Targeted metabolomics in colorectal cancer: a strategic approach using standardized laboratory tests of the blood and urine

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

Release of volatile organic compounds (VOCs) from colorectal cancer cell line LS174T

Colorectal cancer (CRC) is the third most common cancer worldwide. To date, no non-invasive and specific biomarkers have been identified for the diagnosis of CRC. The analysis of volatile organic compounds (VOCs) is attracting increasing attention and provides the possibility of a non-invasive diagnosis. Solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS) have been used to analyze the VOCs released from the headspace gas of LS174T (Dukes' type B colorectal adenocarcinoma) cells, arsenic trioxide (ATO)-treated LS174T cells and the blood from tumor-bearing mice. The data were processed using principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), which showed that the levels of decanal, 2,4-dimethyl- heptane, and twelve other metabolites were significantly greater in the headspace gas of the LS174T cells and blood of tumor-bearing mice. Additionally, in vivo experiments indicated that formic acid, ethenyl ester and p-trimethylsilyloxyphenyl-(trimethylsilyloxy)trimethylsilylacrylate were consumed during tumor growth. In conclusion, VOCs such as 1-methoxy-hexane and 2,4-dimethyl-heptane could be useful diagnostic markers for CRC. Further research should focus on the potential metabolic pathways associated with these profiles.

Investigation of altered urinary metabolomic profiles of invasive ductal carcinoma of breast using targeted and untargeted approaches

INTRODUCTION

Invasive ductal carcinoma (IDC) is a type of breast cancer, usually detected in advanced stages due to its asymptomatic nature which ultimately leads to low survival rate. Identification of urinary metabolic adaptations induced by IDC to understand the disease pathophysiology and monitor therapy response would be a helpful approach in clinical settings. Moreover, its non-invasive and cost effective strategy better suited to minimize apprehension among high risk population.

OBJECTIVE

This study aims toward investigating the urinary metabolic alterations of IDC by targeted (LC-MRM/MS) and untargeted (GC-MS) approaches for the better understanding of the disease pathophysiology and monitoring therapy response.

METHODS

Urinary metabolic alterations of IDC subjects (63) and control subjects (63) were explored by targeted (LC-MRM/MS) and untargeted (GC-MS) approaches. IDC specific urinary metabolomics signature was extracted by applying both univariate and multivariate statistical tools.

RESULTS

Statistical analysis identified 39 urinary metabolites with the highest contribution to metabolomic alterations specific to IDC. Out of which, 19 metabolites were identified from targeted LC-MRM/MS analysis, while 20 were identified from the untargeted GC-MS analysis. Receiver operator characteristic (ROC) curve analysis evidenced 6 most discriminatory metabolites from each type of approach that could differentiate between IDC subjects and controls with higher sensitivity and specificity. Furthermore, metabolic pathway analysis depicted several dysregulated pathways in IDC including sugar, amino acid, nucleotide metabolism, TCA cycle etc. CONCLUSIONS: Overall, this study provides valuable inputs regarding altered urinary metabolites which improved our knowledge on urinary metabolomic alterations induced by IDC. Moreover, this study identified several dysregulated metabolic pathways which offer further insight into the disease pathophysiology.

Clinical multi-omics strategies for the effective cancer management

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis.

BIOLOGICAL SIGNIFICANCE

In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.