Biobehavioral Pathways in Epithelial Ovarian Cancer

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1 Biobehavioral Pathways in Epithelial Ovarian Cancer Susan K. Lutgendorf, Ph.D. Departments of Psychology, Obstetrics and Gynecology, and Urology and Holden Comprehensive Cancer Center University of Iowa Institute of Medicine April 7, 2015

2 Epidemiological Perspectives: Stress and Cancer Initiation Evidence linking stress and cancer initiation not strong; findings inconsistent Meta-analyses find generally small effect sizes Severe life events and chronic distress show more consistent links Twofold increase in breast cancer risk after separation, divorce, or death of spouse (n > 10,000) Childhood physical abuse associated with 47% higher odds of being diagnosed with cancer Persistent depression 88% increase in cancer risk

3 Epidemiological Evidence: Stress Factors and Cancer Progression Depression predicts faster progression in liver, lung, and renal cell cancers Depression and stress-related factors predict shorter overall survival across all cancers: (Meta-analysis: Chida et al, 2008) Trauma history related to faster progression of metastatic breast cancer Social support related to slower progression/longer survival

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5 How Are Behavioral Risk Factors Biologically Transduced To Affect Disease Factors? Green McDonald, O Connell & Lutgendorf (2013)

6 How Are Behavioral Risk Factors Biologically Transduced To Affect Disease Factors? Green McDonald, O Connell & Lutgendorf (2013)

7 How Are Behavioral Risk Factors Biologically Transduced To Affect Disease Factors? Green McDonald, O Connell & Lutgendorf (2013)

8 Biobehavioral Assessment Validated, Quantitative Assessments: Stress Social Support Depression Well Being/Resilience Sleep Coping

9 Distress and Sleep Disturbances in Ovarian Cancer Patients Depression seen in up to 45% of patients at the time of surgery; 21% still depressed at one year post surgery Sleep disturbances high at the time of diagnosis (70%) and tend to persist to one year (64.8%) don t improve with sleep medications Depression, distress, sleep disturbances and social isolation linked to poorer quality of life.

10 Tumor VEGF (log 10) Peripheral IL-6 (log 10) pg/ml Ascites IL-6 (log 10) pg/ml Biobehavioral Effects on Cancer Biology: What do we know? Social support in Ovarian Cancer Patients Greater natural killer cell activity in peripheral blood and TIL Lower levels of NE in tumor and ascites but not in plasma Lower levels of VEGF in peripheral blood and in tumor Lower levels of IL-6 in peripheral blood and in ascites 2.00 Stage Fit line for Total Peripheral IL-6 Ascites IL-6 Tumor VEGF (log 10) Total social support Social Support R Sq Linear = Low Social Social Support High Low Social Social Support High

11 Biobehavioral Effects on Cancer Biology: What do we know? Distress/Depression in Ovarian Cancer Patients Associated with poorer NK cell activity in TIL Greater Th2/Th1 T cell ratio in blood, ascites, and tumor Higher levels of tumor associated macrophages expressing MMP9 (invasion) Higher levels of IL-6 in peripheral blood and ascites

12 10 patients matched on stage, age, grade, histology More than 200 genes over-expressed (> 2-fold) in low ss high depression patients: Growth-regulating transcription factors Extracellular matrix Proteases Chemokines, receptors, and adhesion molecules High Depression & Low Social Support Low Depression & High Social Support 220 up-regulated 46 down-regulated

13 Non-Depressed Depressed Non-Depressed Depressed Non-Depressed Depressed Non-Depressed Depressed promoter sites / gene promoter sites / gene promoter sites / gene promoter sites / gene Signaling Pathways CREB NF-kB STAT3 ELK1.10 p = p = p = p = Significance: NE / bar signaling Inflammation Metastatic capacity MAPK activity: proliferation Lutgendorf, Cole, Brain, Behavior, and Immunity, 2009

14 Low Risk High Risk Low Risk High Risk Norepinephrine (pg / mg) Norepinephrine (pg / ml) Plasma and Tumor Norepinephrine in High and Low Risk Patients Tumor NE p =.0482 Plasma NE p = Lutgendorf, Cole, Brain Behavior and Immunity, 2009

