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EXPRESSION OF THE TUMOR-ASSOCIATED PROTEINS IN THE OVARIAN CANCER

Т. С. Боброва, К. И. Жорданиа, Yu. V. Chuyev

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Abstract

With the help of monoclonal antibodies (MCA-1, MCA-3, G1 class immunoglobulins) and polyspecific antiserum (As) by means of immunoblotting (IB) the increase of the expression of the tumor-associated proteins (TAP) in the samples of the tumor tissues (in 94, 55 and 38% respectively), metastatic lymph nodes — LN(m+) and sera of the patients with ovarian cancer (OC) (in 82, 77 and ~100% of the cases, respectively), was detected. The important feature of As was the reactivity with the samples of the LN (m+) on the numerous proteins (>5-10) in 78% of the patients. The statistical analysis of the data using Student t-criterion revealed the significant differences (MCA-1, MCA-3) in the expression of the markers in the tumor tissues and blood sera of the oncological patients compar- ing with the samples of the adjacent tissues, blood sera of the patients with the other tumor localization and healthy donors (p<0,05). The further research using a larger amount of the clinical material and development of the more precise quantitative immunoenzyme analysis to measure TAP, is needed. It is possible that detection of TAP using MCA-1 and As may serve a basis for the creation of the test-system for the immunodiagnostics of the OC and determination of the stage of the tumor process.

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What this paper is about

With the help of monoclonal antibodies (MCA-1, MCA-3, G1 class immunoglobulins) and polyspecific antiserum (As) by means of immunoblotting (IB) the increase of the expression of the tumor-associated proteins (TAP) in the samples of the tumor tissues (in 94, 55 and 38% respectively), metastatic lymph nodes — LN(m+) and sera of the patients with ovarian cancer (OC) (in 82, 77 and ~100% of the cases, respectively), was detected. The important feature of As was the reactivity with the samples of the LN (m+) on the numerous proteins (>5-10) in 78% of the patients. The statistical analysis of the data using Student t-criterion revealed the significant differences (MCA-1, MCA-3) in the expression of the markers in the tumor tissues and blood sera of the oncological patients compar- ing with the samples of the adjacent tissues, blood sera of the patients with the other tumor localization and healthy donors (p<0,05). The further research using a larger amount of the clinical material and development of the more precise quantitative immunoenzyme analysis to measure TAP, is needed. It is possible that detection of TAP using MCA-1 and As may serve a basis for the creation of the test-system for the immunodiagnostics of the OC and determination of the stage of the tumor process.

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Available abstract

With the help of monoclonal antibodies (MCA-1, MCA-3, G1 class immunoglobulins) and polyspecific antiserum (As) by means of immunoblotting (IB) the increase of the expression of the tumor-associated proteins (TAP) in the samples of the tumor tissues (in 94, 55 and 38% respectively), metastatic lymph nodes — LN(m+) and sera of the patients with ovarian cancer (OC) (in 82, 77 and ~100% of the cases, respectively), was detected. The important feature of As was the reactivity with the samples of the LN (m+) on the numerous proteins (>5-10) in 78% of the patients. The statistical analysis of the data using Student t-criterion revealed the significant differences (MCA-1, MCA-3) in the expression of the markers in the tumor tissues and blood sera of the oncological patients compar- ing with the samples of the adjacent tissues, blood sera of the patients with the other tumor localization and healthy donors (p<0,05). The further research using a larger amount of the clinical material and development of the more precise quantitative immunoenzyme analysis to measure TAP, is needed. It is possible that detection of TAP using MCA-1 and As may serve a basis for the creation of the test-system for the immunodiagnostics of the OC and determination of the stage of the tumor process.

Key concepts: Ovarian cancer, Protein expression, Expression (computer science), Cancer research, Computational biology, Cancer, Biology, Oncology

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