J Cancer Prev 2021; 26(1): 32-40
Published online March 30, 2021
© Korean Society of Cancer Prevention
1Department of Obstetrics & Gynecology, 2Division of Biostatistics, 3Division of Hematology and Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, 4Department of Pathology, Johns Hopkins University, Baltimore, MD, 5Department of Pathology, The Ohio State University, Columbus, OH, 6Department of Hematology and Hematopoietic Cell Transplantation, Comprehensive Cancer Center, City of Hope National Medical Center, Duarte, CA, USA
Correspondence to :
Li-Shu Wang, E-mail: firstname.lastname@example.org, https://orcid.org/0000-0002-6500-6943
Jianhua Yu, E-mail: email@example.com, https://orcid.org/0000-0002-0326-3223
*These authors contributed equally to this work as co-first authors.
**These authors contributed equally to this work as co-correspondence authors.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Free fatty acid receptor 2 (
Keywords: Ffar2, ApcMin/+, Colorectal cancer, Metabolomics, Gut microbiota
Colorectal cancer is the second leading cause of cancer death in both sexes in the United States . Many factors are associated with the development of colorectal cancer, such as “unhealthy” diets [2-6], gut inflammation [7-10], and microbial dysbiosis [11-14].
Free fatty acid receptor 2 (
Our current study demonstrated that loss of
All protocols followed institutional guidelines for animal care dictated by the Medical College of Wisconsin Animal Care and Use Committee (AUA2430). Breeding pairs of the WT and
Human colorectal cancer cells HT29 and SW480 were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) in April 2016 and were cultured as recommended by ATCC.
Specimen preparation and extraction, mass spectrometer platforms and setting, and data analysis were conducted by Metabolon, Inc. (Morrisville, NC, USA) [30-32] according to the previous description [26,27]. Briefly, samples were prepared using an automated MicroLab STAR® system (Reno, NV, USA). Homogenized mucosa samples were extracted using 5 µL of methanol per mg tissue, and the plasma samples were extracted using 5 µL of methanol per mL tissue. Samples were characterized using the ultra-high-performance-liquid chromatography/tandem mass spectrometry (UHPLC-MS/MS) in the negative ion mode, the UHPLC-MS/MS in the positive ion mode, and the gas chromatography-mass spectrometry (GC-MS) after sialylation. Chemical entities were identified by comparing them to the metabolomic library of purified standards based on chromatographic properties and mass spectra.
Cecal feces were collected from a subgroup of the WT mice (n = 5),
The PCR products were quantified by Picogreen (P11496; Thermo Fisher Scientific, Waltham, MA, USA). Two hundred and forty ng of the DNA was pooled for each sample and purified using UltraClean PCR Clean-Up kit (12500; Mo Bio Laboratories) according to the manufacturer’s instructions. Sequencing was conducted using a paired-end, 2 × 250-bp cycle run on an Illumina MiSeq sequencing system and MiSeq Reagent Kit version 2 (500 Cycle) chemistry. Illumina BaseSpace’s 16s Metagenomics App was used to analyze the results.
To provide an even level of coverage for clustering and statistical comparisons, raw taxonomic counts were subsampled to 13,995 sequences per sample and aggregated at phylum through genus levels using QIIME . Differential abundance analysis comparing the WT,
Protein lysates of the human colorectal cancer cell lines were used for immunoblotting analysis.
Data were expressed as mean ± SEM. One-way ANOVA was employed in R version 2.14.2  to identify statistically significant metabolite differences across genotypes. Standard statistical analyses are performed in ArrayStudio on log transformed data. A
To determine the effects of
Fatty acids are oxidized in the mitochondria to generate energy and intermediates for cell proliferation. We observed significantly decreased fatty acid levels, including the medium-chain fatty acids, long-chain fatty acids, and polyunsaturated fatty acids in both the
Primary bile acids are synthesized by cholesterol catabolism in the liver and subsequently conjugated . In the intestine, intestinal bacteria could deconjugate a significant portion of the primary bile acids, and structurally modify them into the secondary bile acids, which have been shown to promote colon carcinogenesis . We observed significantly increased levels of both the primary and secondary bile acids in colonic mucosa in the
After observing significant levels of the carnitine-conjugated long-chain fatty acids in the
Evidence has been accumulated to imply the interplay between gut dysbiosis and colorectal cancer . In order to investigate the effects of
Our previous studies and those of other groups have shown that the expression of
Previously we observed significantly decreased fatty acid levels in the colonic mucosa of
Enhanced fatty acid β-oxidation has been reported in colon cancer patients [42,43]. Our study used human colon cancer cell lines to investigate if the functional
CPT2 has been shown to be over-expressed in primary prostate cancer , and knocking-down of CPT2 inhibited the tumor growth in triple-negative breast cancer . Thus, our findings on increased CPT2 expression in
HADHA has also been reported to be decreased in breast cancer  and clear cell renal cell carcinoma . However, we observed increased expression of HADHA in the
A strong link between microbial dysbiosis and colon cancer has been intensively explored. However, due to the complexity of the gut microbiome, the underlying mechanisms remain unclear. Our current study demonstrated that loss of
We previously reported that the cAMP-protein kinase A (PKA)-cAMP Response Element-Binding Protein (CREB) pathway, downstream of
In summary, we validated Ffar2 as a tumor suppressor
This work was supported by NIH grants CA148818 and USDA/NIFA 2020-67017-30843 (to L.-S. Wang), and CA185301, AI129582, and NS106170 (to J. Yu).
No potential conflicts of interest were disclosed.
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