Clinical factors as prognostic variables among molecular subgroups of endometrial cancer.

BACKGROUND: Clinical factors may influence endometrial cancer survival outcomes. We examined the prognostic significance of age, body mass index (BMI), and type 2 diabetes among molecular subgroups of endometrial cancer.
METHODS: This was a single institution retrospective study of patients who underwent surgery for endometrial carcinoma between January 2007 and December 2012. Tumors were classified into four molecular subgroups by immunohistochemistry of mismatch repair (MMR) proteins and p53, and sequencing of polymerase-ϵ (POLE). Overall, cancer-related, and non-cancer-related mortality were estimated using univariable and multivariable survival analyses.
RESULTS: Age >65 years was associated with increased mortality rates in the whole cohort (n = 515) and in the "no specific molecular profile" (NSMP) (n = 218) and MMR deficient (MMR-D) (n = 191) subgroups during a median follow-up time of 81 months (range 1‒136). However, hazard ratios for cancer-related mortality were non-significant for NSMP and MMR-D. Diabetes was associated with increased overall and non-cancer-related mortality in the whole cohort and MMR-D subgroup. Overweight/obesity had no effect on outcomes in the whole cohort, but was associated with decreased overall and cancer-related mortality in the NSMP subgroup, and increased overall and non-cancer-related mortality in the MMR-D subgroup. Overweight/obesity effect on cancer-related mortality in the NSMP subgroup remained unchanged after controlling for confounders. High-risk uterine factors were more common, and estrogen and progesterone receptor expression less common in NSMP subtype cancers of normal-weight patients compared with overweight/obese patients. No clinical factors were associated with outcomes in p53 aberrant (n = 69) and POLE mutant (n = 37) subgroups. No cancer-related deaths occurred in the POLE mutant subgroup.
CONCLUSIONS: The prognostic effects of age, BMI, and type 2 diabetes do not appear to be uniform for the molecular subgroups of endometrial cancer. Our data support further evaluation of BMI combined with genomics-based risk-assessment.

Introduction

Endometrial cancer is the most common gynecologic malignancy in developed countries, with an incidence of 10 to 16 cases per 100,000 women in Western and Northern Europe [1]. Old age has a negative impact on the survival of endometrial cancer patients [2, 3]. Compared with younger patients, those >65 years have poorer overall survival and disease-specific survival whether or not they underwent lymphadenectomy, and irrespective of the presence of nodal metastasis [2]. Age ≥60 years is an independent predictor of locoregional relapses and disease-related death in stage I endometrial cancer [3]. In contrast, reports on the prognostic significance of body mass index and diabetes in endometrial cancer are inconsistent, as summarized in several meta-analyses [4-6]. The heterogeneous results may be explained by a number of factors, including differences in study design and selection of study subjects, methods of body mass index and diabetes assessment, lack of power, and choice of the outcome of interest. By merely assessing overall survival, the impact of potential risk factors on cancer-related survival may be unrecognized.

Earlier prognostic studies [2-6] were mostly conducted prior to the development of the molecular classification system for endometrial cancer [7]; therefore, they did not address the role of molecular subgroups in modifying the prognostic effect of clinical factors. The molecular classification system, identified through The Cancer Genome Atlas (TCGA), categorizes endometrial cancers into four distinct subgroups: polymerase-ϵ (POLE) ultramutated; microsatellite unstable hypermutated; copy-number low; and copy-number high. This categorization is based on: overall mutational burden; p53, POLE, and phosphatase and tensin homolog (PTEN) mutations; microsatellite instability; and histology [7]. Molecular subgroups are associated with different prognoses, so that: POLE ultramutated tumors have an excellent progression-free survival, microsatellite unstable hypermutated and copy-number low tumors an intermediate progression-free survival; and copy-number high tumors a poor progression-free survival [7].

Given the fact that the molecular subgroups can be considered to be different disease entities, each subgroup should ideally be investigated separately in clinical research studies. Based on the putative role of clinical factors in determining the prognosis of endometrial cancer, we wanted to examine the association of age, body mass index, and type 2 diabetes with patient outcomes among the different molecular subgroups.

Materials and methods

Study population and data collection

Patients underwent surgical treatment for stage I–IV endometrial carcinoma at the Department of Obstetrics and Gynecology, Helsinki University Hospital, between January 1, 2007 and December 31, 2012. Standard surgery included total hysterectomy and bilateral salpingo-oophorectomy. Lymphadenectomy was performed in selected patients. Adjuvant therapy was tailored according to stage and histologic findings at surgery. Patients with early-stage endometrioid carcinoma with high-risk features generally received either vaginal brachytherapy or whole pelvic radiotherapy. Vaginal brachytherapy was mainly limited to patients in whom surgical nodal assessment was performed. Patients with non-endometrioid or advanced-stage endometrioid carcinoma received multimodality treatment with chemotherapy and radiation. Paclitaxel/carboplatin doublet was the standard chemotherapy regimen.

Clinicopathologic data were abstracted from institutional medical and pathology records. Weight and height were recorded at the time of endometrial cancer diagnosis. Overweight and obesity were specified as a body mass index 25–29.9 kg/m2 and ≥30 kg/m2, respectively, according to the World Health Organization (WHO) definitions. WHO class III obesity was defined as a body mass index ≥40 kg/m2. Information on diabetes mellitus was captured by patient intake history at the time of initial consultation. Stage was determined according to the International Federation of Gynecology and Obstetrics guidelines revised in 2009 [8]. The cut-off for age was based on the finding that age >65 years is an independent poor prognostic factor in endometrial cancer [2]. The choice of 5 cm as a determinant for the analysis of tumor size was based on earlier literature according to which size approximating the entire uterine cavity is strongly associated with survival in stage I endometrial cancer [9]. Lymphovascular space invasion was defined as the presence of adenocarcinoma, of any extent, in endothelium-lined channels of uterine specimens outside the tumor.

Cause of death was mainly based on medical records. Missing data were complemented from death certificates. The study was approved by the local institutional review board and the National Supervisory Authority for Welfare and Health. Informed consent was waived because of the retrospective nature of the study.

