Abstract

Background

   Breast cancer survivors face long-term sequelae compared to the general
   population, suggesting altered metabolic profiles after breast cancer.
   We used metabolomics approaches to investigate the metabolic
   differences between breast cancer patients and women in the general
   population, aiming to elaborate metabolic changes among breast cancer
   patients and identify potential targets for clinical interventions to
   mitigate long-term sequelae.

Methods

   Serum samples were retrieved from 125 breast cancer cases recruited
   from the Chicago Multiethnic Epidemiologic Breast Cancer Cohort
   (ChiMEC), and 125 healthy controls selected from Chicago Multiethnic
   Prevention and Surveillance Study (COMPASS). We used liquid
   chromatography-high resolution mass spectrometry to obtain untargeted
   metabolic profiles and partial least squares discriminant analysis
   (PLS-DA) combined with fold change to select metabolic features
   associated with breast cancer. Pathway analyses were conducted using
   Mummichog to identify differentially enriched metabolic pathways among
   cancer patients. As potential confounders we included age, marital
   status, tobacco smoking, alcohol drinking, type 2 diabetes, and area
   deprivation index in our model. Random effects of residence for
   intercept was also included in the model. We further conducted subgroup
   analysis by treatment timing (chemotherapy/radiotherapy/surgery), lymph
   node status, and cancer stages.

Results

   The entire study participants were African American. The average ages
   were 57.1 for cases and 58.0 for controls. We extracted 15,829 features
   in total, among which 507 features were eventually selected by our
   criteria. Pathway enrichment analysis of these 507 features identified
   three differentially enriched metabolic pathways related to
   prostaglandin, leukotriene, and glycerophospholipid. The three pathways
   demonstrated inconsistent patterns. Metabolic features in the
   prostaglandin and leukotriene pathways exhibited increased abundances
   among cancer patients. In contrast, metabolic intensity in the
   glycerolphospholipid pathway was deregulated among cancer patients.
   Subgroup analysis yielded consistent results. However, changes in these
   pathways were strengthened when only using cases with positive lymph
   nodes, and attenuated when only using cases with stage I disease.

Conclusion

   Breast cancer in African American women is associated with increase in
   serum metabolites involved in prostaglandin and leukotriene pathways,
   but with decrease in serum metabolites in glycerolphospholipid pathway.
   Positive lymph nodes and advanced cancer stage may strengthen changes
   in these pathways.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s12885-023-10656-1.

   Keywords: breast cancer, metabolome, metabolomics, prostaglandin,
   leukotriene, glycerophospholipid

Introduction

   Breast cancer survivorship has been improved since 1990s due to
   advances in early detection and cancer therapy [[41]1]. Over 90% of all
   female breast cancer patients survived 5 years after their initial
   diagnosis [[42]2]. Currently, more than 3.8 million women in the US are
   estimated to have a history of breast cancer, comprising the largest
   group of cancer survivors [[43]1]. Meanwhile, breast cancer patients
   generally report poorer health compared to the general population even
   after successful treatment [[44]3, [45]4]. Higher risks for
   cardiovascular disease (CVD) [[46]5–[47]7], pulmonary disease [[48]8],
   fatigue [[49]9], chronic pain [[50]10], and cognitive decline [[51]11]
   are documented among breast cancer survivors. Studies have suggested
   that CVD is the largest single cause of death among breast cancer
   survivors, exceeding cancer-related causes [[52]12].

   The long-term sequelae of breast cancer are usually attributed to the
   side effects of cancer therapies, because radiotherapy, chemotherapy,
   and trastuzumab therapy are able to induce cardiotoxicity and have been
   linked to higher risks for cardiovascular and pulmonary diseases
   [[53]13–[54]23]. However, not all sequelae can be explained by cancer
   therapies. Genetic susceptibility [[55]24, [56]25] and shared risk
   factors including age, obesity, and physical inactivity
   [[57]26–[58]30], also contribute to the development of long-term
   sequelae after breast cancer diagnosis. Among all potential risk
   factors, biological changes induced by breast cancer among survivors
   should not be overlooked.

   Given that these long-term sequelae appear to manifest nearly 5 years
   after initial diagnosis of breast cancer [[59]5, [60]7], there exists a
   potential window period for interventions mitigating disease burdens.
   Meanwhile, minority groups such as African American face a
   disproportionately large burden of both breast cancer and chronic
   diseases [[61]31]. Therefore, understanding the cause and etiology of
   these sequelae among breast cancer patients will be crucial for the
   development of such medical interventions, especially among minority
   groups.

   As disturbances in metabolic activities underlie most diseases, the
   study of the metabolome can provide important insight into the etiology
   of breast cancer sequelae as well as offer the potential to identify
   metabolic pathways for clinical interventions [[62]32]. More recently,
   metabolomics technologies give us the ability to measure thousands of
   metabolites in biological samples, assisting researchers in the
   investigation of metabolic changes. Metabolomics has demonstrated an
   emerging and promising role in the diagnosis and prognosis of chronic
   diseases and clinical interventions [[63]33].

