Cancer is a systemic disease. In order to fully understand it, we must take a holistic view on how cancer interacts with its host. The brain monitors and responds to natural and aberrant signals arriving from the periphery, particularly those of metabolic or immune origin. As has been well described, a hallmark of cancer is marked disruption of metabolic and inflammatory processes. Depending on the salience and timing of these inputs, the brain responds via neural and humoral routes to alter whole-body physiology. These responses have consequences for tumor growth and metastasis, directly influencing patient quality of life and subsequent mortality. Additionally, environmental inputs such as light, diet, and stress, can promote inappropriate neural activity that benefits cancer. Here, I discuss evidence for brain-tumor interactions, with special emphasis on subcortical neuromodulator neural populations, and potential ways of harnessing this cross-talk as a novel approach for cancer treatment.
Uncovering the relationships among cancer and the physiology of its host has cemented the notion that cancer is a systemic disease. Cancer patients frequently experience systemic symptoms like depression, sleep disruption, cognitive impairment, appetite and metabolic dysfunction, and weight loss. These phenomena span different cancer types and occur independently from treatment regimens. Clinical studies consistently report that such symptoms (such as weight loss, sleep disruption, and circadian misalignment) are predictors of poor prognoses and reduced quality of life[
Reciprocally, the host system can influence tumor growth and metastasis via immune, endocrine, and neural pathways. For example, chronic stress, which results in dysregulation of glucocorticoid and adrenergic signaling, exacerbates tumor growth and angiogenesis[
A simplified schematic of reciprocal tumor-host interactions. Tumors promote aberrant physiology via alterations to the immune system and secretion of metabolic “waste” which contributes to further inflammation and altered function of distal organs, including the brain. Feedback from the brain (neural or humoral) can subsequently exacerbate tumor-associated immune and metabolic changes, ultimately facilitating tumor growth, angiogenesis, metastasis, or cancer-associated co-morbidities
Disruption of sleep and/or circadian rhythms in physiology and behavior are frequently observed in cancer patients. Indeed, 35%-80% of cancer patients report poor sleep quality[
Non-exhaustive list of clinical observations of systemic co-morbidities potentially influencing brain function (sleep disturbance, circadian rhythm disruption, cognitive impairment, metabolic abnormalities, microbial dysbiosis, and systemic inflammation) in patients with cancer
Systemic problem | Patient population | Methods | Primary observation | Ref. |
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Sleep disturbance | 823 patients with cancer receiving chemotherapy | Post-hoc analysis of data from a large randomized clinical trial; Hamilton Depression Inventory used to assess sleep disturbance | 36.6% ( |
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85 women with Stages I-IIIA breast cancer | actigraphy for 72 consecutive hours and filled out questionnaires (PSQI, MFSI-SF, FOSQ, FACT-B, and CES-D) on sleep, fatigue, depression, and functional outcome | women slept for ~6 h a night and napped > 1 h during the day. Sleep was disturbed and fatigue levels were high; phase-delayed circadian rhythms | [ |
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97 women with advanced breast cancer (age = 54.6 ± 9.8 years) | 72 h actigraphy; sleep efficiency was determined as the ratio of total sleep time to total sleep time plus wake after sleep onset | Sleep efficiency predicted reduction in overall mortality [hazard ratio (HR), 0.96; 95% confidence interval (CI), 0.94-0.98; |
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40 patients (50 years, SD = 11; 53% White, 28% Asian, 19% Other) with primary breast cancer (18% Stage I, 50% Stage II, 33% Stage III) undergoing chemotherapy | Neurocognitive battery of tests including PSQI, ISI, BFI, CAD, COWAT, HVLT; actigraphy for 7 consecutive days to track arousal/sleep | Better circadian function was associated with less sleep disruption (PSQI, |
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Circadian rhythm disruption | 389 Caucasian cases and 432 Caucasian controls | Investigated the association between an exonic length variation in a circadian gene, Period3 (Per3), and breast cancer risk using blood samples collected from a recently completed breast cancer case-control study in Connecticut | [ |
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57 presurgical breast cancer patients | Daily self-reports of cancer-specific distress and avoidant coping as well as actigraphic and salivary cortisol data | Distress and avoidant coping were related to rest/activity rhythm disruption (daytime sedentariness, inconsistent rhythms). Patients with disrupted rest/activity cycles had flattened diurnal cortisol rhythms | [ |
