Araştırma Makalesi
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Yıl 2023, Cilt: 8 Sayı: 2, 41 - 44
https://doi.org/10.52876/jcs.1383798

Öz

Kaynakça

  • REFERENCES
  • [1] T. Akinyemiju, S. Abera, M. Ahmed, N. Alam, M. A. Alemayohu, C. Allen, et al., (2017) The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national level: results from the global burden of disease study 2015 JAMA oncology, vol. 3, pp. 1683-1691.
  • [2] P. R. Galle, A. Forner, J. M. Llovet, V. Mazzaferro, F. Piscaglia, J.-L. Raoul, et al. (2018) EASL clinical practice guidelines: management of hepatocellular carcinoma. Journal of hepatology, vol. 69, pp. 182-236.
  • [3] H. B. El–Serag and K. L. Rudolph (2007) Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology, vol. 132, pp. 2557-2576.
  • [4] Z. Ding, N. Wang, N. Ji, and Z.-S. Chen (2022) Proteomics technologies for cancer liquid biopsies. Molecular Cancer, vol. 21, p. 53.
  • [5] S. Aksoy, M. ÖZAVSAR, A. ALTINDAL (2022) Classification of VOC Vapors Using Machine Learning Algorithms Journal of Engineering Technology and Applied Sciences, vol. 7, pp. 97-107.
  • [6] W. Naboulsi, D. A. Megger, T. Bracht, M. Kohl, M. Turewicz, M. Eisenacher, et al. (2016) Quantitative tissue proteomics analysis reveals versican as potential biomarker for early-stage hepatocellular carcinoma. Journal of proteome research, vol. 15, pp. 38-47.
  • [7] M. Schonlau and R. Y. Zou (2020) The random forest algorithm for statistical learning. The Stata Journal, vol. 20, pp. 3-29.
  • [8] F. Tang and H. Ishwaran (2017) Random forest missing data algorithms. Statistical Analysis and Data Mining: The ASA Data Science Journal, vol. 10, pp. 363-377.
  • [9] V. Fonti and E. Belitser (2017) Feature selection using lasso. vol. 30, pp. 1-25..
  • [10] T. Kimhofer, H. Fye, S. Taylor-Robinson, M. Thursz, and E. Holmes (2015) Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review. British journal of cancer, vol. 112, pp. 1141-1156.
  • [11] X. Zheng, Q. Peng, L. Wang, X. Zhang, L. Huang, J. Wang, et al. (2020) Serine/arginine-rich splicing factors: the bridge linking alternative splicing and cancer. International journal of biological sciences, vol. 16, p. 2442.
  • [12] R. Karni, E. de Stanchina, S. W. Lowe, R. Sinha, D. Mu, and A. R. Krainer (2007) The gene encoding the splicing factor SF2/ASF is a proto-oncogene. Nature structural & molecular biology, vol. 14, pp. 185-193.
  • [13] O. Anczuków, M. Akerman, A. Cléry, J. Wu, C. Shen, N. H. Shirole, et al. (2015) SRSF1-regulated alternative splicing in breast cancer. Molecular cell, vol. 60, pp. 105-117.
  • [14] F. J. de Miguel, R. D. Sharma, M. J. Pajares, L. M. Montuenga, A. Rubio, and R. Pio (2014) Identification of alternative splicing events regulated by the oncogenic factor SRSF1 in lung cancer. Cancer research, vol. 74, pp. 1105-1115.
  • [15] C. Ghigna, S. Giordano, H. Shen, F. Benvenuto, F. Castiglioni, P. M. Comoglio, et al. (2005) Cell motility is controlled by SF2/ASF through alternative splicing of the Ron protooncogene," Molecular cell, vol. 20, pp. 881-890.
  • [16] J. Long, Z.-W. Lang, H.-G. Wang, T.-L. Wang, B.-E. Wang, and S.-Q. Liu (2010) Glutamine synthetase as an early marker for hepatocellular carcinoma based on proteomic analysis of resected small hepatocellular carcinomas. Hepatobiliary Pancreat Dis Int, vol. 9, pp. 296-305.

Identifying Possible Biomarkers for Early-Stage Hepatocellular Carcinoma using Random Forest Machine Learning Method

Yıl 2023, Cilt: 8 Sayı: 2, 41 - 44
https://doi.org/10.52876/jcs.1383798

Öz

Hepatocellular carcinoma is a primary liver tumour arising from hepatocytes, the liver's own cells. It is one of the most common types of cancer in the world. The most important cause is chronic liver disease due to hepatitis B and C infections. In some patients, HCC causes symptoms such as abdominal pain, loss of appetite, anaemia, nausea, fatigue and jaundice and is diagnosed as a result of tests. In some patients, it is detected incidentally by liver ultrasound, tomography or MRI performed for another reason. The most typical finding is an increase in a substance called alpha-fetoprotein (AFP). Although this does not occur in all patients, elevated AFP in a patient with cirrhosis strongly indicates the presence of HCC. HCC can be seen on ultrasound, tomography or MRI films. Especially in tomography and MRI, the rapid and strong retention of the intravenous drug and then its early wash out is a typical finding and if detected in a patient with cirrhosis, HCC can be diagnosed without the need for biopsy. However, in many patients, imaging findings are not typical and a biopsy is required for diagnosis. In this study, a Random Forest machine learning model was created with proteomic data regarding the cancerous tumor tissue and the adjacent non-cancerous tissue of 19 HCC patients. the accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1-Score, MCC and G-Mean values for the Random Forest model were 0.90, 0.88, 0.90, 0.93, 0.82, 0.91, 0.82 and 0.91, respectively. Considering the model-dependent variable significance, SRSF1 and PBLD proteins are suggested as biomarkers that may be clinically useful in the diagnosis of early-stage HCC.