15 Beta-Adrenergic Signaling Increases Ovarian Tumor Progression (Pre-Clinical Findings) Increases tumor weight and number of nodules Stimulates angiogenesis Stimulates invasion Enhances tumor cell migration Protects tumor cells from anoikis Increases macrophage/monocyte recruitment into the tumor microenvironment Stimulates Epithelial Mesenchymal Transition Effects blocked by beta-blockers

16 SKOV3 HeyA8 SKOV3-ip

17 Cole and Sood, CCR, 2012 Beta-adrenergic Signaling Pathways In Cancer

18 How Are Behavioral Risk Factors Biologically Transduced To Affect Disease Factors? Green McDonald, O Connell & Lutgendorf (2013)

19 Effects of Glucocorticoids on Tumor cells Glucocorticoids Stimulate growth of prostate and breast cancer cells Enhance survival of mammary and other cancer Inhibit tumor cell apoptosis Inhibit the destruction of tumor cells by chemotherapy Alter transcriptional activity of cells such as tumor-associated fibroblasts and adipocytes to support tumor growth and progression Downregulate DNA repair

20 Abnormal Diurnal Cortisol Rhythms in Ovarian Cancer Patients Weinrib et al., Cancer, 2010

21 Diurnal Cortisol Rhythms and Survival in Epithelial Ovarian Cancer Nocturnal Cortisol Cortisol Slope Schrepf et al Psychoneuroendocrinology 2015.

22 Inflammatory Cytokine-Induced Vegetative Symptoms Fatigue Depression Loss of appetite Lowered pain thresholds Difficulty concentrating Sleep Disorders Adapted from Dunn, 1994

23 Elevated nocturnal cortisol in ovarian patients associated with greater fatigue poorer performance status poorer physical well being greater total depression greater vegetative depression Elevated IL-6 associated with Greater fatigue Poorer sleep Greater disability vegetative depression Changes in IL-6 and nocturnal cortisol associated with normalization of these symptoms.

24 Figure 1 Baseline Month 6 Month 12 Control CBSM Control CBSM Control CBSM 273 upregulated 336 downregulated

25 Psychosocial Intervention: Survival Effects in Breast Cancer Patients Survival Following recurrence HR = 0.55; P=0.034 HR = 0.44, P=0.016 HR = 0.41, P=0.014 Stage IIA IIIB breast carcinoma patients (N=227) Group intervention of 26 sessions over 12 months 11 years median follow-up (range, 7-13 years) Andersen et al. Cancer, 2008 Andersen et al CCR, 2010

26 What do we need to know? Deeper understanding of effects of biobehavioral macroenvironment on signaling in tumor and the microenvironment Are there thresholds/ cumulative levels that trigger effects Effects mediated by adipose tissue/adipokines Interactions between biobehavioral, metabolic, microbiome, and tumor factors Effects of biobehavioral factors on chemoresistance, immunotherapy, neuropathy Interaction of behavioral and lifestyle factors to influence disease outcomes Role of neoinnervation on tumor processes Precision assessment of behavioral factors- eg. Sensors, smart phone applications

27 What do we need to know: Interventions Positive factors- what can we learn from Long Term Survivors? Role of Meaning, Resilience, Spirituality Are behavioral interventions that reduce stress and improve social support effective in altering biological variables and in prolonging survival? Treatment of cytokine-induced vegetative symptoms Effects of pharmacologic interventions (e.g. beta blockers; antiinflammatory agents) Who can benefit most? When is the best time to intervene?

28 What Needs To Be Done? Priorities Assessment of patients for biobehavioral risk factors Assessment of biobehavioral factors in drug trials, particularly as related to chemoresistance, immunotherapy Multimodal interventions for distress, sleep, social isolation, stress management- behavioral, diet, exercise Pharmacologic interventions (e.g. beta-blockers) Advocacy Dissemination- e.g. internet, phone interventions

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31 Acknowledgements National Cancer Institute, Biobehavioral Branch: R21 CA88293 R01-CA and supplements R01-CA140933