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104 patients with metastatic breast cancer | Salivary cortisol levels assessed at study entry at 800, 1200, 1700, and 2100 hours on each of 3 consecutive days; NK cells measured using flow cytometry, activity by chromium release assay | Cortisol slope predicted survival up to 7 years later. Earlier mortality occurred among patients with relatively “flat” rhythms, indicating a lack of normal diurnal variation (Cox proportional hazards, |
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43 breast cancer patients | Actigraphy, cancer-specific distress (IES, POMS), saliva samples for assessment of diurnal cortisol rhythm, cortisol awakening response (CAR), and diurnal mean. Ten potential markers of tumor progression were quantified in serum and grouped by exploratory factor analysis | Poor circadian coordination as measured by rest-activity rhythms had higher factor 1 (MMP9, TGF-beta, VEGF) scores ( |
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Cognitive Impairment | 321 patients admitted to the Edmonton General Palliative Care Unit over a period of 26 months | Mini-Mental State Examination (MMSE) was used as screening tool to assess cognitive functioning and was performed on all patients at the time of admission and once to twice weekly thereafter | 142 pts (44%) had abnormal MMSE scores (MMSE < 0.8) on admission, whereas 176 patients (55%) had abnormal MMSE scores at the time of death or discharge; 157 (68%) had abnormal MMSE scores prior to death; Of 124 patients with normal final MMSE scores, 64 (52%) were discharged versus 16 of 116 patients (14%) who had abnormal MMSE final scores ( |
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Meta-analysis of 23 studies on cognitive impairment in cancer patients | Articles published 1980-2012, comparing subjective and objective cognition in cancer patients treated with chemotherapy. Of 818 potentially relevant articles, 23 studies met the inclusion criteria for the current review and one article was sourced from reference lists of included studies | 8/24 included studies found a significant relationship between objective and subjective measures of cognitive performance. These studies were more likely to involve breast cancer patients and to assess the relationship between memory and perceived cognitive impairment | [ |
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22 breast cancer survivors who reported cognitive impairment and who were at least 1 year post-chemotherapy treatment | Qualitative interviews, recorded, transcribed verbatim, and analyzed using a content analysis approach | 6 major domains identified: short-term memory, long-term memory, speed of processing, attention and concentration, language and executive functioning; All survivors found these impairments frustrating, and some also reported these changes as detrimental to their self-confidence and social relationships | [ |
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85 women with early stage breast cancer scheduled for chemotherapy, 43 women scheduled for endocrine therapy and/or radiotherapy and 49 healthy control subjects | 3-year prospective study; neuropsychological performance assessed at baseline (T1), post-chemotherapy (or 6 months) (T2) and at 18 months (T3) | No significant interactions or main effect of group after controlling for age and intelligence; reliable decline on multiple tasks was seen in 20% of chemotherapy patients, 26% of nonchemotherapy patients and 18% of controls at T2 (18%, 14 and 11%, respectively, at T3). Those who experienced treatment-induced menopause were more likely to show decline on multiple measures at T2 (OR = 2.6, 95%CI 0.823-8.266 |
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Metabolic Abnormalities | 265 patients with advanced breast cancer receiving palliative chemotherapy | Retrospective study; mortality was compared for diabetic and nondiabetic patients as well as for patients that presented hyperglycemia during treatment | Overall survival was greater in diabetic patients with proper metabolic control than diabetic patients with hyperglycemia. The risk of death was higher in patients with mean glucose levels > 130 mg/dL during treatment | [ |
Meta-analysis of 20 studies (5 case-control and 15 cohort studies) that reported relative risk (RR) estimates (odds ratio, rate ratio/hazard ratio, or standardized incidence ratio) with 95%CI for the relation between diabetes (largely Type II diabetes) and breast cancer incidence | RRs were calculated using a random-effects model | All 20 studies showed that women with ( |
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Pooled individual-level data from 758,592 premenopausal women from 19 prospective cohorts | Hazard ratios (HRs) of premenopausal breast cancer in association with BMI from ages 18 through 54 years using Cox proportional hazards regression analysis. Median follow-up; 9.3 years (interquartile range, 4.9-13.5 years) per participant, with 13,082 incident cases of breast cancer | Inverse linear associations of BMI with breast cancer risk were found that were stronger for BMI at ages 18 to 24 years (HR per 5 kg/m2 [5.0-U] difference, 0.77; 95%CI, 0.73-0.80) than for BMI at ages 45 to 54 years (HR per 5.0-U difference, 0.88; 95%CI, 0.86-0.91). 4.2-fold risk gradient between the highest and lowest BMI categories (BMI ≥ 35.0 |
