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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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Detection of three grades of Ade and SCC tissue lysates. (a) Change in absorption intensities for three different tissue lysates (normal, Ade and SCC) using the ssDNA-AuNPs-GO sensor array (NP1-NP6). (b) Canonical score plot of the absorbance patterns as obtained from LDA against the three grades of Ade patients. (c) LDA score plot derived from the absorbance changes for the three grades of SCC patients. (d) Heat map derived from absorbance response pattern for different grades of Ade and SCC patients.
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Figure 6: Detection of three grades of Ade and SCC tissue lysates. (a) Change in absorption intensities for three different tissue lysates (normal, Ade and SCC) using the ssDNA-AuNPs-GO sensor array (NP1-NP6). (b) Canonical score plot of the absorbance patterns as obtained from LDA against the three grades of Ade patients. (c) LDA score plot derived from the absorbance changes for the three grades of SCC patients. (d) Heat map derived from absorbance response pattern for different grades of Ade and SCC patients.

Mentions: To provide a test bed for more thoroughly analyzing tumor classification, we prepare tissue lysates from three tumor grades (G1: well-differentiated, G2: moderately-differentiated, and G3: poorly-differentiated) of Ade and SCC individuals. Due to their high genetic similarity, tumor grade classifications are expected to present a particularly stringent test for detection assays. The same sensing assays are performed using 100 ng of proteins. A distinct and reproducible absorbance response pattern is observed for the three grades of two tumor tissues (Figure 6a). In the canonical score plots obtained from LDA, the different grades of two tumors are clustered into non-overlapping groups, respectively (95% confidence ellipses).


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)

Detection of three grades of Ade and SCC tissue lysates. (a) Change in absorption intensities for three different tissue lysates (normal, Ade and SCC) using the ssDNA-AuNPs-GO sensor array (NP1-NP6). (b) Canonical score plot of the absorbance patterns as obtained from LDA against the three grades of Ade patients. (c) LDA score plot derived from the absorbance changes for the three grades of SCC patients. (d) Heat map derived from absorbance response pattern for different grades of Ade and SCC patients.
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Related In: Results  -  Collection

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Figure 6: Detection of three grades of Ade and SCC tissue lysates. (a) Change in absorption intensities for three different tissue lysates (normal, Ade and SCC) using the ssDNA-AuNPs-GO sensor array (NP1-NP6). (b) Canonical score plot of the absorbance patterns as obtained from LDA against the three grades of Ade patients. (c) LDA score plot derived from the absorbance changes for the three grades of SCC patients. (d) Heat map derived from absorbance response pattern for different grades of Ade and SCC patients.
Mentions: To provide a test bed for more thoroughly analyzing tumor classification, we prepare tissue lysates from three tumor grades (G1: well-differentiated, G2: moderately-differentiated, and G3: poorly-differentiated) of Ade and SCC individuals. Due to their high genetic similarity, tumor grade classifications are expected to present a particularly stringent test for detection assays. The same sensing assays are performed using 100 ng of proteins. A distinct and reproducible absorbance response pattern is observed for the three grades of two tumor tissues (Figure 6a). In the canonical score plots obtained from LDA, the different grades of two tumors are clustered into non-overlapping groups, respectively (95% confidence ellipses).

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