Etik Beyan

Since the data used in the study is open access, no ethics committee permission is required.

Destekleyen Kurum

There is no institution supporting the study.

Kaynakça

  • REFERENCES
  • [1] T. Akinyemiju, S. Abera, M. Ahmed, N. Alam, M. A. Alemayohu, C. Allen, et al., (2017) The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national level: results from the global burden of disease study 2015 JAMA oncology, vol. 3, pp. 1683-1691.
  • [2] P. R. Galle, A. Forner, J. M. Llovet, V. Mazzaferro, F. Piscaglia, J.-L. Raoul, et al. (2018) EASL clinical practice guidelines: management of hepatocellular carcinoma. Journal of hepatology, vol. 69, pp. 182-236.
  • [3] H. B. El–Serag and K. L. Rudolph (2007) Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology, vol. 132, pp. 2557-2576.
  • [4] Z. Ding, N. Wang, N. Ji, and Z.-S. Chen (2022) Proteomics technologies for cancer liquid biopsies. Molecular Cancer, vol. 21, p. 53.
  • [5] S. Aksoy, M. ÖZAVSAR, A. ALTINDAL (2022) Classification of VOC Vapors Using Machine Learning Algorithms Journal of Engineering Technology and Applied Sciences, vol. 7, pp. 97-107.
  • [6] W. Naboulsi, D. A. Megger, T. Bracht, M. Kohl, M. Turewicz, M. Eisenacher, et al. (2016) Quantitative tissue proteomics analysis reveals versican as potential biomarker for early-stage hepatocellular carcinoma. Journal of proteome research, vol. 15, pp. 38-47.
  • [7] M. Schonlau and R. Y. Zou (2020) The random forest algorithm for statistical learning. The Stata Journal, vol. 20, pp. 3-29.
  • [8] F. Tang and H. Ishwaran (2017) Random forest missing data algorithms. Statistical Analysis and Data Mining: The ASA Data Science Journal, vol. 10, pp. 363-377.
  • [9] V. Fonti and E. Belitser (2017) Feature selection using lasso. vol. 30, pp. 1-25..
  • [10] T. Kimhofer, H. Fye, S. Taylor-Robinson, M. Thursz, and E. Holmes (2015) Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review. British journal of cancer, vol. 112, pp. 1141-1156.
  • [11] X. Zheng, Q. Peng, L. Wang, X. Zhang, L. Huang, J. Wang, et al. (2020) Serine/arginine-rich splicing factors: the bridge linking alternative splicing and cancer. International journal of biological sciences, vol. 16, p. 2442.
  • [12] R. Karni, E. de Stanchina, S. W. Lowe, R. Sinha, D. Mu, and A. R. Krainer (2007) The gene encoding the splicing factor SF2/ASF is a proto-oncogene. Nature structural & molecular biology, vol. 14, pp. 185-193.
  • [13] O. Anczuków, M. Akerman, A. Cléry, J. Wu, C. Shen, N. H. Shirole, et al. (2015) SRSF1-regulated alternative splicing in breast cancer. Molecular cell, vol. 60, pp. 105-117.
  • [14] F. J. de Miguel, R. D. Sharma, M. J. Pajares, L. M. Montuenga, A. Rubio, and R. Pio (2014) Identification of alternative splicing events regulated by the oncogenic factor SRSF1 in lung cancer. Cancer research, vol. 74, pp. 1105-1115.
  • [15] C. Ghigna, S. Giordano, H. Shen, F. Benvenuto, F. Castiglioni, P. M. Comoglio, et al. (2005) Cell motility is controlled by SF2/ASF through alternative splicing of the Ron protooncogene," Molecular cell, vol. 20, pp. 881-890.
  • [16] J. Long, Z.-W. Lang, H.-G. Wang, T.-L. Wang, B.-E. Wang, and S.-Q. Liu (2010) Glutamine synthetase as an early marker for hepatocellular carcinoma based on proteomic analysis of resected small hepatocellular carcinomas. Hepatobiliary Pancreat Dis Int, vol. 9, pp. 296-305.
Toplam 17 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Öğrenme (Diğer)
Bölüm Articles
Yazarlar

Şeyma Yaşar 0000-0003-1300-3393

Erken Görünüm Tarihi 22 Ocak 2024
Yayımlanma Tarihi
Gönderilme Tarihi 31 Ekim 2023
Kabul Tarihi 23 Kasım 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 8 Sayı: 2

Kaynak Göster

APA Yaşar, Ş. (2024). Identifying Possible Biomarkers for Early-Stage Hepatocellular Carcinoma using Random Forest Machine Learning Method. The Journal of Cognitive Systems, 8(2), 41-44. https://doi.org/10.52876/jcs.1383798