Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to ...revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or "zero-inflated" data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.
The study objective is to examine the impact of obesity on frontline carboplatin dosing in the neoadjuvant and adjuvant settings and to evaluate the association of dosing with survival among ...epithelial ovarian cancer (EOC) patients.
We selected 1527 women diagnosed with EOC from January 1, 2011 to October 20, 2021 from a nationwide electronic health record-derived de-identified database. The dose reduction of frontline carboplatin was defined as a relative dose intensity (RDI) < 0.85. Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association of RDI with survival overall and by histology.
Women with a BMI ≥ 30 kg/m
versus <30 kg/m
were more likely to be underdosed (RDI < 0.85) with frontline carboplatin. Underdosing of carboplatin in the neoadjuvant setting was associated with worse survival among women with serous tumours (HR = 1.98, 95% CI = 1.15, 3.42). Underdosing of carboplatin in the adjuvant setting was not associated with survival.
In the real-world setting, underdosing of carboplatin in the neoadjuvant setting was associated with inferior survival among women with serous tumours. With the increasing utilisation of neoadjuvant chemotherapy in EOC, actual weight-based dosing of carboplatin may be important to improve outcomes in this patient population.
Ovarian cancer is the fifth leading cause of cancer-associated mortality among US women with survival disparities seen across race, ethnicity, and socioeconomic status, even after accounting for ...histology, stage, treatment, and other clinical factors. Neighborhood context can play an important role in ovarian cancer survival, and, to the extent to which minority racial and ethnic groups and populations of lower socioeconomic status are more likely to be segregated into neighborhoods with lower quality social, built, and physical environment, these contextual factors may be a critical component of ovarian cancer survival disparities. Understanding factors associated with ovarian cancer outcome disparities will allow clinicians to identify patients at risk for worse outcomes and point to measures, such as social support programs or transportation aid, that can help to ameliorate such disparities. However, research on the impact of neighborhood contextual factors in ovarian cancer survival and in disparities in ovarian cancer survival is limited. This commentary focuses on the following neighborhood contextual domains: structural and institutional context, social context, physical context represented by environmental exposures, built environment, rurality, and healthcare access. The research conducted to date is presented and clinical implications and recommendations for future interventions and studies to address disparities in ovarian cancer outcomes are proposed.
Black women diagnosed with epithelial ovarian cancer have poorer survival compared to white women. Factors that contribute to this disparity, aside from socioeconomic status and guideline‐adherent ...treatment, have not yet been clearly identified. We examined data from the Ovarian Cancer in Women of African Ancestry (OCWAA) consortium which harmonized data on 1074 Black women and 3263 white women with ovarian cancer from seven US studies. We selected potential mediators and confounders by examining associations between each variable with race and survival. We then conducted a sequential mediation analysis using an imputation method to estimate total, direct, and indirect effects of race on ovarian cancer survival. Black women had worse survival than white women (HR = 1.30; 95% CI 1.16‐1.47) during study follow‐up; 67.9% of Black women and 69.8% of white women died. In our final model, mediators of this disparity include college education, nulliparity, smoking status, body mass index, diabetes, diabetes/race interaction, postmenopausal hormone (PMH) therapy duration, PMH duration/race interaction, PMH duration/age interaction, histotype, and stage. These mediators explained 48.8% (SE = 12.1%) of the overall disparity; histotype/stage and PMH duration accounted for the largest fraction. In summary, nearly half of the disparity in ovarian cancer survival between Black and white women in the OCWAA consortium is explained by education, lifestyle factors, diabetes, PMH use, and tumor characteristics. Our findings suggest that several potentially modifiable factors play a role. Further research to uncover additional mediators, incorporate data on social determinants of health, and identify potential avenues of intervention to reduce this disparity is urgently needed.
What's new?
Disparities in ovarian cancer survival between Black women and white women are accounted for in part by differences in socioeconomic status and adherence to treatment guidelines. The extent to which other factors, such as lifestyle, hormone therapy, and diabetes, influence these survival disparities remains unclear. In our study, using a novel statistical approach, the authors show that almost half of the disparity in ovarian cancer survival between Black women and white women is associated with lifestyle, education, diabetes, postmenopausal hormone use, and tumor characteristics. Further characterization of these mediating factors is essential to reducing racial disparities in ovarian cancer survival.
The association of body composition with epithelial ovarian carcinoma (EOC) mortality is poorly understood. To date, evidence suggests high adiposity associates with decreased mortality (an obesity ...paradox), but the impact of muscle on this association has not been investigated. Herein, we define associations of muscle and adiposity joint-exposure body composition phenotypes with EOC mortality.
Body composition from 500 women in The Body Composition and Epithelial Ovarian Cancer Survival Study was dichotomized as normal/low skeletal muscle index (SMI), a proxy for sarcopenia and high/low adiposity. Four phenotypes were classified as fit/reference (normal SMI/low adiposity; 16.2%), overweight/obese (normal SMI/high adiposity; 51.2%), sarcopenia/overweight-obese (low SMI/high adiposity; 15.6%), and sarcopenia/cachexia (low SMI/low adiposity; 17%). We used multivariable Cox models to estimate associations of each phenotype with mortality for EOC overall and high-grade serous ovarian carcinoma (HGSOC).
Overweight/obesity was associated with up to 51% and 104% increased mortality in EOC and HGSOC (HR = 1.51, 95% CI: 1.05-2.19 and HR = 2.04, 95% CI: 1.29-3.21). Sarcopenia/overweight-obesity was associated with up to 66% and 67% increased mortality in EOC and HGSOC (HR = 1.66, 95% CI: 1.13-2.45 and HR = 1.67, 95% CI: 1.05-2.68). Sarcopenia/cachexia was associated with up to 73% and 109% increased mortality in EOC and HGSOC (HR = 1.73, 95% CI: 1.14-2.63 and HR = 2.09, 95% CI: 1.25-3.50).