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10,786 women ages 35-69 were recruited in a prospective study in Italy; Four matched controls were chosen for each breast cancer case ( |
Blood samples were collected after a 12-h fast between 7:30 and 9:00 a.m. | Adjusted relative risk (RR) for the highest quartile of serum glucose |
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Microbial Dysbiosis | Breast tumor tissue and paired normal adjacent tissue from the same patient | Qualitative survey of breast microbiota DNA | Bacterium |
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48 postmenopausal breast cancer case patients, pretreatment, |
Microbiota profiles in fecal DNA were determined by Illumina sequencing and taxonomy of 16S rRNA genes. Estrogens were quantified in urine; linear and unconditional logistic regression of microbiota α-diversity (PD_whole tree) and UniFrac analysis of β-diversity | Estrogens correlated with α-diversity in control patients (Spearman Rho = 0.37, |
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31 patients with early-stage breast cancer | Bacterial DNA was extracted from the feces; qPCR amplified, targeting 16S rRNA sequences specific to bacterial groups, and then analyzed in relation to clinical characteristics | Absolute numbers of total bacteria and three bacterial groups ( |
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Eighteen patients with breast cancer (BC), 18 with uterine leiomyoma (UL), and 30 healthy women | Feces were collected on 1st admission and processed immediately; qualitative and quantitative analysis of fecal flora | Premenopausal BC patients showed increased Enterobacteriaceae ( |
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Systemic Inflammation | Data from the Health, Eating, Activity, and Lifestyle (HEAL) Study (a multiethnic prospective cohort study of women diagnosed with stage 0 to IIIA breast cancer) (734 total survivors) | Concentrations of CRP and SAA were measured approximately 31 months after diagnosis and tested for associations with disease-free survival (approximately 4.1 years of follow-up) and overall survival (approximately 6.9 years of follow-up) | Elevated SAA and CRP were associated with reduced overall survival, regardless of adjustment for age, tumor stage, race, and body mass index (SAA |
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96 patients with metastatic breast cancer. During follow-up 51 patients died of their cancer | Evaluated the value of an inflammation-based score (Glasgow Prognostic Score, GPS) in patients with metastatic breast cancer (scored on 0-2 scale) | Multivariate analysis of the GPS and treatment received, only the GPS (HR 2.26, 95%CI 1.45-3.52, |
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Colorectal ( |
Median survival, univariate/multivariate analyses of correlations between inflammatory markers and survival | Association between duration of survival and both log10 C-reactive protein and albumin concentrations ( |
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Cross-sectional and retrospective studies. CS included 100 women undergoing mastectomy for breast cancer risk reduction ( |
Metabolic syndrome-associated circulating factors were compared by CLS-B status. The association between CLS of the breast and the metabolic syndrome was validated; Distant recurrence-free survival (dRFS) was compared by CLS-B status | Pts with WAT inflammation had elevated insulin, glucose, leptin, triglycerides, C-reactive protein, and IL6 and lower high-density lipoprotein cholesterol and adiponectin ( |
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The hypothalamus is a critical structure for maintaining homeostasis[
HO neurons project throughout the brain to participate in functions ranging from arousal and motivation, to anxiety and reproductive behavior[
Leptin, an adipokine hormone that correlates with satiety and body fat accumulation, generally inhibits HO neurons through direct and indirect pathways[
Indeed, brain-tumor-metabolic interactions were recently tested in a mouse model of non-metastatic breast cancer[
Highlighted pathways linking the brain and periphery in the context of cancer. Environmental (e.g., light, stress) or endogenous signals reach the brain to alter the activity of neurons involved in sleep (LHA hypocretin/orexin), circadian rhythms (SCN-GABA), reward (VTA-Dopamine), metabolism, and energy balance (Parabrachial CGRP). Aberrant activity of these cells promotes signaling in the periphery that ultimately facilitates tumor growth, angiogenesis, and invasiveness. Systems highlighted are bolded in
Non-exhaustive list of primary animal model evidence for brain-tumor interactions regulating cancer incidence, disease progression, morbidity and mortality (see
Cancer type/model | Main focus | Primary findings | Ref. |
