Induction of Gastric Cancer by Successive Oncogenic Activation in the Corpus.

BACKGROUND & AIMS: Metaplasia and dysplasia in the corpus are reportedly derived from de-differentiation of chief cells. However, the cellular origin of metaplasia and cancer remained uncertain. Therefore, we investigated whether pepsinogen C (PGC) transcript-expressing cells represent the cellular origin of metaplasia and cancer using a novel Pgc-specific CreERT2 recombinase mouse model. METHODS: We generated a Pgc-mCherry-IRES-CreERT2 (Pgc-CreERT2) knock-in mouse model. Pgc-CreERT2/+ and Rosa-EYFP mice were crossed to generate Pgc-CreERT2/Rosa-EYFP (Pgc-CreERT2/YFP) mice. Gastric tissues were collected, followed by lineage-tracing experiments and histologic and immunofluorescence staining. We further established Pgc-CreERT2;KrasG12D/+ mice and investigated whether PGC transcript-expressing cells are responsible for the precancerous state in gastric glands. To investigate cancer development from PGC transcript-expressing cells with activated Kras, inactivated Apc, and Trp53 signaling pathways, we crossed Pgc-CreERT2/+ mice with conditional KrasG12D, Apcflox, Trp53flox mice. RESULTS: Expectedly, mCherry mainly labeled chief cells in the Pgc-CreERT2 mice. However, mCherry was also detected throughout the neck cell and isthmal stem/progenitor regions, albeit at lower levels. In the Pgc-CreERT2;KrasG12D/+ mice, PGC transcript-expressing cells with KrasG12D/+ mutation presented pseudopyloric metaplasia. The early induction of proliferation at the isthmus may reflect the ability of isthmal progenitors to react rapidly to Pgc-driven KrasG12D/+ oncogenic mutation. Furthermore, Pgc-CreERT2;KrasG12D/+;Apcflox/flox mice presented intramucosal dysplasia/carcinoma and Pgc-CreERT2;KrasG12D/+;Apcflox/flox;Trp53flox/flox mice presented invasive and metastatic gastric carcinoma. CONCLUSIONS: The Pgc-CreERT2 knock-in mouse is an invaluable tool to study the effects of successive oncogenic activation in the mouse corpus. Time-course observations can be made regarding the responses of isthmal and chief cells to oncogenic insults. We can observe stomach-specific tumorigenesis from the beginning to metastatic development.

A Point Mutation R122C in RUNX3 Promotes the Expansion of Isthmus Stem Cells and Inhibits Their Differentiation in the Stomach.

BACKGROUND & AIMS: RUNX transcription factors play pivotal roles in embryonic development and neoplasia. We previously identified the single missense mutation R122C in RUNX3 from human gastric cancer. However, how RUNX3R122C mutation disrupts stem cell homeostasis and promotes gastric carcinogenesis remained unclear. METHODS: To understand the oncogenic nature of this mutation in vivo, we generated the RUNX3R122C knock-in mice. Stomach tissues were harvested, followed by histologic and immunofluorescence staining, organoid culture, flow cytometry to isolate gastric corpus isthmus and nonisthmus epithelial cells, and RNA extraction for transcriptomic analysis. RESULTS: The corpus tissue of RUNX3R122C/R122C homozygous mice showed a precancerous phenotype such as spasmolytic polypeptide-expressing metaplasia. We observed mucous neck cell hyperplasia; massive reduction of pit, parietal, and chief cell populations; as well as a dramatic increase in the number of rapidly proliferating isthmus stem/progenitor cells in the corpus of RUNX3R122C/R122C mice. Transcriptomic analyses of the isolated epithelial cells showed that the cell-cycle-related MYC target gene signature was enriched in the corpus epithelial cells of RUNX3R122C/R122C mice compared with the wild-type corpus. Mechanistically, RUNX3R122C mutant protein disrupted the regulation of the restriction point where cells decide to enter either a proliferative or quiescent state, thereby driving stem cell expansion and limiting the ability of cells to terminally differentiate. CONCLUSIONS: RUNX3R122C missense mutation is associated with the continuous cycling of isthmus stem/progenitor cells, maturation arrest, and development of a precancerous state. This work highlights the importance of RUNX3 in the prevention of metaplasia and gastric cancer.

Investigation on the potential of Mueller matrix imaging for digital staining.

Digital staining based on Mueller matrix measurements and their derivatives was investigated. Mueller matrix imaging was performed at the microscopic level on gastric tissue sections. Full Mueller matrices (4 × 4) were reconstructed using recorded images, followed by the extraction of polarization parameters. The most effective parameters and their combinations were extracted from Mueller matrix elements, principal component scores and polarization parameters respectively to classify samples into three categories - i.e. cancer, dysplasia and intestinal metaplasia/normal glands for various regions of interest sizes. It was observed that two-step classification yielded higher classification accuracy than the traditional one-step classification and that pixel classification based on Mueller matrix elements yielded higher accuracy than that based on polarization parameters and derived principal components. Moreover, Mueller matrix images with a lower spatial resolution generated higher classification accuracy but those with a higher spatial resolution revealed more morphological details.ns. The original stained image (top) and the digital staining image (bottom).

Real-time Raman spectroscopy for in vivo, online gastric cancer diagnosis during clinical endoscopic examination.

Optical spectroscopic techniques including reflectance, fluorescence and Raman spectroscopy have shown promising potential for in vivo precancer and cancer diagnostics in a variety of organs. However, data-analysis has mostly been limited to post-processing and off-line algorithm development. In this work, we develop a fully automated on-line Raman spectral diagnostics framework integrated with a multimodal image-guided Raman technique for real-time in vivo cancer detection at endoscopy. A total of 2748 in vivo gastric tissue spectra (2465 normal and 283 cancer) were acquired from 305 patients recruited to construct a spectral database for diagnostic algorithms development. The novel diagnostic scheme developed implements on-line preprocessing, outlier detection based on principal component analysis statistics (i.e., Hotelling's T2 and Q-residuals) for tissue Raman spectra verification as well as for organ specific probabilistic diagnostics using different diagnostic algorithms. Free-running optical diagnosis and processing time of < 0.5 s can be achieved, which is critical to realizing real-time in vivo tissue diagnostics during clinical endoscopic examination. The optimized partial least squares-discriminant analysis (PLS-DA) models based on the randomly resampled training database (80% for learning and 20% for testing) provide the diagnostic accuracy of 85.6% [95% confidence interval (CI): 82.9% to 88.2%] [sensitivity of 80.5% (95% CI: 71.4% to 89.6%) and specificity of 86.2% (95% CI: 83.6% to 88.7%)] for the detection of gastric cancer. The PLS-DA algorithms are further applied prospectively on 10 gastric patients at gastroscopy, achieving the predictive accuracy of 80.0% (60/75) [sensitivity of 90.0% (27/30) and specificity of 73.3% (33/45)] for in vivo diagnosis of gastric cancer. The receiver operating characteristics curves further confirmed the efficacy of Raman endoscopy together with PLS-DA algorithms for in vivo prospective diagnosis of gastric cancer. This work successfully moves biomedical Raman spectroscopic technique into real-time, on-line clinical cancer diagnosis, especially in routine endoscopic diagnostic applications.