible that KRAS mutations may play a role in such benign/non-
cancer pathologies such as those described in arteriovenous malformations of the brain[37] or as
we have previously observed in endometriosis[9,10]. It is also possible that early activation of
KRAS induces senescence[38] in endometrial cells, thereby inhibiting progression towards
malignant transformation. In contrast to our high frequency KRAS mutations, CTNNB1 and
ARID1A are commonly mutated in endometrial cancer and EAOCs[32,33] but were not observed
in any of our normal endometrium specimens. This may suggest that, within the context of
endometrial-derived carcinomas, such mutations are later events in tumorigenesis or that
accumulation of mutations in cancer-destined precursors is etiologically distinct from age-related
accumulations.
Lastly, it is important to note that many of the cancer specimens in the TCGA dataset harbor
multiple driver mutations within the same tumor. Although some of our normal endometrium
specimens harbored multiple driver alterations within the same block, this was relatively
uncommon and it remains unclear if mutations affected overlapping populations or independent
subclones. The recent study by Moore et al. found two or more driver mutations in single
endometrial glands in 22% of specimens[35], suggesting an elevated probability, albeit still non-
conclusive, that driver mutations may co-exist in the same non-cancerous cells.
Within the eutopic endometrium, detection of driver mutations increases with age despite the
lack of remarkable histological changes. Other factors, particularly oral contraceptive use or
hormonal intrauterine device use may further modulate (reduce) risk of accumulating driver
mutations within endometrial tissues, such as has been observed as a decline in the frequency of
PTEN-null glands in women using these contraceptive methods[21] . Because of the lack of
follow-up with patients in our study, it remains unclear what role, if any, these mutations play in
the eutopic endometrium. Other obvious questions include whether mutations persist, harbored
in early progenitor populations, or do they disappear at each menstrual cycle re-emerging de-
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Oncogenic Mutations in Eutopic Endometrium
8
novo with the rapid proliferation of the endometrial lining each month[20]? Our observation of
surprisingly high frequency of driver mutations in the eutopic endometrium of women without
evidence of malignancy or even subtle pathology suggests that care must be taken when
interpreting detected mutations in non-cancer affected individuals. Ongoing preclinical
development of mutation detection assays have suggested non-cancer affected populations are
unaffected by somatic driver alterations[39], many of which overlapped with our assays.
However, closer inspection suggests at least some studies may not show a full picture with both
sampling methodology and control population age-bias potentially contributing to the failure to
detect driver mutations in non-cancer populations. The development of screening methods for
occult or pre-cancerous disease will need to incorporate appropriate specimen sampling, age-
appropriate control populations, and a solid understanding of normal age-related somatic
mutation accumulation.
In summary, our findings highlight the complexity of the eutopic endometrium and challenge our
current understanding of so-called “normal tissues”. As the mutations identified are obviously
oncogenic in other tissues, these findings highlight the need to consider cell context and
microenvironment along with mutation in the development of cancer.
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Acknowledgements
This research is funded by the Canadian Cancer Society (Impact grant #701603), Canadian
Institutes of Health Research (Foundation grant #154290), and the Janet D. Cottrelle Foundation
through the BC Cancer Foundation. The VGH & UBC Hospital Foundation and the BC Cancer
Foundation provided funding to OVCARE: BC’s Ovarian Cancer Research Team. A Frederick
Banting and Charles Best Canada Graduate Scholarship from the Canadian Institutes of Health
Research provided support to V. Lac. The Janet D. Cottrelle Foundation Scholars fund provided
support to M.S. Anglesio. The Dr. Chew Wei Memorial Professorship in Gynecologic Oncology
and the Canada Research Chairs program (Research Chair in Molecular and Genomic Pathology)
provided support to D.G. Huntsman. The Michael Smith Foundation for Health Research Health
Professional-Investigator Award provided support to P.J. Yong.
We would also like to acknowledge the staff at the Genetic Pathology Evaluation Centre
(GPEC), the Department of Anatomical Pathology at the Vancouver General Hospital in
Vancouver, OVCARE’s gynaecological tissue bank, and the Calgary Laboratory Services for
their assistance with specimen collection, immunohistochemical staining and optimization, and
tissue sectioning.
Statement of Author Contributions:
VL, MSA, and DGH designed the study. TMN and BT-C identified specimens for the study, VL,
AL, JK, TP, and MM processed samples, and performed experiments. TMN, BT-C, and MK
reviewed pathology and generated/reviewed IHC data. VL and RA-H performed data analysis.
AA and DC provided statistical design input and oversight. PJY and BCG provided clinical input
to the study design. VL drafted the manuscript. All authors revised the manuscript and approved
submission of the final version.