Molecular classification

Tumors were categorized into molecular subgroups according to the TransPORTEC classifier that recapitulates the four molecular subgroups of the TCGA as follows: “no specific molecular profile” (NSMP, surrogate to copy-number low in the TCGA classification system); mismatch repair deficient (MMR-D, surrogate to microsatellite unstable hypermutated); p53 abnormal (p53 abn, surrogate to copy-number high); and POLE mutant [10]. Minor adjustments were introduced to the TransPORTEC protocol. First, while our p53 and microsatellite instability analyses were solely based on immunohistochemistry, the TransPORTEC classifier uses a combination of TP53 mutational testing and p53 immunohistochemistry to determine p53 status, and primarily the Promega microsatellite instability analysis for determination of microsatellite instability status. For tumors exhibiting low levels of instability, or from which extracted DNA quality is poor, immunohistochemistry of MMR proteins is performed. Second, the TransPORTEC classifier detects POLE exonuclease domain hotspot mutations by Sanger sequencing of exons 9 and 13, whereas we performed sequencing of exons 9, 13, and 14. Lastly, we did not exclude cases with multiple classifying alterations. Instead, they were categorized according to the alteration that determines the clinical outcome [11, 12].

Patients with adequate tumor samples for a tissue microarray were eligible for the study. For the construction of tissue microarray, histologic slides were reviewed by a pathologist and representative areas of each tumor were marked on the slides. Four duplicate 0.8 mm cores were drawn from the corresponding area of the paraffin blocks and a tissue microarray block was prepared. The following monoclonal antibodies were used for chromogenic immunohistochemistry: MLH1 (ES05, Dako, Santa Clara, CA, USA); MSH2 (G219-1129, BD Biosciences, San Jose, CA, USA); MSH6 (EPR3945, Abcam, Cambridge, UK); PMS2 (EPR3947, Epitomics, Burlingame, CA, USA); and p53 (DO-7, Dako). Tissue microarray slides were scanned with three-dimensional Histech Pannoramic 250 Flash II scanner by Fimmic Oy (Helsinki, Finland). Slide images were managed and analyzed with WebMicroscope Software (Fimmic Oy). Virtual slides were scored by a pathologist blinded to clinical data. A second investigator examined equivocal cases and a consensus was reached. MMR protein status was considered deficient when we observed a complete loss of nuclear expression in carcinoma cells of one or more MMR proteins (MLH1, MSH2, MSH6, PMS2) detected by immunohistochemistry. Aberrant p53 staining was defined as strong and diffuse nuclear staining or completely negative (‘null’) staining in carcinoma cells. Weak and heterogeneous staining was classified as wild-type expression. Stromal cells and inflammatory cells served as internal controls for MMR and p53 stainings. Samples with scarce carcinoma cells or completely negative staining of the internal controls, when applicable, were discarded.

For DNA extraction, representative areas of formalin-fixed paraffin-embedded tumor tissue were macrodissected as identified by pathologist assessment. DNA was extracted by proteinase K/phenol-chloroform method. POLE exonuclease domain mutation (EDM) screening of hot spots in exon 9 (c.857C>G, p.P286R; c.890C>T, p.S297F), exon 13 (c.1231G>C, p.V411L), and exon 14 (c.1366G>C, p.A456P) was performed by direct sequencing. The following primers were used: Ex 9F (5’–3’): CCTAATGGGGAGTTTAGAGCTT; Ex 9R (5’–3’): CCCATCCCAGGAGCTTACTT; Ex 13F (5’–3’): TCTGTTCTCATTCTCCTTCCAG; Ex 13R (5’–3’): CGGGATGTGGCTTACGTG; Ex 14F (5’–3’): TGACCCTGGGCTCTTGATTT; Ex 14R (5’–3’): ACAGGACAGATAATGCTCACC. Polymerase chain reaction products were sequenced on an ABI3730XI Automatic DNA Sequencer (Applied Biosystems, Foster City, CA, USA). Sequence graphs were analyzed both manually and with Mutation Surveyor (Softgenetics, State College, PA, USA). Only cases with good-quality sequence for all the examined four POLE hot spots were included in the analysis.

For further characterization, the following monoclonal antibodies were used for chromogenic immunohistochemistry on multicore tissue microarray slides: estrogen receptor-α (SP1, Roche/Ventana, Oro Valley, AZ, USA); progesterone receptor (clone 16, Novocastra, Newcastle upon Tyne, UK); and L1 cell adhesion molecule (L1CAM, clone 14.10, Covance, Princeton, NJ, USA). The cut-off for positive estrogen and progesterone receptor expression was set at 10% based on endometrial cancer and breast cancer studies [13-15]. For L1CAM expression, ≥10% of membranous staining was considered positive [16-18].

Statistical methods

Chi-squared test was used for comparison of categorical variables, and analysis of variance and Kruskal-Wallis test for comparison of continuous variables after testing for normality by Shapiro-Wilk test. Hazard ratios for overall mortality, cancer-related mortality, and non-cancer-related mortality were estimated using univariable and multivariable Cox regression analyses. Cancer-related mortality was the main outcome measure. Variables with proven prognostic significance were entered as covariates in the multivariable model. These included stage [19], features of the primary tumor [20, 21], estrogen and progesterone receptor expression [13, 14, 22], L1CAM expression [16–18, 23], and adjuvant therapy [24]. Survival times were estimated using the Kaplan-Meier method. Differences between groups were compared using the log rank test. Survivals were calculated as the times from surgery to death. Statistical significance was set at P < 0.05. Data were analyzed using the Statistical Package for the Social Sciences version 25 software (IBM Corp., Armonk, NY, USA).

Results

A total of 515 endometrial carcinomas were classified into molecular subgroups. Twenty cases (3.9%) displayed multiple molecular features. Three cases displayed POLE EDM and either MMR-D or p53 abn, and one case had all three molecular alterations. These were classified as POLE EDM tumors [12]. Sixteen cases, classified as MMR-D tumors [11], displayed both MMR-D and p53 abn. The basic characteristics of the study population are summarized in Table 1. We found that POLE EDM is associated with younger age and lower body mass index, whereas p53 abn is associated with older age. The prevalence of type 2 diabetes was similar between molecular subgroups.

Table 1

Characteristics of the study population according to molecular subgroups.

