title: Ultra-sensitive high performance liquid chromatography-laser-induced fluorescence based proteomics for clinical applications.
abstract: An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper.
  
  
  CONCLUSIONS
  In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India.
authors.affiliation: Dept. of Atomic and Molecular Physics, Manipal University, Manipal, Karnataka, India.
authors.forename: Ajeetkumar
authors.initials: A
authors.lastname: Patil
authors.affiliation: Dept. of Microbiology, Melaka Manipal Medical College, Manipal University, Manipal, India.
authors.forename: Sujatha
authors.initials: S
authors.lastname: Bhat
authors.affiliation: Dept. of Oral Medicine and Radiology, Manipal College of Dental Sciences, Manipal, India.
authors.forename: Keerthilatha M
authors.initials: KM
authors.lastname: Pai
authors.affiliation: Dept. of Obstetrics and Gynaecology, Kasturba Medical College, Manipal, India.
authors.forename: Lavanya
authors.initials: L
authors.lastname: Rai
authors.affiliation: 21, Udayagiri, Sion, Trombay, Mumbai, India.
authors.forename: V B
authors.initials: VB
authors.lastname: Kartha
authors.affiliation: Dept. of Atomic and Molecular Physics, Manipal University, Manipal, Karnataka, India. Electronic address: santhosh.cls@manipal.edu.
authors.forename: Santhosh
authors.initials: S
authors.lastname: Chidangil
mesh_terms: D000328:Adult; D000368:Aged; D002853:Chromatography, Liquid / Q000379:methods; D005260:Female; D005453:Fluorescence; D006801:Humans; D007834:Lasers; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000378:metabolism*; D040901:Proteomics / Q000295:instrumentation / Q000379:methods*; D002583:Uterine Cervical Neoplasms / Q000378:metabolism*
chemical_list: D009363:Neoplasm Proteins
keywords: Cervical cancer; HPLC–LIF; Oral cancer; Protein profiling