Breast cancer remains a leading cause of morbidity and mortality worldwide yet methods for early detection remain elusive. We describe the discovery and validation of biochemical signatures measured by mass spectrometry, performed upon blood samples from patients and controls that accurately identify (>95%) the presence of clinical breast cancer. Targeted quantitative MS/MS conducted upon 1225 individuals, including patients with breast and other cancers, normal controls as well as individuals with a variety of metabolic disorders provide a biochemical phenotype that accurately identifies the presence of breast cancer and predicts response and survival following the administration of neoadjuvant chemotherapy. The metabolic changes identified are consistent with inborn-like errors of metabolism and define a continuum from normal controls to elevated risk to invasive breast cancer. Similar results were observed in other adenocarcinomas but were not found in squamous cell cancers or hematologic neoplasms. The findings describe a new early detection platform for breast cancer and support a role for pre-existing, inborn-like errors of metabolism in the process of breast carcinogenesis that may also extend to other glandular malignancies.Statement of Significance: Findings provide a powerful tool for early detection and the assessment of prognosis in breast cancer and define a novel concept of breast carcinogenesis that characterizes malignant transformation as the clinical manifestation of underlying metabolic insufficiencies.
focused on microRNAs (miRs), the most abundant class of small RNAs in these samples. Informed consent was given by all patients. Results and discussions On average, we detected 233 miRs in tumours and 175 in exosomes that were classified as present/ absent and interrogated across samples. Cross-sectional analysis: same timepoint across patients. Longitudinal analysis: tumour and exosomes from the same patient. Cross-sectional analysis identified 49 miRs shared by all tumours, 33 by all exosomes collected before surgery, 83 by all exosomes collected after surgery. To pinpoint miRs useful to monitor tumour dynamics in each patient, three criteria were defined: 1) miRs present both in tumours and exosomes before surgery, and; 2) miRs present in tumours and absent in exosomes soon-after surgery. We found 133 miRs in patients A, 50 in B, 34 in C and 11 in D. Combining the cross-sectional and longitudinal analysis, we found two miRs fulfilling the above criteria that were shared by three out of four patients. These two miRs were still detected in Patient D exosomes soon after surgery, likely reflecting non-curative surgery. Validation of these data is currently ongoing in a larger series of patients. Conclusion Overall, this study pinpointed two miRs that may prove useful to monitor tumour dynamics and response to treatment in GC. The longitudinal analysis holds the promise of revealing a set of miRs with clinical utility for anticipating disease relapse, on a personalised manner.
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