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67NR/4T1/4T07 syngeneic breast cancer cells (female BalbC mice; subQ/orthotopic) | Effects of peripheral tumors on central regulation of sleep and metabolism | Tumors alter leptin/ghrelin signaling, disrupting central hypocretin/orexin activity to influence glucose metabolism and sleep via the sympathetic nervous system | [ |
LL2 Lewis Lung carcinoma/B6 (male C57bl6j mice; subQ) | Dopaminergic regulation of tumor growth | Activation of VTA-dopamine neurons blunts tumor growth via sympathetic modulation of bone-marrow myeloid derived suppressor cells | [ |
p53R270H©/+WAP-Cre mutant model of Li-Fraumeni syndrome (mouse; transgenic) | Circadian disruption-induced cancer development | Chronic phase shifting accelerated spontaneous tumor growth and altered tumor phenotype | [ |
Effects of tumors on affective behaviors | Tumor growth is associated with central cytokine concentrations, altered glucocorticoid responses, and the development of depressive-like behavior | [ |
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Colon-26 adenocarcinoma cells (mouse; SubQ) | Effects of tumors on fatigue, muscle physiology, and affective behaviors | Tumors promoted central proinflammatory cytokine production and depressive-like behavior prior to defects in muscle function, behavior rescued by SSRI | [ |
HeyA8, SKOV3ip1, MB-231 orthotopic human ovarian carcinoma cells (nude mice; IP) | Effects of stress on tumor development and angiogenesis | Stress-induced adrenergic signaling (cAMP->PKA) promotes tumor growth and angiogenesis | [ |
Non-metastatic methylcholanthrene-induced sarcoma (F344/NTacfBR male rats; SubQ) | Effects of inflammation on central hypocretin/orexin neurons and fatigue | Tumors reduced hypocretin/orexin transcript expression and promoted fatigue | [ |
LL2 or TC-1 lung epithelial cells (male C57Bl6 mice; subQ) | Role of sleep fragmentation (SF) on tumor growth and progression | SF accelerates tumor growth, likely through a TLR4 dependent mechanism | [ |
LL2 Lewis Lung carcinoma cells/Apc/min+ mice (male and female C57Bl6; subQ/transgenic) | Role of calcitonin-gene related peptide (CGRP) neurons in cancer-associated cachexia | Inactivation of parabrachial CGRP neurons prevents and reverses cancer-induced anorexia, fatigue, and changes in affective behavior | [ |
MADB106 breast cancer cells (outbred “hyperreactive” Wistar rats; subQ) | Role of dopaminergic system in tumor growth/metastasis | Smaller tumors, fewer metastases, and reduced angiogenesis in rats with a hyperreactive dopaminergic system | [ |
K-rasLSL-G12D/+;p53flox/flox (KP) or K-rasLSL-G12D/+ (K) lung cancer model 129SvJ x C57bl6 mice (cre-dependent p53 deletion) | Effects of circadian disruption (environmental and genetic) on lung tumor growth and progression | Both genetic and physiologic circadian disruption accelerate tumor growth and promote c-myc upregulation and metabolic reprogramming | [ |
diethylnitrosamine-induced hepatocarcinogenesis (male Sprague-Dawley rats) | Sympathetic nervous system effect on hepatocarcinogenesis | High density of SNS bundles associated with poor prognosis, SNS activation of Kupffer cells drives inflammation | [ |
Hepatocarcinoma Morris 7288CTC cells (male buffalo rats) or steroid receptor (SR)-1+ or SR-1- MCF-7 human breast cancer xenografts (female nude rats) | Role of light and melatonin in cancer progression | Melatonin depleted blood accelerates tumor growth and metabolism compared to melatonin-rich blood from healthy women; light accelerates tumor growth in dose-dependent manner | [ |
B16 melanoma cells (male nude mice/C57bl6 D2 receptor-KO) | Role of peripheral dopaminergic signaling in tumor growth/angiogenesis/metastasis | 6-OHDA ablation of dopaminergic nerves enhanced tumor angiogenesis and growth, likely through D2-mediated mechanism | [ |
GOS Glasgow osteosarcoma and pancreatic adenocarcinoma (P03) xenographs (male B6D2F1 mice; subQ into flank) | Effect of suprachiasmatic nucleus lesions on tumor growth | SCN lesions drastically increased tumor size in both cancer models examined | [ |
TC-1 mouse lung cancer cells and human lung adenocarcinoma cells (male C57bl6 mice and obstructive sleep apnea patients) | Effect of sleep fragmentation on plasma exosomes and tumor growth | Chronic sleep fragmentation alters the microRNA cargo of plasma exosomes to promote tumor cell proliferation | [ |
EG, SKOV3ip1, and 222 human ovarian cancer cells (nude male mice) | Effect of stress hormones on cancer invasiveness and growth | Adrenergic and glucocorticoid signaling promotes tumor invasiveness (in part) via upregulation of MMPs | [ |
VTA: ventral tegmental area; cAMP: cyclic adenosine monophosphate; PKA: protein kinase A; 6-OHDA: 6-hydroxydopamine; MMPs: matrix metalloproteinases
In two mouse models of lung cancer (LLC and TC1), Hakim
The paired suprachiasmatic nuclei (SCN) are the primary structures responsible for setting circadian rhythms in physiology and behavior that we observe across most of the phylogenetic tree[
This process takes approximately 24 h to complete, where light-induced gene transcription has a phase-modulatory effect on the clock. This feedback loop operates in a cell-autonomous manner throughout the body, with peripheral clocks “set” via neural and humoral routes originating from the SCN[
