Infrared spectra of single biological cells often exhibit the ‘dispersion artefact’ observed as a sharp decrease in intensity on the high wavenumber side of absorption bands, in particular the Amide I band at ∼1655 cm⁻¹, causing a downward shift of the true peak position. The presence of this effect makes any biochemical interpretation of the spectra unreliable. Recent theory has shed light on the origins of the ‘dispersion artefact’ which has been attributed to resonant Mie scattering (RMieS). In this paper a preliminary algorithm for correcting RMieS is presented and evaluated using simulated data. Results show that the ‘dispersion artefact’ appears to be removed; however, the correction is not perfect. An iterative approach was subsequently implemented whereby the reference spectrum is improved after each iteration, resulting in a more accurate correction. Consequently the corrected spectra become increasingly more representative of the pure absorbance spectra. Using this correction method reliable peak positions can be obtained.

This communication reports that three prostate cancer cells of differing metastatic potential were discriminated based on their Young's moduli (LNCaP – 287 ± 52 N m⁻², PC-3 – 1401 ± 162 N m⁻² and BPH – 2797 ± 491 N m⁻²) which were determined using AFM and the Hertz model.

The detection of promoter region hypermethylation and transcriptional silencing has facilitated the identification of candidate renal cell carcinoma (RCC) tumour suppressor genes (TSGs). We have used a genome-wide strategy (methylated DNA immunoprecipitation (MeDIP) and whole-genome array analysis in combination with high-density expression array analysis) to identify genes that are frequently methylated and silenced in RCC. MeDIP analysis on 9 RCC tumours and 3 non-malignant normal kidney tissue samples was performed, and an initial shortlist of 56 candidate genes that were methylated by array analysis was further investigated; 9 genes were confirmed to show frequent promoter region methylation in primary RCC tumour samples (KLHL35 (39%), QPCT (19%), SCUBE3 (19%), ZSCAN18 (32%), CCDC8 (35%), FBN2 (34%), ATP5G2 (36%), PCDH8 (58%) and CORO6 (22%)). RNAi knockdown for KLHL35, QPCT, SCUBE3, ZSCAN18, CCDC8 and FBN2 resulted in an anchorage-independent growth advantage. Tumour methylation of SCUBE3 was associated with a significantly increased risk of cancer death or relapse (P=0.0046). The identification of candidate epigenetically inactivated RCC TSGs provides new insights into renal tumourigenesis.

Fourier transform infrared (FTIR) spectroscopy is a vibrational spectroscopic technique that uses infrared radiation to vibrate molecular bonds within the sample that absorbs it. As different samples contain different molecular bonds or different configurations of molecular bonds, FTIR allows us to obtain chemical information on molecules within the sample. Fourier transform infrared microspectroscopy in conjunction with a principal component-discriminant function analysis (PC-DFA) algorithm was applied to the grading of prostate cancer (CaP) tissue specimens. The PC-DFA algorithm is used alongside the established diagnostic measures of Gleason grading and the tumour/node/metastasis system. Principal component-discriminant function analysis improved the sensitivity and specificity of a three-band Gleason score criterion diagnosis previously reported by attaining an overall sensitivity of 92.3% and specificity of 99.4%. For the first time, we present the use of a two-band criterion showing an association of FTIR-based spectral characteristics with clinically aggressive behaviour in CaP manifest as local and/or distal spread. This paper shows the potential for the use of spectroscopic analysis for the evaluation of the biopotential of CaP in an accurate and reproducible manner.

Promoter region hyermethylation and transcriptional silencing is a frequent cause of tumour suppressor gene (TSG) inactivation in many types of human cancers. Functional epigenetic studies, in which gene expression is induced by treatment with demethylating agents, may identify novel genes with tumour-specific methylation. We used high-density gene expression microarrays in a functional epigenetic study of 11 renal cell carcinoma (RCC) cell lines. Twenty-eight genes were then selected for analysis of promoter methylation status in cell lines and primary RCC. Eight genes (BNC1, PDLIM4, RPRM, CST6, SFRP1, GREM1, COL14A1 and COL15A1) showed frequent (>30% of RCC tested) tumour-specific promoter region methylation. Hypermethylation was associated with transcriptional silencing. Re-expression of BNC1, CST6, RPRM and SFRP1 suppressed the growth of RCC cell lines and RNA interference knock-down of BNC1, SFRP1 and COL14A1 increased the growth of RCC cell lines. Methylation of BNC1 or COL14A1 was associated with a poorer prognosis independent of tumour size, stage or grade. The identification of these epigenetically inactivated candidate RCC TSGs can provide insights into renal tumourigenesis and a basis for developing novel therapies and biomarkers for prognosis and detection.