	NSMP (n = 218)	POLE EDM (n = 37)	MMR-D (n = 191)	p53 abn (n = 69)	P
Age (years) [median (interquartile range)]	66 (60−73)	59 (53−68)	70 (61−77)	72 (66−78)	<0.0005
Age >65 years	116 (53.2%)	11 (29.7%)	121 (63.4%)	52 (75.4%)	<0.0005
Body mass index (kg/m2) [median (interquartile range)]	28.5 (24.3−33.2)	25.1 (23.0−28.3)	27.1 (23.3−32.7)	27.3 (24.4−30.5)	0.023
Overweight/obese	157 (72.0%)	21 (56.8%)	118 (61.8%)	45 (65.2%)	0.091
World Health Organization class III obesity	14 (6.4%)	1 (2.7%)	7 (3.7%)	3 (4.3%)	0.541
Type 2 diabetes	40 (18.3%)	4 (10.8%)	37 (19.4%)	13 (18.8%)	0.671
Pelvic lymphadenectomy	129 (59.2%)	23 (62.2%)	106 (55.5%)	32 (46.4%)	0.255
Pelvic-aortic lymphadenectomy	19 (8.7%)	5 (13.5%)	34 (17.8%)	22 (31.9%)	<0.0005
Stage					<0.0005
IA	123 (56.4%)	28 (75.7%)	84 (44.0%)	22 (31.9%)
IB	42 (19.3%)	6 (16.2%)	44 (23.0%)	18 (26.1%)
II	23 (10.6%)	2 (5.4%)	19 (9.9%)	1 (1.4%)
IIIA	9 (4.1%)	1 (2.7%)	13 (6.8%)	5 (7.2%)
IIIB	1 (0.5%)	0 (0%)	2 (1.0%)	1 (1.4%)
IIIC1	13 (6.0%)	0 (0%)	18 (9.4%)	3 (4.3%)
IIIC2	1 (0.5%)	0 (0%)	7 (3.7%)	9 (13.0%)
IVA	0 (0%)	0 (0%)	0 (0%)	0 (0%)
IVB	6 (2.8%)	0 (0%)	4 (2.1%)	10 (14.5%)
Histology					<0.0005
Endometrioid carcinoma	206 (94.5%)	34 (91.9%)	174 (91.1%)	36 (52.2%)
Clear cell carcinoma	5 (2.3%)	2 (5.4%)	5 (2.6%)	13 (18.8%)
Serous carcinoma	2 (0.9%)	1 (2.7%)	3 (1.6%)	11 (15.9%)
Carcinosarcoma	2 (0.9%)	0 (0%)	3 (1.6%)	7 (10.1%)
Undifferentiated carcinoma	3 (1.4%)	0 (0%)	6 (3.1%)	2 (2.9%)
Grade (For endometrioid only; n = 450)					<0.0005
1	141 (68.4%)	21 (61.8%)	79 (45.4%)	5 (13.9%)
2	52 (25.2%)	8 (23.5%)	54 (31.0%)	15 (41.7%)
3	13 (6.3%)	5 (14.7%)	41 (23.6%)	16 (44.4%)
Adjuvant therapy					<0.0005
None	33 (15.1%)	6 (16.2%)	20 (10.5%)	7 (10.1%)
Vaginal brachytherapy	116 (53.2%)	22 (59.5%)	83 (43.5%)	18 (26.1%)
Pelvic radiotherapy	28 (12.8%)	6 (16.2%)	35 (18.3%)	12 (17.4%)
Chemotherapy	7 (3.2%)	0 (0%)	8 (4.2%)	7 (10.1%)
Chemotherapy and vaginal brachytherapy	10 (4.6%)	0 (0%)	10 (5.2%)	11 (15.9%)
Chemotherapy and pelvic radiotherapy	24 (11.0%)	3 (8.1%)	35 (18.3%)	14 (20.3%)

Abbreviations: MMR-D, mismatch repair deficient; NSMP, no specific molecular profile; POLE EDM, polymerase-ϵ exonuclease domain mutation; p53 abn, p53 abnormal.

Median follow-up time was 81 months (range 1–136). During follow-up a total of 160 patients died, including 97 deaths related to endometrial cancer (Table 2).

Table 2

Univariable Cox regression analyses of overall, cancer-related and non-cancer-related mortality.

	Mortality	All	NSMP	POLE EDM	MMR-D	p53 abn
		(n = 515)	(n = 218)	(n = 37)	(n = 191)	(n = 69)
		HR (95% CI)	HR (95% CI)	HR (95% CI)	HR (95% CI)	HR (95% CI)
Age >65 Years	Overall †	2.7 (1.9−3.9) P < 0.0005	2.8 (1.4−5.5) P = 0.004	4.6 (0.42−51) P = 0.212	2.6 (1.5−4.4) P = 0.001	0.95 (0.45−2.0) P = 0.900
	Cancer-related ‡	1.7 (1.1−2.6) P = 0.016	2.0 (0.87−4.7) P = 0.102	‒	1.3 (0.68−2.4) P = 0.461	0.74 (0.33−1.7) P = 0.471
	Non-cancer-related §	8.2 (3.5−19) P < 0.0005	4.8 (1.4−17) P = 0.013	4.6 (0.42−51) P = 0.212	23 (3.1−165) P = 0.002	2.7 (0.34−21) P = 0.353
Overweight/ Obese	Overall †	0.82 (0.60−1.1) P = 0.218	0.37 (0.21−0.68) P = 0.001	0.37 (0.033−4.0) P = 0.410	1.8 (1.1−3.0) P = 0.018	0.65 (0.34−1.2) P = 0.190
	Cancer-related ‡	0.72 (0.48−1.1) P = 0.104	0.32 (0.15−0.71) P = 0.005	‒	1.3 (0.72−2.5) P = 0.356	0.69 (0.33−1.5) P = 0.327
	Non-cancer-related §	1.0 (0.60−1.7) P = 0.954	0.46 (0.18−1.2) P = 0.101	0.37 (0.033−4.0 P = 0.410	3.1 (1.3−7.5) P = 0.013	0.56 (0.16−1.9) P = 0.364
Type 2 diabetes	Overall †	1.5 (1.1−2.2) P = 0.019	0.87 (0.39−1.9) P = 0.729	5.0 (0.45−55) P = 0.191	2.5 (1.5−4.0) P < 0.0005	0.95 (0.42−2.2) P = 0.907
	Cancer-related ‡	1.0 (0.62−1.8) P = 0.876	0.61 (0.18−2.0) P = 0.421	‒	1.8 (0.91−3.6) P = 0.089	0.51 (0.15−1.7) P = 0.266
	Non-cancer-related §	2.5 (1.5−4.3) P < 0.0005	1.3 (0.42−3.9) P = 0.674	5.0 (0.45−55) P = 0.191	3.6 (1.8−7.4) P < 0.0005	2.8 (0.79−10) P = 0.111

† N deaths = 160 (n = 43, n = 3, n = 76 and n = 38 for NSMP, POLE EDM, MMR-D and p53 abn, respectively)

‡ N deaths = 97 (n = 25, n = 0, n = 44 and n = 28 for NSMP, POLE EDM, MMR-D and p53 abn, respectively).