Chronic circadian disruption (e.g., via aberrant light exposure, genetic manipulations, or phase shifting) is repeatedly associated with spontaneous cancer occurrence in humans and multiple rodent models spanning a variety of cancer types[
In a similar study, Papagiannakopoulos and colleagues investigated the effects of environmental and genetic circadian disruption on lung tumorigenesis[
In a reciprocal set of experiments to those discussed above, Masri & colleagues investigated how tumors themselves disrupt host circadian rhythms, independent of the outside environment[
Melatonin is an indoleamine hormone produced and secreted into circulation primarily by the pineal gland in mammals, where it acts as an endogenous signal of darkness[
Melatonin is a pleiotropic immunomodulatory molecule. Broadly, melatonin is immune-enhancing, acting as a mild anti-inflammatory agent, buffering the immune system against glucocorticoids and reactive oxidative and nitrosative stress[
In a clever experimental design, Blask & colleagues investigated the role of melatonin on human breast cancer xenograft tumor progression in nude rats[
The midbrain ventral tegmental area (VTA) and neighboring substantia nigra are the primary source of all dopamine (DA) within the brain. Known for its important role in reward and motivational processing (i.e., calculating reward-prediction errors), the VTA has recently become a target for modulating cancer. Elevated concentrations of dopamine are associated with blunted tumor growth, reduced angiogenesis, and lower metastatic capacity of cancer in rats[
After these initial studies, they applied their findings to a mouse model of lung cancer[
Glucocorticoids (primarily cortisol in humans and corticosterone in mice) are powerfully regulated by circadian rhythms, stress, metabolic state, and immune status[
Thaker, Sood & colleagues provided empirical evidence that psychological stress can facilitate tumor growth in multiple animal models via its promotion of glucocorticoid and adrenergic signaling[
Disrupted energy balance resulting in enhanced capacity to sustain proliferative growth is a hallmark of cancer[
Anorexia is a common phenomenon in cancer patients with weight loss, and even when patients attempt to eat enough to compensate, they frequently cannot maintain a healthy weight. Although significant evidence suggests that inflammatory signaling secondary to tumor growth or cancer-treatment associates with anorexia, a specific neural population and mechanism governing this common problem is lacking[
In a mouse model of Lewis lung carcinoma, Schwartz and colleagues investigated how peripheral tumors modulate CGRP neural activity and their role in cancer-associated anorexia/cachexia[
Another research area that is rapidly growing in scope is that of brain-gut and gut-cancer interactions. Changes in systemic microbial diversity can influence brain function, alter immune phenotypes, and dictate subsequent cancer development or a tumor’s response to immunotherapy[
Together, the studies discussed above aim to provide an understanding of the types of inputs the brain receives, the signals it propagates, and the effects of these messages on tumor growth and metastasis. Reciprocally, tumor-induced changes in physiology are relayed to the brain via endocrine, immune, or neural signals that ultimately change the activity of discrete neural populations important for maintaining homeostasis. Resolving the “conflict of interest” between cancer and the brain will undoubtedly lead to improvements in patient quality of life and unlock a novel means for cancer treatment. A summary of these findings from basic science are presented in
In this vein, treatments targeting the circadian system (i.e., chronotherapy) have gained significant traction in recent years[
Alternatively, targeted stimulation of specific brain areas deregulated in cancer may help overcome resistance to more traditional treatment strategies. As discussed above, stimulation of the dopaminergic ventral tegmental area promotes tumor suppression via the sympathetic nervous system[
As cancer drastically alters energy balance, influencing the activity of specific brain nuclei regulating metabolism and food intake (e.g., hypocretin, AgRP, POMC, CGRP neurons) represents a strategy to not only improve quality of life, but limit energy availability to the cancer. Indeed, inhibition of aberrant hypocretin/orexin signaling promotes sleep and attenuates tumor-induced metabolic abnormalities in a mouse model of breast cancer[
I thank Drs. Luis de Lecea and Natalie Nevárez for providing critical critiques during the preparation of this manuscript. I thank Dr. Peter Dong for making the illustrations featured in this manuscript. This review was made possible thanks to a BRAIN Initiative NIMH F32MH115431. All efforts were made to include relevant research, failure to do so is the sole responsibility of the author.
Borniger JC contributed solely to this study.
Not applicable.
This study was supported by NIMH BRAIN Initiative (F32 MH115431).
The author declared that there are no conflicts of interest.
Not applicable.
Not applicable.
© The Author(s) 2019.