title: Comparison of Automated and Conventional IHC Visual Scoring Analysis for MHC Class I and Tapasin Expression in Cervical Carcinoma.
abstract: BACKGROUND
  Cervical cancer (CXCA) is the second most common cancer among women in Thailand and worldwide. Immune evasion caused by down-regulation of host immune responsive genes, such as MHC class I and loss of antigen processing machinery (APM), presents a capability leading to cancer development. Immunohistochemical staining (HC) is regarded as a common technique for protein marker detection in clinical laboratories. At present, IHC automation has been launched to facilitate the speed and feasibility to replace conventional IHC. However, evaluation of its use is still limited.
  
  
  OBJECTIVE
  This study aimed to evaluate IHC scoring by automated visual analysis compared to conventional IHC analysis.
  
  
  METHODS
  The paraffin-embedded tissues of 96 invasive CXCA were processed using a tissue microarray (TMA) platform followed by automated IHC staining of the anti-MHC class I (heavy chain, β2M) and an APM-Tapasin expression. Conventional IHC and automated slide scanning with scoring visual analysis were compared.
  
  
  RESULTS
  The results showed significant association between conventional and automated IHC evaluation (p-value > 0.05, Chi-square) for MHC class I and Tapasin stated in percentage of positive cancer cells, whereas intensity was found (p-value < 0.05, Chi-square) with moderate agreement (p-value < 0.001, kappa) 0.434-0.615 and 0.353-0.554, respectively. After calculated values, the results showed significant association between conventional and automated IHC evaluation (p-value > 0.05, Chi-square) for MHC class I and Tapasin with the highest agreement level (p-value < 0.001, kappa) of summation 0.595-0.755 and multiply scoring 0.633-0.689, respectively.
  
  
  CONCLUSIONS
  The automation softwarefor IHC scoring and interpretation can be used for the determination of MHC class I and Tapasin in CXCA. In addition, an antigen presentation pattern must be included to allow an accurate result for MHC class I in clinical use. An appropriate sample size and design of staging coverage as well as clinical prognosis outcomes of progression should be used infurther investigation.
authors.forename: Surasak
authors.initials: S
authors.lastname: Wanram
authors.forename: Jakkra
authors.initials: J
authors.lastname: Sombatwong
authors.forename: Anun
authors.initials: A
authors.lastname: Sakunpong
authors.forename: Prinya
authors.initials: P
authors.lastname: Prasongdee
authors.forename: Pawana
authors.initials: P
authors.lastname: Panomket
authors.forename: Parichart
authors.initials: P
authors.lastname: Wongsena
authors.forename: Temduang
authors.initials: T
authors.lastname: Limpaiboon
authors.forename: Patcharee
authors.initials: P
authors.lastname: Jearanaikoon
mesh_terms: D002277:Carcinoma / Q000378:metabolism*; D005260:Female; D015870:Gene Expression; D005805:Genes, MHC Class I; D015395:Histocompatibility Antigens Class I; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D007150:Immunohistochemistry / Q000295:instrumentation* / Q000379:methods; D026901:Membrane Transport Proteins; D002583:Uterine Cervical Neoplasms / Q000378:metabolism*
chemical_list: D015395:Histocompatibility Antigens Class I; D026901:Membrane Transport Proteins; C107762:tapasin