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An array-based approach to determine different subtype and differentiation of non-small cell lung cancer.

Li C, Yang Y, Wei L, Wang X, Wang Z, Yin Y, Li G - Theranostics (2015)

Bottom Line: Strategically, we first select eight proteins at 0.5 nM concentration in buffer or 10 nM in human serum to verify the discriminant ability of our method, then choose adenocarcinoma and squamous-cell carcinoma that account for 90% non-small cell lung cancer, as well as their respective three tumor grades as model system to provide a realistic testing ground for clinical cancer analysis.Consequently, total differentiation between different subtype and grade of tumor tissues has been achieved with as little as 100 ng of intracellular protein, suggesting the high sensitivity and selectivity of this sensor array.Overall, this array-based approach may provide the possibility for unbiased and simplified personalized tumor classification diagnostics in the future.

View Article: PubMed Central - PubMed

Affiliation: 1. State Key Laboratory of Pharmaceutical Biotechnology, Department of Biochemistry,Nanjing University, Nanjing 210093, China.

ABSTRACT
Simple and accurate methods of discriminating subtype or differentiation of human tumor are critical for designing treatment strategies and predicting disease prognosis, and the currently used method to determine the two important factors mainly depends on histological examination by microscopy observation, which is laborious, highly trained operator required, and prone to be disruptive due to individual-to-individual judgment. Here we report a novel array-based method based on the interaction of graphene oxide (GO) and single-strand DNA modified gold nanoparticles (ssDNA-AuNPs) to distinguish between different subtypes and grades of tumors through their overall intracellular proteome signatures. Strategically, we first select eight proteins at 0.5 nM concentration in buffer or 10 nM in human serum to verify the discriminant ability of our method, then choose adenocarcinoma and squamous-cell carcinoma that account for 90% non-small cell lung cancer, as well as their respective three tumor grades as model system to provide a realistic testing ground for clinical cancer analysis. Consequently, total differentiation between different subtype and grade of tumor tissues has been achieved with as little as 100 ng of intracellular protein, suggesting the high sensitivity and selectivity of this sensor array. Overall, this array-based approach may provide the possibility for unbiased and simplified personalized tumor classification diagnostics in the future.

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Related in: MedlinePlus

Two-dimensional LDA score plot derived from combining the absorbance response patterns of different grades of two tumor types, with 95% confidence ellipses. The color shading is drawn to show the distinct regions between Ade and SCC tissues.
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Figure 7: Two-dimensional LDA score plot derived from combining the absorbance response patterns of different grades of two tumor types, with 95% confidence ellipses. The color shading is drawn to show the distinct regions between Ade and SCC tissues.

Mentions: Significantly, when the absorbance response data from the different degrees of differentiation of Ade and SCC tissue lysates are combined and analyzed by LDA, the Ade and SCC tissues cluster into two completely separate regions along the F1 and F2 axes (Figure 7), suggesting a dramatic difference between the fingerprint-like response patterns. In addition, no overlap is observed in the 2D plot, and 100% classification accuracy of all six analytes is obtained. A general trend is also found, where the well-differentiated of Ade and SCC are located on the left side and the moderately or poorly-differentiated tumor are located on the right side. To confirm the detection efficiency of our sensitive array-based strategy, we have also performed blind experiments to identify unknown samples from patients chosen from the training matrix. Of 30 cases, 27 are correctly classified with an identification accuracy of 90% (Table S9 in the Supplementary Material). All in all, the developed array-based sensing approach can completely identify healthy and tumor tissue, as well as discriminating between tumor grades, providing a promising strategy for tumor classification in cancer diagnosis.


An array-based approach to determine different subtype and differentiation of non-small cell lung cancer.

Li C, Yang Y, Wei L, Wang X, Wang Z, Yin Y, Li G - Theranostics (2015)

Two-dimensional LDA score plot derived from combining the absorbance response patterns of different grades of two tumor types, with 95% confidence ellipses. The color shading is drawn to show the distinct regions between Ade and SCC tissues.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4265748&req=5

Figure 7: Two-dimensional LDA score plot derived from combining the absorbance response patterns of different grades of two tumor types, with 95% confidence ellipses. The color shading is drawn to show the distinct regions between Ade and SCC tissues.
Mentions: Significantly, when the absorbance response data from the different degrees of differentiation of Ade and SCC tissue lysates are combined and analyzed by LDA, the Ade and SCC tissues cluster into two completely separate regions along the F1 and F2 axes (Figure 7), suggesting a dramatic difference between the fingerprint-like response patterns. In addition, no overlap is observed in the 2D plot, and 100% classification accuracy of all six analytes is obtained. A general trend is also found, where the well-differentiated of Ade and SCC are located on the left side and the moderately or poorly-differentiated tumor are located on the right side. To confirm the detection efficiency of our sensitive array-based strategy, we have also performed blind experiments to identify unknown samples from patients chosen from the training matrix. Of 30 cases, 27 are correctly classified with an identification accuracy of 90% (Table S9 in the Supplementary Material). All in all, the developed array-based sensing approach can completely identify healthy and tumor tissue, as well as discriminating between tumor grades, providing a promising strategy for tumor classification in cancer diagnosis.

Bottom Line: Strategically, we first select eight proteins at 0.5 nM concentration in buffer or 10 nM in human serum to verify the discriminant ability of our method, then choose adenocarcinoma and squamous-cell carcinoma that account for 90% non-small cell lung cancer, as well as their respective three tumor grades as model system to provide a realistic testing ground for clinical cancer analysis.Consequently, total differentiation between different subtype and grade of tumor tissues has been achieved with as little as 100 ng of intracellular protein, suggesting the high sensitivity and selectivity of this sensor array.Overall, this array-based approach may provide the possibility for unbiased and simplified personalized tumor classification diagnostics in the future.

View Article: PubMed Central - PubMed

Affiliation: 1. State Key Laboratory of Pharmaceutical Biotechnology, Department of Biochemistry,Nanjing University, Nanjing 210093, China.

ABSTRACT
Simple and accurate methods of discriminating subtype or differentiation of human tumor are critical for designing treatment strategies and predicting disease prognosis, and the currently used method to determine the two important factors mainly depends on histological examination by microscopy observation, which is laborious, highly trained operator required, and prone to be disruptive due to individual-to-individual judgment. Here we report a novel array-based method based on the interaction of graphene oxide (GO) and single-strand DNA modified gold nanoparticles (ssDNA-AuNPs) to distinguish between different subtypes and grades of tumors through their overall intracellular proteome signatures. Strategically, we first select eight proteins at 0.5 nM concentration in buffer or 10 nM in human serum to verify the discriminant ability of our method, then choose adenocarcinoma and squamous-cell carcinoma that account for 90% non-small cell lung cancer, as well as their respective three tumor grades as model system to provide a realistic testing ground for clinical cancer analysis. Consequently, total differentiation between different subtype and grade of tumor tissues has been achieved with as little as 100 ng of intracellular protein, suggesting the high sensitivity and selectivity of this sensor array. Overall, this array-based approach may provide the possibility for unbiased and simplified personalized tumor classification diagnostics in the future.

Show MeSH
Related in: MedlinePlus