§ N deaths = 63 (n = 18, n = 3, n = 32 and n = 10 for NSMP, POLE EDM, MMR-D and p53 abn, respectively).

Abbreviations: CI, confidence interval; HR, hazard ratio; MMR-D, mismatch repair deficient; NSMP, no specific molecular profile; POLE EDM, polymerase-ϵ exonuclease domain mutation; p53 abn, p53 abnormal.

Univariable Cox regression analyses were performed separately for overall mortality, cancer-related mortality, and non-cancer-related mortality (Table 2). Associations of clinical factors with the outcomes were first examined in the whole cohort. Old age (>65 years) was invariably associated with poor outcomes. Overweight/obesity (body mass index ≥25 kg/m2) was not associated with any of the outcomes, whereas type 2 diabetes was associated with increased overall mortality and non-cancer-related mortality.

Associations were then examined separately for each molecular subgroup (Table 2). Old age was associated with increased overall mortality and non-cancer-related mortality in NSMP and MMR-D subgroups. Overweight/obesity and type 2 diabetes were associated with increased overall mortality and non-cancer-related mortality in the MMR-D subgroup. In the NSMP subgroup, overweight/obesity was associated with decreased overall mortality and cancer-related mortality, our main outcome of interest. For POLE EDM and p53 abn, significant associations between clinical factors and outcomes were not observed. Hazard ratios for cancer-related mortality were not calculable in the POLE EDM subgroup because there were no cancer-related deaths in this subgroup of patients.

Kaplan-Meier disease-specific survival analyses were performed separately for three body mass index categories in the NSMP subgroup. Disease-specific survival was similarly improved for overweight patients (body mass index 25−29.9 kg/m2) and obese patients (body mass index ≥30 kg/m2) compared with normal-weight patients (body mass index <25 kg/m2) (Fig 1). Body mass index 25 kg/m2 was therefore selected as the cut-off for further analyses.

Fig 1

Kaplan-Meier disease-specific survival analyses concerning body mass index in the “no specific molecular profile” subgroup.

Table 3 shows the proportions of various prognostic variables in normal-weight and overweight/obese patients with NSMP subtype cancer. High-risk histology, deep myometrial invasion (≥50%), and lymphovascular space invasion were more common in normal-weight compared with overweight/obese patients. Moreover, estrogen and progesterone receptor expression was less common in normal-weight patients. L1CAM expression and proportions of old patients (>65 years), stage II−IV cancers, large tumors (>5 cm), and adjuvant therapies received were not significantly different for normal-weight and overweight/obese patients.

Table 3

Proportions of various prognostic variables in normal-weight and overweight/obese patients with “no specific molecular profile” subtype endometrial cancer.

	Normal-weight (n = 61)	Overweight/obese (n = 157)	P
Age >65 years	33 (54.1%)	83 (52.9%)	0.870
Stage II−IV	18 (29.5%)	35 (22.3%)	0.265
Histology			<0.0005
Endometrioid grade 1−2 carcinoma	44 (72.1%)	149 (94.9%)
Endometrioid grade 3 carcinoma	9 (14.8%)	4 (2.5%)
Non-endometrioid carcinoma	8 (13.1%)	4 (2.5%)
Myometrial invasion ≥50%	30 (49.2%)	53 (33.8%)	0.035
Tumor size >5 cm †	17 (28.8%)	27 (18.9%)	0.120
Lymphovascular space invasion	21 (34.4%)	28 (17.8%)	0.008
Estrogen receptor expression ‡	48 (80.0%)	143 (94.1%)	0.002
Progesterone receptor expression §	40 (66.7%)	139 (89.1%)	<0.0005
L1 cell adhesion molecule expression ¶	6 (10.3%)	8 (5.3%)	0.187
Adjuvant therapy			0.537
None or vaginal brachytherapy	39 (63.9%)	110 (70.1%)
Pelvic radiotherapy	7 (11.5%)	21 (13.4%)
Chemotherapy	7 (11.5%)	10 (6.4%)
Chemotherapy and pelvic radiotherapy	8 (13.1%)	16 (10.2%)

† Data missing for 2 normal-weight and 14 overweight/obese patients

‡ data missing for 1 normal-weight and 5 overweight/obese patients

§ data missing for 1 normal-weight and 1 overweight/obese patient

¶ data missing for 3 normal-weight and 5 overweight/obese patients.

To assess the contribution of various clinicopathologic variables to patient outcome in the NSMP subgroup, we performed univariable and multivariable Cox regression analyses of cancer-related mortality (Table 4). All of the tested variables, i.e. overweight/obesity, stage, features of the primary tumor, estrogen and progesterone receptor expression, L1CAM expression, and adjuvant therapy, were associated with cancer-related mortality in unadjusted analyses. In the multivariable model, only overweight/obesity was found to have a significant independent effect on the outcome.

Table 4

Univariable and multivariable Cox regression analyses of cancer-related mortality for the “no specific molecular profile” subgroup.

