p53 protein, activated and stabilized by posttranslational modifications, performs its major functions by inducing DNA repair, cell-cycle arrest, or apoptosis through transcriptional activation. Here, we determined the ability of p53 protein stabilized via proteasome inhibition to perform similar functions as p53 induced by stresses such as DNA damage. Treating mice with the proteasome inhibitor bortezomib stabilized p53 in stem/progenitor cells of the intestine and stomach, in other proliferating tissues, and in intestinal tumors. Robust basal p53 mRNA levels were observed in the same compartments where p53 was stabilized. Spatial activation of p53 target genes in response to bortezomib in the small intestine demonstrated that CDKN1A and BAX were upregulated in the proliferative crypts but not in the differentiated villi of the small intestine; PUMA was specifically activated at the crypt base of p53 wild-type mice. Thus, cellular context determines the p53 transcriptional target selection. p53dependent apoptosis was induced in Lgr5-expressing stem cells of the small intestine and high p53 transcriptional activity and apoptosis was induced in intestinal adenomas and in xenograft tumors. Bortezomib inhibited the growth of intestinal adenomas and xenograft tumors with wild-type p53, indicating the importance of p53 in the response to proteasome inhibitors in tissue homeostasis and in cancer therapy. Significance: These findings show that bortezomib is less active in p53-defective tumors, yet its success in treating multiple myeloma suggests its use can be extended to p53proficient solid tumors.

BackgroundDifferentiating between malignant and normal cells within tissue samples is vital for molecular profiling of cancer using advances in genomics and transcriptomics. Cell-surface markers of tumour–normal discrimination have additional value in terms of translatability to diagnostic and therapeutic strategies. In gastric cancer (GC), previous studies have identified individual genes or proteins that are upregulated in cancer. However, a systematic analysis of cell-surface markers and development of a composite panel involving multiple candidates to differentiate tumour from normal has not been previously reported.MethodsWhole transcriptome sequencing (WTS) of GC and matched normal samples from the Singapore Gastric Cancer Consortium (SGCC) was used as a discovery cohort to identify upregulated putative cell-surface proteins. Matched WTS data from the The Cancer Genome Atlas (TCGA) was used as a validation cohort. Promising candidates from this analysis were validated orthogonally using multispectral immunohistochemistry (mIHC) with automated quantitative analysis using the Vectra platform. mIHC was performed on a tissue microarray containing matched normal, marginal and tumour tissues. The receiver-operating characteristic (ROC) curves were analysed to identify markers with the highest diagnostic validity independently and in combination.ResultsAnalysis of putative membrane protein transcripts from the SGCC discovery cohort WTS data (n=15 matched tumour and normal pairs) identified several differentially and highly expressed candidates in tumour compared with normal tissues. After validation with TCGA data (n=29 matched tumour and normal pairs), the following proteins were selected for mIHC analysis: CEACAM5, CEACAM6, CLDN4, CLDN7, and EpCAM. These were compared with established glycoprotein markers in GC, namely CA19-9 and CA72-4. Individual ROC curves yielded the best performance for CEACAM5 (area under the ROC curve (AUC)=0.80), CEACAM6 (AUC=0.82), EpCAM (AUC=0.83), and CA72-4 (AUC=0.76). Combined multiplexed imaging of these four markers revealed improved specificity and sensitivity for detection of tumour from normal tissue (AUC of 4-plex=0.91).ConclusionCEAMCAM5, CEACAM6, EpCAM, and CA72-4 form a versatile set of markers for robust discrimination of GC from adjacent normal tissue. As cell-surface markers, they are compatible with both IHC and live imaging approaches. These candidates may be exploited to improve automated identification of tumour tissue in GC.

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