   Within this context, we aim to investigate the metabolic profile of
   breast cancer patients soon after diagnosis and identify potential
   biological pathways using the state-of-the-art metabolomics
   technologies among a case-control study with 125 breast cancer cases
   and 125 controls that were frequency-matched by age. All the
   participants were African American women residing in Chicago, offering
   the opportunity to mitigate the larger burdens of both breast cancer
   and chronic disease in this group [[64]31].

Method

Study population

   The Chicago Multiethnic Epidemiologic Breast Cancer Cohort (ChiMEC) was
   initiated as a hospital-based case-control study to facilitate research
   on the effects of high-penetrance susceptibility genes, common genetic
   variants, and environmental risk factors for breast cancer
   [[65]34–[66]37]. Breast cancer cases were followed for survival,
   disease recurrence, and other outcomes to form the ChiMEC cohort, with
   a current sample size of 5097 patients [[67]38]. Patients diagnosed or
   treated at the University of Chicago Hospitals were ascertained through
   the cancer risk clinic and breast center. Clinical, pathological, and
   treatment data were collected via electronic medical records.
   Epidemiological risk factor data were collected via a questionnaire. A
   biobank was established, collecting blood and tumor samples. This
   analysis randomly selected female African American patients who were
   ≥ 18 years of age at diagnosis, lived in Chicago, enrolled in the
   ChiMEC study between 2012 and 2018, had histologically diagnosed
   non-metastatic invasive breast cancer, and had serum samples available.
   Stage IV distant metastatic patients were excluded as these patients
   might have tumor cells in circulation and experience dramatic metabolic
   changes.

   The healthy controls were selected from the Chicago Multiethnic
   Prevention and Surveillance Study (COMPASS), a large scale,
   longitudinal cohort study with a current sample size of 7728
   participants from 72 of the 77 Chicago community areas [[68]39].
   Residents of the greater Chicago area were eligible for COMPASS if they
   were: (1) 18 or older at the time of enrollment; (2) able to give
   consent and provide survey data in English or Spanish; (3) willing to
   provide blood, urine, saliva samples, and access to medical records.
   Recruitment strategies to increase minority enrollment have included a
   predominantly minority interviewer team and focus on recruitment in
   census tracts with minority and diverse populations as the primary
   sampling unit. Enrollment entails the completion of a 1-hour long
   survey, consenting for past and future medical records from all
   sources, the collection of clinical and physical measurement data and
   the on-site collection of biological samples including blood, urine and
   saliva. On collection, all biological samples are processed and
   liquated within 24 h before long-term storage and subsequent analysis.
   Participants completed an extensive survey providing information on
   medical history, socioeconomic status, psychosocial variables,
   lifestyle behaviors, social environment, immune status, use of medical
   services, medication use, among other covariates. Blood collection
   occurred at the same time as consent and the in-person interview.

Informed consent

   has been obtained from all ChiMEC and COMPASS participants. For the
   current analysis, 125 African American participants were randomly
   selected from ChiMEC and COMPASS, respectively, frequency-matched by
   age. In addition to data collection through questionnaire interview and
   electronic medical records, we also conducted geocoding analysis based
   on residence addresses of participants in both studies to collect
   neighborhood-level characteristics, and we calculated area deprivation
   index (ADI) [[69]40].

High-resolution metabolomics

   The precipitation of proteins were performed using the Ostro 96-well
   plate by following the manufacturer’s protocol for each serum sample.
   In brief, 100uL of serum were placed in the well with 100uL of
   surrogate standard Loratadine. Then 200uL of cold solvent
   (acetonitrile:formic acid 99:1) were added, followed by gentle mixing
   before the filtration by manifold processor. The procedure was repeated
   with 400ul cold solvent (acetonitrile/water/formic acid 3:1:1%). The
   resulting solution were dried by nitrogen flow and reconstituted in
   200uL solvent (acetonitrile/water 1:1) with spiked-in internal
   standards (Celecobix and 4-Aminobiphenyl).

   For testing the serum extraction procedure, a quality control sample
   was prepared by mixing same volumes of all serum samples. The same
   extraction protocol was performed on these quality control samples
   randomly placed in the well plate. The quality control extracts
   together with the extraction blanks were injected during the sample
   analysis.

   Liquid chromatography mass spectrometry (LC-MS) analysis of the
   metabolite extracts was performed using an Agilent 6545 Q-TOF and
   1290UPLC system controlled by the Agilent Mass Hunter acquisition
   software. The mass spectrometer was operated in 2 GHz extended dynamic
   range mode employing precursor ion analysis for relative quantification
   experiments in positive/negative ion modes. Internal references were