A multiplexed, automated immuno-matrix assisted laser desorption/ionization mass spectrometry assay for simultaneous and precise quantitation of PTEN and p110α in cell lines and tumor tissues
Abstract:The PI3-kinase/AKT/mTOR pathway plays a central role in cancer signaling. While p110α is the catalytic α-subunit of PI3-kinase and a major drug target, PTEN is the main negative regulator of...
“…MALDI-TOF mass spectrometry technology has been widely used in clinical tumor diagnosis, treatment, and prognosis monitoring and can be used as a powerful tumor marker discovery research tool[ 18 ]. In the next few years, with the development of genomics and proteomics, an increasing number of new markers with high diagnostic sensitivity and specificity will be discovered, identified, and applied in the clinic, which will significantly improve the clinical detection rate of cancer, allow for its early diagnosis and treatment[ 19 ], and provide new methods and ideas for the study of tumorigenesis mechanisms[ 20 ].…”
BACKGROUND
Colorectal cancer (CRC) is a highly malignant cancer with a high incidence and mortality in China. It is urgent to find a diagnostic marker with higher sensitivity and specificity than the traditional approaches for CRC diagnosis.
AIM
To provide new ideas for the diagnosis of CRC based on serum proteomics.
METHODS
Specimens from 83 healthy people, 62 colon polyp (CRP) patients, and 101 CRC patients were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic value of the profiles of differentially expressed proteins was then analyzed.
RESULTS
Compared with the healthy control group, CRC patients had elevated expression of 5 proteins and reduced expression of 14 proteins. The area under the curve (AUC) for a differentially expressed protein with a mass-to-charge ratio of 2022.34 was the largest; the AUC was 0.843, which was higher than the AUC of 0.717 observed with carcinoembryonic antigen (CEA), and the sensitivity and specificity of this identified marker were 75.3% and 79.5%, respectively. After cross-validation, the accuracy of diagnosis using levels of this differentially expressed protein was 82.37%. Compared with the CRP group, the expression of 3 proteins in the serum of CRC patients was elevated and 11 proteins were expressed at reduced levels. Proteins possessing mass-to-charge ratio values of 2899.38 and 877.3 were selected to establish a classification tree model. The results showed that the accuracy of CRC diagnosis was 89.5%, the accuracy of CRP diagnosis was 81.6%, and the overall accuracy of this approach was 86.3%. The overall sensitivity and specificity of diagnosis using the proteomics approach were 81.8% and 66.75%, respectively. The sensitivities and specificities of diagnoses based on CEA and carbohydrate antigen 19-9 expression were 55.6% and 91.3% and 65.4% and 65.2%, respectively.
CONCLUSION
We demonstrated that serum proteomics may be helpful for the detection of CRC, and it may assist clinical practice for CRC diagnosis.
“…MALDI-TOF mass spectrometry technology has been widely used in clinical tumor diagnosis, treatment, and prognosis monitoring and can be used as a powerful tumor marker discovery research tool[ 18 ]. In the next few years, with the development of genomics and proteomics, an increasing number of new markers with high diagnostic sensitivity and specificity will be discovered, identified, and applied in the clinic, which will significantly improve the clinical detection rate of cancer, allow for its early diagnosis and treatment[ 19 ], and provide new methods and ideas for the study of tumorigenesis mechanisms[ 20 ].…”
BACKGROUND
Colorectal cancer (CRC) is a highly malignant cancer with a high incidence and mortality in China. It is urgent to find a diagnostic marker with higher sensitivity and specificity than the traditional approaches for CRC diagnosis.
AIM
To provide new ideas for the diagnosis of CRC based on serum proteomics.
METHODS
Specimens from 83 healthy people, 62 colon polyp (CRP) patients, and 101 CRC patients were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. The diagnostic value of the profiles of differentially expressed proteins was then analyzed.
RESULTS
Compared with the healthy control group, CRC patients had elevated expression of 5 proteins and reduced expression of 14 proteins. The area under the curve (AUC) for a differentially expressed protein with a mass-to-charge ratio of 2022.34 was the largest; the AUC was 0.843, which was higher than the AUC of 0.717 observed with carcinoembryonic antigen (CEA), and the sensitivity and specificity of this identified marker were 75.3% and 79.5%, respectively. After cross-validation, the accuracy of diagnosis using levels of this differentially expressed protein was 82.37%. Compared with the CRP group, the expression of 3 proteins in the serum of CRC patients was elevated and 11 proteins were expressed at reduced levels. Proteins possessing mass-to-charge ratio values of 2899.38 and 877.3 were selected to establish a classification tree model. The results showed that the accuracy of CRC diagnosis was 89.5%, the accuracy of CRP diagnosis was 81.6%, and the overall accuracy of this approach was 86.3%. The overall sensitivity and specificity of diagnosis using the proteomics approach were 81.8% and 66.75%, respectively. The sensitivities and specificities of diagnoses based on CEA and carbohydrate antigen 19-9 expression were 55.6% and 91.3% and 65.4% and 65.2%, respectively.
CONCLUSION
We demonstrated that serum proteomics may be helpful for the detection of CRC, and it may assist clinical practice for CRC diagnosis.
Capivasertib is a potent selective inhibitor of AKT. It was recently FDA-approved in combination with fulvestrant to treat HR+, HER2-negative breast cancers with certain genetic alteration(s) activating the PI3K pathway. In Phase I trials, heavily pre-treated patients with tumours selected for activating PI3K pathway mutations treated with capivasertib monotherapy demonstrated objective response rates of <30%. We investigated the proteomic profile associated with capivasertib response in genetically pre-selected patients and cancer cell lines. We analyzed samples from 16 PIK3CA-mutated patient tumours collected prior to capivasertib monotherapy in the Phase I trial. PI3K pathway proteins were precisely quantified with immuno-MALDI-MS. Global proteomic profiles were also obtained. Patients were classified according to response to capivasertib monotherapy: “clinical benefit (CB)” (≥12 weeks without progression, n=7) or “no clinical benefit (NCB)” (progression in <12 weeks, n=9). Proteins that differed between the patient groups were subsequently quantified in AKT1- or PIK3CA-altered breast cancer cell lines with varying capivasertib sensitivity. The measured concentrations of AKT1 and AKT2 varied among the PIK3CA-mutated tumours but did not differ between the CB and NCB groups. However, analysis of the global proteome data showed that translational activity was higher in tumours of the NCB vs. CB group. When reproducibly quantified by validated LC-MRM-MS assays, the same proteins of interest similarly distinguished between capivasertib-sensitive vs. -resistant cell lines. The results provide further evidence that increased mTORC1-driven translation functions as a mechanism of resistance to capivasertib monotherapy. Protein concentrations may offer additional insights for patient selection for capivasertib, even among genetically pre-selected patients.
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