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not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available
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Oncogenic Mutations in Eutopic Endometrium
10
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Oncogenic Mutations in Eutopic Endometrium
12
Table 1. Mutational findings within normal endometrium samples from hysterectomy patients
and corresponding variant allele frequencies (VAF) determine through targeted sequencing and
droplet digital PCR (ddPCR).
Patient and
Block ID
Region of Uterus
Sampled
PTEN IHC Driver Mutation
Identified
VAF (%) -
Sequencing
VAF (%) -
ddPCR
Hx_2A ante rior normal
Hx_2B posteri or normal ERBB2 S310F 0.974 0.792
Hx_4A ante rior loss - zonal
Hx_4B posteri or normal
Hx_5A ante rior loss - zonal
Hx_5B posteri or normal
Hx_6A ante rior normal KRAS G12V 2.654 1.63
Hx_6B posteri or normal KRAS G12A 1.408 1.08
Hx_7A posteri or loss - zonal
Hx_7B ante rior normal
Hx_8A posteri or loss - zonal
Hx_8B ante rior loss - zonal
Hx_9A ante rior normal
Hx_9B posteri or loss - zonal KRAS G13D 2.16 1.95
Hx_10A n/a normal
Hx_10B n/a loss - zonal
Hx_12A ante rior normal PIK3CA R88Q 1.337 1.23
Hx_12B posteri or normal
Hx_13A posteri or normal PIK3CA H1047R 2.497 3.36
KRAS G12C 1.036 0.538
Hx_13B ante rior normal
Hx_16A ante rior normal KRAS G12V 1.079 1.06
PIK3CA E542K 1.015 0.897
Hx_16B posteri or loss - zonal PIK3CA H1047R 2.402 1.92
Hx_18A ante rior normal FGFR2 K659E 5.505 7.77
KRAS G12V 1.551 1.24
Hx_18B posteri or loss - zonal
Hx_21A ante rior normal KRAS G12D 5.587 4.71
PIK3CA M1043I 2.39 2.27
Hx_21B posteri or normal KRAS G12V 6.112 6.32
PIK3CA H1047R 2.373 2.76
FGFR2 S252W 1.889 1.17
Hx_22A ante rior loss - zonal
Hx_22B posteri or normal
Hx_23A ante rior n/a
Hx_23B posteri or normal KRAS G12D 11.866 10.2
Hx_25A n/a normal KRAS G12A 1.584 1.60
Hx_25B n/a loss - zonal KRAS G12A 1.670 1.00
*Data for nine patients without detectable somatic mutations or abnormal immunohistochemistry
findings are omitted from this table.
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Oncogenic Mutations in Eutopic Endometrium
13
Figure Legends:
Figure 1. Overview of somatic, oncogenic alterations detected in the eutopic endometrium from
(A) hysterectomy patients or (B) dilation and curettage or endometrial biopsy patients. Red
rectangles denote driver mutations detected by targeted sequencing, whereas blue rectangles
denote (zonal) loss detected through immunohistochemistry studies. The asterisk (*) denotes a
patient wherein zonal loss of PTEN as well as a PTEN driver mutation was detected.
Figure 2. The prevalence of somatic driver mutations in the eutopic endometrium across age.
According to this logistic regression model, the prevalence of mutation increases with age (OR:
1.05 (95% CI: 1.00 – 1.10), p = 0.035, Wald test).
Figure 3. (A) Comparison of the prevalence of somatic mutations in endometrial cancer versus
histologically normal eutopic endometrium (mutations found in endometrial cancer but were not
detected in any eutopic endometrium sample are not displayed). (B) KRAS mutation prevalence
across age in endometrial cancer samples versus normal endometrium samples. In normal
endometrium samples, the prevalence of KRAS mutation increases with age (OR = 1.06, 95% CI
= 1.01 – 1.11, p = 0.01953, Wald test), whereas it decreases with age in endometrial cancer
samples (OR = 0.96, 95% CI = 0.94 – 0.99, p = 0.0164, Wald test).
Supplementary Figure Legends:
Supplementary Figure S1. PTEN IHC studies of eutopic endometrium specimens showing
zonal loss of PTEN in epithelial cells and matching H&E staining.
Supplementary Figure S2. Comparison of point mutations detected in anterior and posterior
samplings from patients in the Hx cohort.
Supplementary Figure S3. Logistic regression model of mutation prevalence across age in
secretory phase versus proliferative phase endometrium
Supplementary Figure S4. Logistic regression model of mutation prevalence across age in
endometrial cancer versus normal endometrium.
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