Overweight/obesity, sarcopenia/overweight-obesity and sarcopenia/cachexia phenotypes were each associated with increased mortality in EOC and HGSOC. Exercise and dietary interventions could be leveraged as ancillary treatment strategies for improving outcomes in the most fatal gynecological malignancy with no previously established modifiable prognostic factors.
Prevention of Epithelial Ovarian Cancer Sellers, Thomas A; Peres, Lauren C; Hathaway, Cassandra A ...
Cold Spring Harbor perspectives in medicine,
08/2023, Letnik:
13, Številka:
8
Journal Article
Recenzirano
Given the challenges with achieving effective and durable treatment for epithelial ovarian cancer, primary prevention is highly desirable. Fortunately, decades of research have provided evidence for ...several strategies that can be deployed to optimize risk reduction. These include surgery, chemoprevention, and lifestyle factor modifications. These broad categories vary in terms of the magnitude of risk reduction possible, the possible short-term and long-term side effects, the degree of difficulty, and acceptability. Thus, the concept of a risk-based model to personalize preventive interventions is advocated to guide discussion between care providers and women at risk. For women with inherited major gene mutations that greatly increase risk of ovarian cancer, surgical approaches have favorable risk to benefit ratios. Chemoprevention and lifestyle factor modifications portend a lower degree of risk reduction but confer lower risk of undesirable side effects. Since complete prevention is not currently possible, better methods for early detection remain a high priority.
Abstract
Summary
Multiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the ...tumor immune microenvironment (TIME). Generally, mIF data is used to examine the abundance of immune cells in the TIME; however, this does not capture spatial patterns of immune cells throughout the TIME, a metric increasingly recognized as important for prognosis. To address this gap, we developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME. The spatialTIME package calculates univariate and bivariate spatial statistics (e.g. Ripley’s K, Besag’s L, Macron’s M and G or nearest neighbor distance) and creates publication quality plots for spatial organization of the cells in each tissue sample. The iTIME web application allows users to statistically compare the abundance measures with patient clinical features along with visualization of the TIME for one tissue sample at a time.
Availability and implementation
spatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME).
Supplementary information
Supplementary data are available at Bioinformatics online.
Although ovarian cancer is a deadly disease, approximately a third of women survive ≥9 years after diagnosis. The factors associated with achieving long-term survival are not well understood. In this ...study, data from the Surveillance, Epidemiology, and End Results (SEER) program were used to determine predictors of survival trajectories among women with epithelial ovarian cancer and across histotype (high-grade serous carcinoma (HGSC) and non-HGSC).
Data on 35,868 women diagnosed with epithelial ovarian cancer in 2004–2016 were extracted from SEER. Extended Cox proportional hazards regression was used to estimate overall and histotype-specific associations between patient and tumor characteristics and all-cause mortality within each survival time (t) interval (t < 3, 3 ≤ t < 6, 6 ≤ t < 9, and 9 ≤ t < 13 years).
Age at diagnosis, marital status, race/ethnicity, stage, and surgery were more strongly associated with mortality in the short-term survival period, and these associations waned with increasing survival time. Exceptions to this pattern were age >70 years at diagnosis, where a high risk of mortality was observed in both the t < 3 and t ≥ 9 year time periods, and non-Hispanic Asian/Pacific Islanders, where a more pronounced inverse association with mortality was observed in t ≥ 9 years after diagnosis. Similar associations were observed for HGSC, although the waning effect was not apparent for most characteristics. Mortality associations for non-HGSC were more pronounced for stage and race/ethnicity, primarily for non-Hispanic Asian/Pacific Islanders.
Most patient and tumor characteristics were more strongly associated with mortality in the years following diagnosis, but have declining impact with increasing survival time. Given this waning effect, it is critical to identify factors impacting risk of mortality as ovarian cancer patients advance through the survival trajectory.
•Though an important predictor of survival overall, stage had a declining impact on mortality with increasing survival time.•Increased risk of mortality for non-Hispanic black women was restricted to the first six years after diagnosis.•Only stage, non-Hispanic Asian/Pacific Islander race, and an age of >70 years were associated with long-term survival.
Obesity disproportionately affects African American (AA) women and has been shown to increase ovarian cancer risk, with some suggestions that the association may differ by race.
We evaluated body ...mass index (BMI) and invasive epithelial ovarian cancer (EOC) risk in a pooled study of case-control and nested case-control studies including AA and White women. We evaluated both young adult and recent BMI (within the last 5 years). Associations were estimated using multi-level and multinomial logistic regression models.
The sample included 1078 AA cases, 2582 AA controls, 3240 White cases and 9851 White controls. We observed a higher risk for the non-high-grade serous (NHGS) histotypes for AA women with obesity (OR
= 1.62, 95% CI: 1.16, 2.26) and White women with obesity (OR
= 1.20, 95% CI: 1.02, 2.42) compared to non-obese. Obesity was associated with higher NHGS risk in White women who never used HT (OR
= 1.40, 95% CI: 1.08, 1.82). Higher NHGS ovarian cancer risk was observed for AA women who ever used HT (OR
= 2.66, 95% CI: 1.15, 6.13), while in White women, there was an inverse association between recent BMI and risk of EOC and HGS in ever-HT users (EOC OR
= 0.81, 95% CI: 0.69, 0.95, HGS OR
= 0.73, 95% CI: 0.61, 0.88).
Obesity contributes to NHGS EOC risk in AA and White women, but risk across racial groups studied differs by HT use and histotype.
PDF
