Obesity and gynecological cancers: A toxic relationship

Abstract

Despite the evidence supporting the relevance of obesity and obesity-associated disorders in the development, management, and prognosis of various cancers, obesity rates continue to increase worldwide. Growing evidence supports the involvement of obesity in the development of gynecologic malignancies. This article explores the molecular basis governing the alteration of hallmarks of cancer in the development of obesity-related gynecologic malignancies encompassing cervical, endometrial, and ovarian cancers. We highlight specific examples of how development, management, and prognosis are affected for each cancer, incorporate current knowledge on complementary approaches including lifestyle interventions to improve patient outcomes, and highlight how new technologies are helping us better understand the biology underlying this neglected pandemic.

Keywords: FIGO Cancer Report; carcinogenesis; endometrial neoplasms; obesity; ovarian neoplasms; prognoses; treatment outcome; uterine cervix neoplasms.

FIGURE 1

Trends in obesity rates among women from 20 OECD countries between 1975 and 2016. On the left, trends in countries that currently present obesity prevalence less than 25%. On the right, countries where current prevalence exceeds 25%. The continuous black line (red dots) indicates the average rate trend for 10 countries analyzed. Graphs were built after downloading data from OurWorldInData.org .

FIGURE 2

Trends in age‐standardized incidence and mortality rates for obesity‐related and nonrelated cancers among women between 1978 and 2016 in the USA (according to nine SEER registers). Top graphs summarize trends in incidence rates. Bottom graphs show trends in mortality rates. The continuous black line (red dots) indicates the average rate trend for all cancers analyzed. Graphs were built after downloading data from the Global Cancer Observatory , , .

FIGURE 3

Trends in age‐standardized incidence (1993–2012) and mortality (1990–2016) rates for ovarian cancer in 20 OECD countries. On the left, trends in countries that currently present obesity prevalence less than 25%. On the right, those countries where current prevalence exceeds 25%. The continuous black line (red dots) indicates the average rate trend for 10 countries analyzed. Graphs were built after downloading data from the Global Cancer Observatory , , .

FIGURE 4

Trends in age‐standardized incidence (1993–2012) and mortality (1990–2016) rates for uterine cervix cancer in 20 OECD countries. On the left, trends in countries that currently present obesity prevalence less than 25%. On the right, those countries where current prevalence exceeds 25%. The continuous black line (red dots) indicates the average rate trend for 10 countries analyzed. Graphs were built after downloading data from the Global Cancer Observatory , , .

FIGURE 5

Trends in age‐standardized incidence (1993–2012) and mortality (1990–2016) rates for uterine cancer (endometrial) in 20 OECD countries. On the left, trends in countries that currently present obesity prevalence less than 25%. On the right, those countries where current prevalence exceeds 25%. The continuous black line (red dots) indicates the average rate trend for 10 countries analyzed. Graphs were built after downloading data from Global Cancer Observatory , , .

FIGURE 6

Comparative analysis of the effect of increase in body mass index among women (35– to +85‐year‐olds) in age‐standardized incidence rates for three gynecologic cancers over time (1993–2012) between Norway (country with obesity prevalence less than 25% in 2016) and Australia (country with obesity prevalence over 25% in 2016). The continuous red line and surrounding shadows show the fitted polynomial (quadratic) line and its 95% CI shaded fit, respectively. Graphs were built after downloading data from OurWorldInData.org and the Global Cancer Observatory , , . Correlation analyses were made using JMP16 software (SAS Institute, Cary, NC, USA).

FIGURE 7

Comparative analysis of the effect of increase in body mass index among women (35– to +85‐year‐olds) in age‐standardized mortality rates for three gynecologic cancers over time (1993–2012) between Norway (country with obesity prevalence less than 25% in 2016) and Australia (country with obesity prevalence over 25% in 2016). The continuous red line and surrounding shadows show the fitted polynomial (quadratic) line and its 95% CI shaded fit, respectively. Graphs were built after downloading data from OurWorldInData.org and the Global Cancer Observatory , , . Correlation analysis was made using JMP16 software (SAS Institute, Cary, NC, USA).

FIGURE 8

Effects of obesity and adiposity in the hallmarks of cancer. The three stuck and sketched yellow and brown circles symbolize hypertrophic and dysfunctional adipocytes. Modified from Hannah and Weinberg , © 2011, with permission from Elsevier.