Integrative approach for differentially overexpressed genes in gastric cancer by combining large-scale gene expression profiling and network analysis

Gene expression profiling is a valuable tool for identifying differentially expressed genes in studies of disease subtype and patient outcome for various cancers. However, it remains difficult to assign biological significance to the vast number of genes. There is an increasing awareness of gene expression profile as an important part of the contextual molecular network at play in complex biological processes such as cancer initiation and progression. This study analysed the transcriptional profiles commonly activated at different stages of gastric cancers using an integrated approach combining gene expression profiling of 222 human tissues and gene regulatory dynamic mapping. We focused on an inferred core network with CDKN1A (p21WAF1/CIP1) as the hub, and extracted seven candidates for gastric carcinogenesis (MMP7, SPARC, SOD2, INHBA, IGFBP7, NEK6, LUM). They were classified into two groups based on the correlation between expression level and stage. The seven genes were commonly activated and their expression levels tended to increase as disease progressed. NEK6 and INHBA are particularly promising candidate genes overexpressed at the protein level, as confirmed by immunohistochemistry and western blotting. This integrated approach could help to identify candidate players in gastric carcinogenesis and progression. These genes are potential markers of gastric cancer regardless of stage

Age estimation of teeth using Raman spectroscopy

U ovom radu istražena je mogućnost primjene Ramanove spektroskopije za forenzičko određivanje dobi. Ispitani uzorak sačinjen je od 71 zuba od donora starosne dobi između 11 i 76 godina. Pri izboru zubi za ispitivanje nisu primjenjivani specifični kriteriji; zubi zahvaćeni različitim patološkim promjenama namjerno su uključeni kako bi se simulirao realističan forenzički scenarij. Ramanovi spektri snimljeni su s površine zubi bez prethodne obrade, u skladu s nedestruktivnom pripremom uzoraka koja se općenito preferira u forenzičkim znanostima. Kako bi se ispitala iskoristivost različitih zubnih tkiva za određivanje dobi, Ramanovi spektri snimljeni su s tri različite pozicije na vanjskoj površini zuba: kruni, vratu i apeksu. Pomoću prikupljenih spektara tvrdih zubnih tkiva pripremljen je model određivanja starosne dobi metodom regresije glavnih komponenata. Cijeli spektri u rasponu od 3500–200 cm-1 upotrijebljeni su za analizu glavnih komponenata i pripremu modela za određivanje dobi pomoću regresije glavnih komponenata. Dobiveni rezultati modela za određivanje dobi potvrđeni su unakrsnom validacijom i usporedbom s rezultatima modela dobivenog parcijalnom regresijom najmanjih kvadrata. Prediktivne vrijednosti modela za određivanje dobi razlikovale su se ovisno o poziciji snimanja spektara. Najviši koeficijenti korelacije i najniže vrijednosti parametara pogreške su ostvareni u modelima temeljenim na spektrima s apeksa korijena zuba (R2 vrijednosti od 0,84 za muške i 0,71 za ženske donore). Modeli temeljeni na ostalim kombinacijama spola donora i pozicije snimanja pokazali su niže vrijednosti R2 , u rasponu od 0,17-0,59. Niske vrijednosti R2 (0,18-0,24) zapažene su i kod zajedničkih modela koji su uključivali spektre oba spola. Optimalno određivanje dobi ostvareno je primjenom Ramanovih spektara snimljenih s cementa na apeksu. Kako bi se omogućilo optimalno predviđanje dobi pomoću ispitivanih modela, bilo je potrebno odvojeno analizirati muške od ženskih donora, s obzirom da je spajanje oba spola u jedinstveni model značajno smanjilo njegovu prediktivnu vrijednost (R2 = 0,29). Zaključno, ovaj rad pokazao je mogućnost predviđanja dobi primjenom modela regresije glavnih komponenata uz korištenje Ramanovih spektara prikupljenih s vanjskih površina zubi zahvaćenih različitim patološkim procesima.Aim: Age determination is one of the most common forensic procedures which has a wide range of applications, including identifications of accident victims, crime investigations, and social benefit regulations. To date, only a few studies have employed Raman spectrometry to relate the aging-dependent compositional changes in tooth tissues with the donor’s age for forensic purposes. The available studies are limited to investigations of intact teeth, representing an ideal-case scenario which is quite different from forensic reality. Therefore, the aim of this study was to simulate a more realistic forensic scenario and evaluate the feasibility of Raman spectrometric age determination by using teeth affected by various pathologies. Also, tooth specimens were used for the collection of Raman spectra without any previous preparation, as non-destructive specimen handling is generally preferred in forensic investigations. Materials and methods: The sample of 71 teeth used for this study was obtained by a random draw from the archive of the Department of Dental Anthropology of the School of Dental Medicine, University of Zagreb, Croatia. The age of tooth donors ranged between 11 and 76 years. The teeth had been extracted due to various indications, most common being periodontitis (51 %) and failed endodontic treatment (39 %). To simulate a forensic analysis of teeth at different post-extraction time periods, the time span between extraction and performing Raman spectrometric