Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Iwano, Tomohiko; Yoshimura, Kenichi; Inoue, Shunsuke B.; Odate, Toru; Ogata, Koretsugu; Funatsu, Shinji; Tanihata, Hiroshi; Kondo, Tetsuo; Ichikawa, Daisuke; Takeda, Sén

doi:10.1002/bjs.11613

Cited by 27 publications

(30 citation statements)

References 19 publications

(21 reference statements)

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“…Experiments have shown that a lipid is a useful biomarker for cancer diagnosis [ 63 , 64 ], especially in breast cancer. Therefore, the authors of this paper summarize the lipid molecules with diagnostic potential related to breast cancer in patients ( Table 1 ) [ 11 , 42 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 ].…”

Section: Role Of Lipid In the Diagnosis Of Breast Cancermentioning

confidence: 99%

The Function and Mechanism of Lipid Molecules and Their Roles in The Diagnosis and Prognosis of Breast Cancer

et al. 2020

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Lipids are essential components of cell structure and play important roles in signal transduction between cells and body metabolism. With the continuous development and innovation of lipidomics technology, many studies have shown that the relationship between lipids and cancer is steadily increasing, involving cancer occurrence, proliferation, migration, and apoptosis. Breast cancer has seriously affected the safety and quality of life of human beings worldwide and has become a significant public health problem in modern society, with an especially high incidence among women. Therefore, the issue has inspired scientific researchers to study the link between lipids and breast cancer. This article reviews the research progress of lipidomics, the biological characteristics of lipid molecules, and the relationship between some lipids and cancer drug resistance. Furthermore, this work summarizes the lipid molecules related to breast cancer diagnosis and prognosis, and then it clarifies their impact on the occurrence and development of breast cancer The discussion revolves around the current research hotspot long-chain non-coding RNAs (lncRNAs), summarizes and explains their impact on tumor lipid metabolism, and provides more scientific basis for future cancer research studies.

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Section: Role Of Lipid In the Diagnosis Of Breast Cancermentioning

confidence: 99%

The Function and Mechanism of Lipid Molecules and Their Roles in The Diagnosis and Prognosis of Breast Cancer

et al. 2020

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“…This was in good agreement with previous reports demonstrating significant changes in lipid profiles in cancer patients [ 20 – 22 ]. Other reports have demonstrated the high discriminant accuracy of PESI-MS and machine learning for head and neck cancer and breast cancer (92.9 and 96.0%, respectively) [ 12 , 23 ]. Similarly, this system also could rapidly discriminate CRLM from non-cancerous tissue.…”

Section: Discussionmentioning

confidence: 99%

A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis

et al. 2021

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Background Probe electrospray ionization-mass spectrometry (PESI-MS) can rapidly visualize mass spectra of small, surgically obtained tissue samples, and is a promising novel diagnostic tool when combined with machine learning which discriminates malignant spectrum patterns from others. The present study was performed to evaluate the utility of this device for rapid diagnosis of colorectal liver metastasis (CRLM). Methods A prospectively planned study using retrospectively obtained tissues was performed. In total, 103 CRLM samples and 80 non-cancer liver tissues cut from surgically extracted specimens were analyzed using PESI-MS. Mass spectra obtained by PESI-MS were classified into cancer or non-cancer groups by using logistic regression, a kind of machine learning. Next, to identify the exact molecules responsible for the difference between CRLM and non-cancerous tissues, we performed liquid chromatography-electrospray ionization-MS (LC-ESI-MS), which visualizes sample molecular composition in more detail. Results This diagnostic system distinguished CRLM from non-cancer liver parenchyma with an accuracy rate of 99.5%. The area under the receiver operating characteristic curve reached 0.9999. LC-ESI-MS analysis showed higher ion intensities of phosphatidylcholine and phosphatidylethanolamine in CRLM than in non-cancer liver parenchyma (P < 0.01, respectively). The proportion of phospholipids categorized as monounsaturated fatty acids was higher in CRLM (37.2%) than in non-cancer liver parenchyma (10.7%; P < 0.01). Conclusion The combination of PESI-MS and machine learning distinguished CRLM from non-cancer tissue with high accuracy. Phospholipids categorized as monounsaturated fatty acids contributed to the difference between CRLM and normal parenchyma and might also be a useful diagnostic biomarker and therapeutic target for CRLM.

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“…The PESI‐MS analysis was performed using a triple quadrupole mass spectrometer (DPiMS‐8060; Shimadzu Corp.), which has a PESI ion source that replaces the ESI module of the original LCMS‐8060 spectrometer. The mass spectra were acquired for nonneoplastic and PDAC specimens in the positive ion mode, and all subsequent analyses were performed as previously described previously 5–9 …”

Section: Methodsmentioning

confidence: 99%

New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound‐guided fine needle aspiration and surgery

et al. 2021

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Background and Aim Preoperative histological evaluation of pancreatic neoplasms is important for guiding the resection strategy and preventing postoperative adverse events. However, conventional endoscopic methods have technical limitations that reduce the accuracy of the histopathological examination. Probe electrospray ionization mass spectrometry (PESI‐MS) may be a useful technique for rapidly evaluating small specimens. Methods This single‐center prospective study included patients with pancreatic neoplasms between October 2018 and December 2019. Pancreatic ductal adenocarcinoma (PDAC) specimens were obtained via endoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) and non‐neoplastic tissue was obtained via surgery. Specimens were subjected to PESI‐MS and the mass spectra were analyzed using partial least squares regression‐discriminant analysis. Results The study included 40 patients with 20 nonneoplastic specimens and 19 PDAC specimens (1 case of neuroendocrine carcinoma was omitted). All nonneoplastic specimens were sufficient for PESI‐MS analysis, although only 7 of 19 PDAC specimens were sufficient for PESI‐MS analysis because of poor sample quality or insufficient quantity (<1 mg). Among the 27 analyzed cases, the mass spectra clearly differentiated between the PDAC and nonneoplastic specimens. Conclusions This study revealed that PESI‐MS could differentiate between PDAC and nonneoplastic specimens, even in cases where EUS‐FNA produced very small specimens.

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Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Cited by 27 publications

References 19 publications

The Function and Mechanism of Lipid Molecules and Their Roles in The Diagnosis and Prognosis of Breast Cancer

The Function and Mechanism of Lipid Molecules and Their Roles in The Diagnosis and Prognosis of Breast Cancer

A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis

New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound‐guided fine needle aspiration and surgery

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