	Univariable (n = 218)			Multivariable (n = 186)
	N deaths = 25			N deaths = 20
	N (%)	HR (95% CI)	P	HR (95% CI)	P
Overweight/obese	157 (72.0%)	0.32 (0.15−0.71)	0.005	0.32 (0.11−0.92)	0.034
Stage II-IV	53 (24.3%)	5.3 (2.4−12)	<0.0005	6.1 (0.97−39)	0.053
Histology			<0.0005		0.425
Endometrioid grade 1−2 carcinoma	193 (88.5%)	1		1
Endometrioid grade 3 carcinoma	13 (6.0%)	14 (5.6−33)	<0.0005	3.2 (0.49−20)	0.228
Non-endometrioid carcinoma	12 (5.5%)	6.6 (2.2−20)	0.001	1.4 (0.19−10)	0.736
Myometrial invasion ≥50%	83 (38.1%)	5.7 (2.3−14)	<0.0005	2.9 (0.68−12)	0.153
Tumor size >5 cm †	44 (21.8%)	3.8 (1.7−8.4)	0.001	1.4 (0.38−4.8)	0.634
Lymphovascular space invasion	49 (22.5%)	5.9 (2.7−13)	<0.0005	1.8 (0.58−5.4)	0.315
Estrogen receptor expression ‡	191 (90.1%)	0.14 (0.063−0.32)	<0.0005	0.62 (0.11−3.5)	0.587
Progesterone receptor expression §	179 (82.9%)	0.28 (0.12−0.64)	0.003	1.6 (0.42−6.3)	0.483
L1 cell adhesion molecule expression ¶	14 (6.7%)	7.1 (2.8−18)	<0.0005	3.0 (0.61−14)	0.177
Adjuvant therapy			0.012		0.273
None or vaginal brachytherapy	149 (68.3%)	1		1
Pelvic radiotherapy	28 (12.8%)	1.4 (0.40−5.2)	0.573	0.20 (0.028−1.4)	0.111
Chemotherapy	17 (7.8%)	3.8 (1.2−12)	0.022	0.78 (0.14−4.3)	0.772
Chemotherapy and pelvic radiotherapy	24 (11.0%)	4.2 (1.6−11)	0.003	0.21 (0.026−1.7)	0.141

† Data missing for 16 patients

‡ data missing for 6 patients

§ data missing for 2 patients

¶ data missing for 8 patients.

Abbreviations: CI, confidence interval; HR, hazard ratio.

Discussion

We explored the variation and prognostic significance of age, overweight/obesity, and type 2 diabetes in 515 women with endometrial carcinoma that were classified into molecular subgroups by immunohistochemistry of MMR proteins and p53, as well as POLE sequencing. Old age, overweight/obesity, and type 2 diabetes in the MMR-D subgroup, and old age in the NSMP subgroup were associated with increased overall mortality and non-cancer-related mortality. Overweight/obesity was associated with decreased overall mortality and cancer-related mortality in the NSMP subgroup. POLE EDM was associated with younger age and lower body mass index, whereas p53 abn was associated with older age, in accordance with previous studies [25-27]. For these subgroups, significant associations between clinical factors and outcomes were not observed. Hazard ratios for cancer-related mortality were not calculable in the POLE EDM subgroup because there were no cancer-related events in this subgroup of patients. Clinicopathologic characteristics generally varied among subgroups, which can be explained by the fact that the molecular classifier employed in this study correlates with traditional prognostic factors of endometrial cancer [10].

To better understand the effect of body mass index on cancer-related mortality in the NSMP subgroup, we compared the proportions of various risk factors in normal-weight and overweight/obese patients in this subgroup, and found that high-risk uterine factors were more common in normal-weight patients. The presence of uterine risk factors is associated with increased risk for recurrences and poor survival, even in the absence of metastatic nodal disease [20, 21]. Lean patients in the NSMP subgroup also had a high-risk expression profile of molecular biomarkers. Expression of estrogen and progesterone receptors, known to be associated with improved endometrial cancer-specific survival [13, 14, 22], was less common in normal-weight patients compared with overweight/obese patients. Moreover, although not statistically significant, the expression of L1CAM, a poor prognostic factor in endometrial cancer [16–18, 23], was twice as common in normal-weight patients as in overweight/obese patients. When the prognostic effects of uterine risk factors and molecular biomarkers, along with overweight/obesity, stage and adjuvant therapy, were assessed in a multivariable model, only overweight/obesity had an independent effect on cancer-related mortality. This emphasizes the prognostic strength of body mass index in the NSMP subgroup, relative to other established risk factors.

This study is strengthened by the large sample size that allowed us to undertake analyses stratified into the various molecular subgroups of endometrial cancer. Admittedly, however, the smaller sizes of POLE EDM and p53 abn molecular subgroups may have precluded significant findings of clinical factors on outcomes in these subgroups. Information on cause of death was available for all of the deceased which allowed us to make a distinction in assessing not only overall mortality, but also cancer-related mortality, which can be considered the ideal outcome of interest when looking for causalities in cancer research. Knowledge of cancer-related deaths is especially important in endometrial cancer, for which competing causes of death are common; in the current study, 39% of deaths were secondary to causes other than endometrial cancer. Unlike most earlier studies, we were also able to distinguish between type 1 and type 2 diabetes. This improved the assessment of the true relation between diabetes and outcomes, as only type 2 diabetes appears to be prognostic in endometrial cancer [28].

Although our findings are limited to a single institution, the stage distribution and proportion of non-endometrioid carcinomas were comparable to an unselected cohort of 5,866 patients in the Gynecologic Oncology Group 210 surgical pathological staging study, in which the vast majority of tumors were early-stage endometrioid carcinomas [29]. The frequency of diabetes was captured by self-report, which could potentially lead to some misclassification. However, patient administered questionnaires, also used in our hospital, appear to be a reliable source of information in diabetes [30]. Information on the treatment of diabetes was unavailable for our study, which may partly distort the results, as metformin has been shown to improve overall survival and progression-free survival in patients with endometrial cancer [31].

Based on the current findings, endometrial cancer subgroups described by the TCGA represent not only unique genomic subgroups, but also entities that have distinct clinical prognostic features. Presuming that the proportions of molecular subgroups can vary across different study cohorts, the earlier contradictory findings [4-6] on clinical factors as prognosticators may be somewhat explained by the neutral effect of clinical factors on outcomes of POLE EDM and p53 abn subgroups, and partly opposing effect on outcomes of NSMP and MMR-D subgroups. Our findings may aid in patient counseling on the interrelation between dietary intake and prognosis, in addition to lending support to the implementation of body mass index in genomics-based risk-assessment. Future studies will probably show if refinement of genomics-based characterization can explain the different prognosis of patients with identical molecular subgroups but unlike clinical characteristics. For example, inactivation of PTEN, whose mutational frequency differs between TCGA subgroups [7], has been suggested to determine the outcome of endometrial cancer patients in the context of body mass index [32, 33].