measurements ranged between 0.1 and 5.5 years. No special selection criteria were applied; teeth affected with various pathological processes were deliberately included to simulate a realistic sample. Raman spectra were recorded using an FT-Raman accessory of the Spectrum GXspectrometer (Perkin-Elmer, Waltham, MA, USA) equipped with an Nd-YAG laser of 1064 nm wavelength. Each spectrum was recorded by averaging 100 scans in the spectral range between 3500 and 200 cm-1 and with a spectral resolution of 4 cm-1 . Spectra were collected from three distinct sites on each tooth: crown, neck, and apex. The spectra were stored in a dataset and connected with the donor’s age and collection site. All spectra were baseline corrected and normalized using the peak at 960 cm-1 (symmetric PO4 stretching) to exclude possible differences caused by variations in recording conditions. Whole Raman spectra (3500 – 200 cm-1 ) were used for principal component analysis (PCA) and principal component regression (PCR) with 3 to 7 principal components. PCR was used to establish a relationship between the recorded spectra and the donor’s age. PCA and PCR were performed using a model built within Matlab 2010 (MathWorks, Natick, MA, USA) and its add-on PLS_Toolbox (Eigenvector Research, Manson, WA, USA). Separate PCA/PCR models were built according to the spectra collection site and donor’s gender, resulting in the following six combinations: apex male, apex female, crown male, crown female, neck male, and neck female. Additionally, spectra from both genders were mixed together in three “joint” models that accounted only for the spectra collection site. All models were cross-validated using the Venetian blinds method. Results: Raman spectra of dental hard tissues featured the inorganic part represented by vibrational bands in the wavenumber range of 1100 – 400 cm-1 (PO4 and CO3 vibrations) and the organic part represented in the range of 3100 – 1100 cm-1 (amide bands and C-H vibrations). The inorganic/organic ratio was considerably higher in spectra collected from the crown compared to the other two sites. The changes in the intensity of bands representing both the inorganic and organic components of tooth tissues indicated that it is possible to build a PCA model for distinguishing donor’s age using Raman spectra. Also, the spectral changes occurring as a function of donor’s age indicates that a PCR model for age determination can be built. The predictive capabilities of PCR models for age determination differed according to different spectra collection sites. The highest coefficients of correlation and lowest error values were obtained in models based on apex spectra (R2 values of 0.84 and 0.71 for males and females, respectively). Models based on other combinations of genders and spectra collection sites had comparably lower R2 values, ranging from 0.17 to 0.59. Low R2 values (0.18 – 0.24) were also obtained for joint models that were built using spectra from both genders. The PCA models based on apex spectra showed a comparatively better separation of age groups than the models based on neck and crown spectra. Accordingly, the PCR age determination models based on apex spectra showed higher coefficients of determination and lower error values compared to the models based on neck and crown spectra. Conclusions: This study showed that the age determination model based on principal component regression can be built using Raman spectra collected from surfaces of non-sound teeth without any previous preparation. The optimal age determination capability was attained by using Raman spectra collected from cementum at root apex, whereas spectra collected from mineralized tissues at the tooth neck and crown were less suitable. The age determination model based on apex spectra showed an optimal performance only when tooth donor genders were analyzed separately

Principal Component Regression for Forensic Age Determination Using the Raman Spectra of Teeth

Raman spectra of mineralized tooth tissues were used to build a principal component regression (PCR) age determination model for forensic application. A sample of 71 teeth was obtained from donors aging from 11 to 76 years. No particular selection criteria were applied; teeth affected with various pathological processes were deliberately included to simulate a realistic forensic scenario. In order to comply with the nondestructive specimen handling, Raman spectra were collected from tooth surfaces without any previous preparation. Different tooth tissues were evaluated by collecting the spectra from three distinct sites: tooth crown, tooth neck, and root apex. Whole recorded spectra (3500–200 cm) were used for principal component analysis and building of the age determination model using PCR. The predictive capabilities of the obtained age determination models varied according to the spectra collection site. Optimal age determination was attained by using Raman spectra collected from cementum at root apex (R values of 0.84 and 0.71 for male and female donors, respectively). For optimal performance of that model, male and female donors had to be analyzed separately, as merging both genders into a single model considerably diminished its predictive capability (R = 0.29)

Possibility of Human Gender Recognition Using Raman Spectra of Teeth

Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender-dependent life events