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Abstract Introduction
Cancer is a complex and life threatening diseases, existing in many forms which have unknown pathogenesis. A combination of factors are known to contribute to increasing the probability of encountering cancer. Lifestyle factors such as smoking are known to contribute towards both lung and bladder cancer, with lung cancer providing over 230,000 diagnosed cases in the United States annually. Here, we present a study comparing plasma samples from a cohort of bladder and lung cancer patients, with those of healthy controls using a high-throughput OMICS workflow. This LC-MS workflow allows for the rapid screening and semi-quantification of various compound classes and peptides using a single LC-MS platform.
Methods
A targeted OMICS solution was used for the rapid screening and semi-quantification of multiple compound classes using a single LC-MS and informatics platform. Plasma samples from a cohort consisting of bladder and lung cancer patients as well as those of healthy controls were analysed. All LC and MS methods were generated using the Waters Targeted OMICS method library, and did not require any optimization.
A known level of labeled analogues from each compound class was added to each sample. The level of each analyte was estimated from its ratio to the appropriate analogue.
LC-MS data were processed using Skyline. Additional visualization and analyses were performed using Metaboanalyst.
Preliminary results
Data was collected for 18 plasma samples (6 controls, 6 bladder cancer and 6 lung cancers), each sample was run in duplicate (proteins) or triplicate (acylcarnitines and amino acids). Pooled QC's were acquired every 9th inj.
128 compounds were detected and quantified using Skyline, generating a %CV less than 20% for the QC samples: 80 proteins, 20 acylcarnitines and 28 amino acids. High precision was demonstrated for the the quality control samples. Valine-d8 (spiked in all samples for the amino acid screening) is used as an example to illustrate the consistency of peak area across the whole study (<5% CV).
Pair-wise comparisons using a t-test were performed on each compound class. 12 compounds were highlighted as differentially expressed between bladder / control and 11 between lung / control. For example, the amino acid sarcosine was demonstrated to be up-regulated in both lung and bladder cancer samples; the acyl carnitine analysis highlighted Octenoyl carnitine (C8:1) as being down-regulated in the bladder cancer cohort; and the protein analysis found that various analytes were differentiating, including Apolipoprotein C-III and H
Overall the data demonstrated the ability of this targeted OMICS approach to highlight potential and relevant markers of interest in a simple and rapid manner. There was no need for method development and results were obtained in less than 24 hours. The next step in the study would be to concentrate on the highlighted markers and validate them by performing a more statistically rigorous study. |
= Discovery stage.
= Translation stage.
= Clinically available.
