AIMTo explore the correlation of metabolomics profiles of gastric cancer (GC) with its chromosomal instability (CIN) status.METHODSNineteen GC patients were classified as CIN and non-CIN type by The Cancer Genome Atlas Research Group system, based on 409 oncogenes and tumor suppressor genes sequenced. The aqueous metabolites of the GC tumor and its surrounding adjacent healthy tissues were identified through liquid chromatography-mass spectrometry. Groups were compared by defining variable importance in projection score of > 1.2, a fold change value or its reciprocal of > 1.2, and a P value of < 0.05 as a significant difference.RESULTSIn total, twelve men and seven women were enrolled, with a median age of 66 years (range, 47-87 years). The numbers of gene alterations in the CIN GC group were significantly higher than those in the non-CIN GC (32-218 vs 2-17; P < 0.0005). Compared with the adjacent healthy tissues, GC tumors demonstrated significantly higher aspartic acid, citicoline, glutamic acid, oxidized glutathione, succinyladenosine, and uridine diphosphate-N-acetylglucosamine levels, but significantly lower butyrylcarnitine, glutathione hydroxyhexanoycarnitine, inosinic acid, isovalerylcarnitine, and threonine levels (all P < 0.05). CIN tumors contained significantly higher phosphocholine and uridine 5’-monophosphate levels but significantly lower beta-citryl-L-glutamic acid levels than did non-CIN tumors (all P < 0.05). CIN GC tumors demonstrated additional altered pathways involving alanine, aspartate, and glutamate metabolism, glyoxylate and dicarboxylate metabolism, histidine metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis.CONCLUSIONMetabolomic profiles of GC tumors and the adjacent healthy tissue are distinct, and the CIN status is associated with downstream metabolic alterations in GC.

Purpose This study aimed to develop and demonstrate the in vivo feasibility of a 3D stack‐of‐spiral balanced steady‐state free precession(3D‐bSSFP) urea sequence, interleaved with a metabolite‐specific gradient echo (GRE) sequence for pyruvate and metabolic products, for improving the SNR and spatial resolution of the first hyperpolarized 13C‐MRI human study with injection of co‐hyperpolarized [1‐13C]pyruvate and [13C,15N2]urea. Methods A metabolite‐specific bSSFP urea imaging sequence was designed using a urea‐specific excitation pulse, optimized TR, and 3D stack‐of‐spiral readouts. Simulations and phantom studies were performed to validate the spectral response of the sequence. The image quality of urea data acquired by the 3D‐bSSFP sequence and the 2D‐GRE sequence was evaluated with 2 identical injections of co‐hyperpolarized [1‐13C]pyruvate and [13C,15N2]urea formula in a rat. Subsequently, the feasibility of the acquisition strategy was validated in a prostate cancer patient. Results Simulations and phantom studies demonstrated that 3D‐bSSFP sequence achieved urea‐only excitation, while minimally perturbing other metabolites (<1%). An animal study demonstrated that compared to GRE, bSSFP sequence provided an ∼2.5‐fold improvement in SNR without perturbing urea or pyruvate kinetics, and bSSFP approach with a shorter spiral readout reduced blurring artifacts caused by J‐coupling of [13C,15N2]urea. The human study demonstrated the in vivo feasibility and data quality of the acquisition strategy. Conclusion The 3D‐bSSFP urea sequence with a stack‐of‐spiral acquisition demonstrated significantly increased SNR and image quality for [13C,15N2]urea in co‐hyperpolarized [1‐13C]pyruvate and [13C,15N2]urea imaging studies. This work lays the foundation for future human studies to achieve high‐quality and high‐SNR metabolism and perfusion images.

Contrast extravasation on CT, high volume RBC transfusions and ISS ≥ 16 can help us to select pelvic fracture patients for angiography more precisely.