In summary, our findings suggest that the prognostic effects of old age, overweight/obesity, and type 2 diabetes are not uniform for the molecular subgroups of endometrial cancer. Thus, clinical factors should be assessed as prognostic variables in conjunction with the molecular subgroup. The present data suggest that the metabolic consequences of adiposity play different roles in the aggressiveness of endometrial cancer, depending on the molecular subtype. Further work is needed to identify molecular pathways and prognostic biomarkers specific to women with different clinical characteristics.

28 Aug 2020

PONE-D-20-16843

Demographic factors as prognostic variables among molecular subgroups of endometrial cancer

PLOS ONE

Dear Dr. Loukovaara,

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Ludmila Vodickova, M.D., PhD

Academic Editor

PLOS ONE

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Reviewer #2: Partly

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: The authors conducted a single center retrospective study to evaluate the association between demographic factors such as age, body mass index and diabetes and outcomes among the different molecular subgroups of endometrial cancer. This is a topic of interest as our understanding of the underlying molecular biology of endometrial cancer has improved. Overall the manuscript is well written.

The abstract conclusion is too strong given the retrospective nature of the study and limited sample size within some of the subgroups. Recommend changing to "The prognostic effects of age, body mass index and type 2 diabetes do not appear to be uniform for the molecular subgroups of endometrial cancer." Also the data may support further evaluation of body mass index combined with genomics-based risk-assessment for discussion regarding prognosis but hard to argue implementation of BMI FOR genomic-based risk assessment.

Lines 164-166 - This section "Twenty cases (3.9%) displayed multiple molecular features. Three cases displayed POLE EDM and either MMR-D or p53 abn, and one case had all three molecular alterations. These were classified as POLE EDM tumors. Sixteen cases, classified as MMR-D tumors, displayed both MMR-D and p53 abn." belongs in the results section. In the methods please detail how you made this decision to categorize this cases in the manner you chose. Quit frankly this is problematic as these case may represent mixed histologic subtypes. While mixed endometrial cancers are rare they definitely are present and often the prognosis follows the highest grade. In the TCGA study 62% of the mixed histology clustered with CNH subgroup. While the authors used p53 protein expression as a surrogate for mutations this technology is not the same as some cancers with TP53 mutations may stain negative. Moreover, cancers could be grouped as CNH and not harbor a TP53 mutation (10%). Did histologic findings, ER/PR status, assist in distinguishing these cases further and what were the histologic and grade criteria for these 20 cases. If you rerun your analysis without these 20 cases do your results change?

Lines 312-313 The authors state "This may be the first study investigating associations of demographic factors with survival in the molecular subgroups of endometrial cancer described by the TCGA." you may want to consider deleting "This may be the first. . . " Also consider adding Dr. Roque manuscript "Association between differential gene expression and body mass index amon endometrial cancer from TCGA Project." Gynecology Oncol 2016 to support your findings.

Discussion - one issue to consider is that the patients evaluated in your study may not have a high frequency of morbid obesity. The worse survival outcomes are really seen in this group of patients. What is the percentage of patients with BMI>40 in each category? see Von Gruenigen et al paper regarding the outcomes of patients on GOG99.

Von Gruenigen VE, Tian C, Frasure H, Waggoner S, Keys H, Barakat RR. Treatment effects, disease recurrence, and survival in obese women with early endometrial carcinoma : a Gynecologic Oncology Group study. Cancer 2006;107(12):2786-91

There is also the issue of paradoxical obesity - obese patients tend to have a lower grade of disease and as you alluded may have a more favorable disease biology for those in the NSMP group.

Reviewer #2: This is an interesting study and as far as I know, it is the first to examine the impact of potentially important clinical predictors on endometrial cancer outcomes stratified by molecular subgroup.

The strengths of the manuscript include its novelty, large numbers from a single centre perspective, complete molecular subgroup assignment using standardised immunohistochemistry and POLE sequencing, long follow up and almost complete survival outcome data.

The weaknesses of the manuscript mostly relate to sample size since the study is underpowered to examine the associations between clinico-pathological factors and survival outcomes within each molecular subgroup, particularly when considering the POLE mutant and p53 subgroups. So really, this study can only examine the influence of clinical factors on outcomes from endometrial cancer in the NSMP and MMRd groups. Nonetheless, I think this manuscript is still of sufficient interest for publication since it will stimulate further research in this area and a sufficiently powered study would need several thousand patients - which is obviously unrealistic to achieve without a signal from a smaller study like this.

Considerations for the authors, to help improve the manuscript:

1. The English could be improved in places, for example, in the abstract "For POLE mutant (n = 37) and p53 aberrant (n = 69) subgroups, significant associations between demographic factors and overall mortality, cancer-related mortality and non-cancer related mortality were not observed during a median follow-up time of 81 months (range 1-136)." - this would definitely be better phrased ""For POLE mutant (n = 37) and p53 aberrant (n = 69) subgroups, no significant associations were observed between demographic factors and overall mortality, cancer-related mortality and non-cancer related mortality during a median follow-up time of 81 months (range 1-136)." This is a single example but there are multiple places where the English could do with a re-write.

2. The results would benefit from information regarding overall, cancer-specific and non-cancer deaths in the whole cohort and with respect to the 4 molecular subgroups. This isn't novel of course but it does help the reader to see that the expected outcomes are seen in this cohort and that the subgroups are behaving as predicted. If we know the cohort is representative, we can trust the subsequent analyses using the cohort. I think it needs a whole paragraph (and maybe Kaplan Meier curves for the 4 subgroups) detailing the outcomes of the whole cohort and then the outcomes by subgroup, including numbers of deaths. The death count is added as a footnote to a table at the moment, but that was the only place where it was visible to me.

3. The manuscript reads like a bit of a hotch potch rather than telling a story. I think it would benefit from a complete re-write, especially the introduction and discussion. There is a story here but the authors aren't telling it. The study is showing that tumour biology predominates in the excellent (POLE) and poor (p53) prognosis molecular subgroups, but in the intermediate prognosis groups, clinical factors become more important. It makes sense that cancer-related deaths are less common with obesity in the NSMP group where obesity predisposes to low grade, early stage endometrial cancer. It is not clear thus far the impact of obesity in the MMRd group, and this study helps to start documenting this. I think the introduction and discussion could be improved by telling the big picture first rather than individually reporting on the minutiae of each aspect of the study, without bringing it all together in a story.

Minor points for correction:

Line 25: Demographic factors have been suggested to be prognostic in endometrial cancer. Needs re-writing. What about "Clinical factors may influence endometrial cancer survival outcomes." BMI is not strictly demographic and the English as written is poor.

Line 28-30: Methods are incompletely described. No mention of years of accrual of cohort. No mention of setting. No mention of what survival outcomes, how they were obtained. No mention of stats used.

Line 31-33: See point 1

Line 43-45: Not keen on this conclusion. The last sentence should be deleted. Isn't your conclusion that tumour biology predominates for excellent (POLE) and poor prognostic (p53) subgroups, but in the NSMP and MMRd subgroups, clinical factors may influence survival outcomes in endometrial cancer?

Introduction: This is too long. It discusses the minutiae of the association of obesity, diabetes and age on endometrial cancer survival outcomes. It should be about one page in total length, give the big picture not the detail, explaining the rationale for the study set in the context of what the problem is you are trying to address.

Methods: What variables were included in the multivariable analysis. It is impossible to comment on the robustness of the analyses or the conclusions made without knowing what has been included here.

Results: Table 1 - please clarify how many patients had/ did not have adjuvant therapy before describing the detail of what they had. It appears that a very high proportion of patients had some form of adjuvant treatment even though there were lots of grade 1 stage 1a endometrial cancers in the cohort. This needs to be clarified.

Discussion: Much easier to follow if presented as a story. Start with a summary of the main findings before talking about your findings in the context of previous work, strengths/ limitations, clinical implications and future work. Limit to 4 pages.

**********

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22 Sep 2020

Ludmila Vodickova, MD, PhD

Academic Editor

PLOS ONE

September 20, 2020

Dear Editor:

Thank you for your e-mail of August 28. We have addressed the questions raised by the Journal and Reviewers as follows:

Additional Journal Requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Author response: PLOS ONE style requirements are met.

2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.

Author response: Participant consent was waived because this was a retrospective study where consent was difficult or impossible to obtain. This is now stated in the manuscript (lines 108-109). Instead of participant consent, the institutional review board called for an approval by the National Supervisory Authority for Welfare and Health, which was granted (lines 107-108).

Reviewer #1:

The abstract conclusion is too strong given the retrospective nature of the study and limited sample size within some of the subgroups. Recommend changing to "The prognostic effects of age, body mass index and type 2 diabetes do not appear to be uniform for the molecular subgroups of endometrial cancer." Also the data may support further evaluation of body mass index combined with genomics-based risk-assessment for discussion regarding prognosis but hard to argue implementation of BMI FOR genomic-based risk assessment.

Author response: The abstract conclusion has been changed as suggested by the Reviewer.

Lines 164-166 - This section "Twenty cases (3.9%) displayed multiple molecular features. Three cases displayed POLE EDM and either MMR-D or p53 abn, and one case had all three molecular alterations. These were classified as POLE EDM tumors. Sixteen cases, classified as MMR-D tumors, displayed both MMR-D and p53 abn." belongs in the results section. In the methods please detail how you made this decision to categorize this cases in the manner you chose. Quit frankly this is problematic as these case may represent mixed histologic subtypes. While mixed endometrial cancers are rare they definitely are present and often the prognosis follows the highest grade. In the TCGA study 62% of the mixed histology clustered with CNH subgroup. While the authors used p53 protein expression as a surrogate for mutations this technology is not the same as some cancers with TP53 mutations may stain negative. Moreover, cancers could be grouped as CNH and not harbor a TP53 mutation (10%). Did histologic findings, ER/PR status, assist in distinguishing these cases further and what were the histologic and grade criteria for these 20 cases. If you rerun your analysis without these 20 cases do your results change?

Author response: Data on multiple classifiers can now be found in the results section (lines 182-186). Categorization of multiple classifiers was based on clinical outcomes of these tumors, as reported in recent literature (lines 125-126, references #11 and #12). Given the fact that the TCGA classification system is not primarily based on morphology, our approach may be more relevant than categorization according to histologic criteria (or ER/PR status). Multiple classifiers were categorized either as POLE EDM (n = 4) or MMR-D (n = 16). Their histology distributions were as follows:

-POLE EDM (n = 4): 1 grade 2 endometrioid carcinoma, 1 grade 3 endometrioid carcinoma, 1 clear cell carcinoma, and 1 serous carcinoma

-MMR-D (n = 16): 6 grade 2 endometrioid carcinomas, 7 grade 3 endometrioid carcinomas, 1 serous carcinoma, 1 carcinosarcoma, and 1 undifferentiated carcinoma

These data are not shown in the manuscript because the number of multiple classifiers was too small for a meaningful comparison with single classifiers.

Hazard ratios for mortality outcomes remained essentially unaltered after exclusion of multiple classifiers from the POLE EDM and MMR-D subgroups (not shown).

Lines 312-313 The authors state "This may be the first study investigating associations of demographic factors with survival in the molecular subgroups of endometrial cancer described by the TCGA." you may want to consider deleting "This may be the first. . . " Also consider adding Dr. Roque manuscript "Association between differential gene expression and body mass index among endometrial cancer from TCGA Project." Gynecology Oncol 2016 to support your findings.

Author response: Roque et al. evaluated differences in gene expression profiles of obese and non-obese women with endometrial cancer and examined the association of BMI within the clusters identified in TCGA. However, associations of BMI with survival outcomes were not examined. Regardless, we have rephrased the sentence in the discussion as suggested (lines 310-311). The article by Roque et al. is now cited (reference #27).

Discussion - one issue to consider is that the patients evaluated in your study may not have a high frequency of morbid obesity. The worse survival outcomes are really seen in this group of patients. What is the percentage of patients with BMI>40 in each category? see Von Gruenigen et al paper regarding the outcomes of patients on GOG99.

Author response: The proportion of morbidly obese patients (BMI ≥40 kg/m2) in each molecular subgroup can now be found in Table 1. The rate of morbid obesity was too small for further analyses.

There is also the issue of paradoxical obesity - obese patients tend to have a lower grade of disease and as you alluded may have a more favorable disease biology for those in the NSMP group.

Author response: The multivariable analysis of cancer-related mortality in the NSMP subgroup included histology and grade as confounders (Table 4). The hazard ratio for overweight/obesity remained significant in this analysis. It could therefore be assumed that BMI has an independent effect on patient outcome in this subgroup.

Reviewer #2:

Considerations for the authors, to help improve the manuscript:

1. The English could be improved in places, for example, in the abstract "For POLE mutant (n = 37) and p53 aberrant (n = 69) subgroups, significant associations between demographic factors and overall mortality, cancer-related mortality and non-cancer related mortality were not observed during a median follow-up time of 81 months (range 1-136)." - this would definitely be better phrased ""For POLE mutant (n = 37) and p53 aberrant (n = 69) subgroups, no significant associations were observed between demographic factors and overall mortality, cancer-related mortality and non-cancer related mortality during a median follow-up time of 81 months (range 1-136)." This is a single example but there are multiple places where the English could do with a re-write.

Author response: This sentence in the abstract was deleted as the abstract was for the most part rewritten. The whole manuscript has now been edited by a professional language editing service (Helsinki University Language Center).

2. The results would benefit from information regarding overall, cancer-specific and non-cancer deaths in the whole cohort and with respect to the 4 molecular subgroups. This isn't novel of course but it does help the reader to see that the expected outcomes are seen in this cohort and that the subgroups are behaving as predicted. If we know the cohort is representative, we can trust the subsequent analyses using the cohort. I think it needs a whole paragraph (and maybe Kaplan Meier curves for the 4 subgroups) detailing the outcomes of the whole cohort and then the outcomes by subgroup, including numbers of deaths. The death count is added as a footnote to a table at the moment, but that was the only place where it was visible to me.

Author response: A column showing mortality data for the whole cohort has been added to Table 2. Numbers of deaths in the whole cohort and in each subgroup are shown as a footnote in Table 2. Numbers of deaths in the whole cohort are now also reported in the text (lines 192-193).

3. The manuscript reads like a bit of a hotch potch rather than telling a story. I think it would benefit from a complete re-write, especially the introduction and discussion. There is a story here but the authors aren't telling it. The study is showing that tumour biology predominates in the excellent (POLE) and poor (p53) prognosis molecular subgroups, but in the intermediate prognosis groups, clinical factors become more important. It makes sense that cancer-related deaths are less common with obesity in the NSMP group where obesity predisposes to low grade, early stage endometrial cancer. It is not clear thus far the impact of obesity in the MMRd group, and this study helps to start documenting this. I think the introduction and discussion could be improved by telling the big picture first rather than individually reporting on the minutiae of each aspect of the study, without bringing it all together in a story.

Author response: The introduction and discussion have been rewritten. The introduction is now shorter. The discussion begins with a summary of the main findings.

Minor points for correction:

Line 25: Demographic factors have been suggested to be prognostic in endometrial cancer. Needs re-writing. What about "Clinical factors may influence endometrial cancer survival outcomes." BMI is not strictly demographic and the English as written is poor.

Author response: Corrected as suggested by the Reviewer (line 24). The same correction (word “clinical” instead of “demographic”) has been made throughout the manuscript, including the title.

Line 28-30: Methods are incompletely described. No mention of years of accrual of cohort. No mention of setting. No mention of what survival outcomes, how they were obtained. No mention of stats used.

Author response: The abstract methods has been complemented as suggested by the Reviewer.

Line 31-33: See point 1

Author response: Please see our response to point 1.

Line 43-45: Not keen on this conclusion. The last sentence should be deleted. Isn't your conclusion that tumour biology predominates for excellent (POLE) and poor prognostic (p53) subgroups, but in the NSMP and MMRd subgroups, clinical factors may influence survival outcomes in endometrial cancer?

Author response: The abstract conclusion has been changed as suggested by Reviewer #1, please see above.

Introduction: This is too long. It discusses the minutiae of the association of obesity, diabetes and age on endometrial cancer survival outcomes. It should be about one page in total length, give the big picture not the detail, explaining the rationale for the study set in the context of what the problem is you are trying to address.

Author response: Please see our response to point 3.

Methods: What variables were included in the multivariable analysis. It is impossible to comment on the robustness of the analyses or the conclusions made without knowing what has been included here.

Author response: Variables included in the multivariable analysis are found in Table 4. They can now also be found in the Methods section, along with appropriate references (lines 173-175).

Results: Table 1 - please clarify how many patients had/ did not have adjuvant therapy before describing the detail of what they had. It appears that a very high proportion of patients had some form of adjuvant treatment even though there were lots of grade 1 stage 1a endometrial cancers in the cohort. This needs to be clarified.

Author response: A new line has been added to Table 1, showing the number of patients who did not receive any adjuvant therapies. Stratification of patients to adjuvant therapies is outlined in Materials and methods (lines 86-92).

Discussion: Much easier to follow if presented as a story. Start with a summary of the main findings before talking about your findings in the context of previous work, strengths/ limitations, clinical implications and future work. Limit to 4 pages.

Author response: Please see our response to point 3.

We thank the Reviewers for the valuable comments which helped us to improve the presentation considerably. A clean and marked version of the revised manuscript have been uploaded in the editorial system. In the marked version, changes are shown as red and strikethrough text. We hope that the revised manuscript will be found suitable for publication in PLOS ONE.

With kind regards,

Mikko Loukovaara, MD

Department of Obstetrics and Gynecology

Helsinki University Hospital and University of Helsinki

P.O. Box 140, 00029 HUS, Helsinki, Finland

Tel.: +358504272526

Fax: +358947173640

E-mail: mikko.loukovaara@hus.fi

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

9 Nov 2020

Clinical factors as prognostic variables among molecular subgroups of endometrial cancer

PONE-D-20-16843R1

Dear Dr. Loukovaara,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Ludmila Vodickova, M.D., PhD

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The manuscript is much improved. Please do not use the term 'morbid obesity'. It is pejorative and labelling. Please instead refer simply to BMI>40 or, if you must classify, to WHO class III obesity. Since the term is mentioned only twice in the whole manuscript, with one of those times to define it, my guess would be you can stick to BMI >40 and refer to overweight/obesity as BMI>25.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

13 Nov 2020

PONE-D-20-16843R1

Clinical factors as prognostic variables among molecular subgroups of endometrial cancer

Dear Dr. Loukovaara:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

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