Cancer relapse occurs with substantial frequency even after treatment with curative intent. Here we studied drug-tolerant colonies (DTCs), which are subpopulations of cancer cells that survive in the presence of drugs. Proteomic characterization of DTCs identified stemness- and epithelial-dominant subpopulations, but functional screening suggested that DTC formation was regulated at the transcriptional level independent from protein expression patterns. We consistently found that α-amanitin, an RNA polymerase II (RNAPII) inhibitor, effectively inhibited DTCs by suppressing TAF15 expression, which binds to RNA to modulate transcription and RNA processing. Sequential administration of α-amanitin and cisplatin extended overall survival in a cancer-relapse mouse model, namely peritonitis carcinomatosa. Therefore, post-treatment cancer relapse may occur through non-distinct subpopulations and may be effectively prevented by α-amanitin to disrupt transcriptional machinery, including TAF15.

Large-capacity forceps performed better than standard forceps in terms of size, adequacy of the sample, submucosal sampling rate, and detection of neoplasia.

BackgroundThe binding of EGFR and its ligands leads to autophosphorylation of receptor tyrosine kinase as well as subsequent activation of signal transduction pathways that are involved in regulating cellular proliferation, differentiation, and survival. An EGFR inhibitor, cetuximab binds to EGFR and consequently blocks a variety of cellular processes. KRAS/BRAF mutations are known to be associated with a low response rate to cetuximab. In the present study, to clarify the anti-tumor mechanisms of cetuximab, we evaluated the KRAS/BRAF status, phosphorylation level of the EGFR pathway, and the tumor suppression effect in vivo, using a human colon cancer cell line HT29, which exhibited the highest EGFR expression in response to the cetuximab therapy among the 6 colorectal cancer cell lines tested.FindingsThe conventional growth suppression assay did not work efficiently with cetuximab. EGF, TGF-α, and IGF activated the EGFR/MAPK cell signaling pathway by initiating the phosphorylation of EGFR. Cetuximab partially inhibited the EGFR/MAPK pathway induced by EGF, TGF-α, and IGF. However, cetuximab exposure induced the EGFR, MEK, and ERK1/2 phosphorylation by itself. Mouse xenograft tumor growth was significantly inhibited by cetuximab and both cetuximab-treated and -untreated xenograft specimens exhibited phosphorylations of the EGFR pathway proteins.ConclusionsWe have confirmed that cetuximab inhibited the EGFR/MAPK pathway and reduced tumor growth in the xenografts while the remaining tumor showed EGFR pathway activation. These results suggest that: ( i ) The effect of cetuximab in growth signaling is not sufficient to induce complete growth suppression in vitro; ( ii ) time-course monitoring may be necessary to evaluate the effect of cetuximab because EGFR signaling is transmitted in a minute order; and ( iii ) cetuximab treatment may have cells acquired resistant selectively survived in the heterogeneous cancer population.

To confirm the clinical significance of NF-κB and JNK protein expression from experimentally identified candidates for predicting prognosis for patients with 5-FU treatment, we evaluated the protein expression of surgically removed specimens. A total of 79 specimens were obtained from 30 gastric and 49 colorectal cancer patients who underwent R0 resection followed by postoperative 5-FU based adjuvant chemotherapy. Immunohistochemical examinations of NF-κB and JNK on tissue microarrays (TMAs) revealed that significantly shorter time-to-relapse (TTR) in both NF-κB(+) and JNK(−) subgroups in both gastric (NF-κB(+), p = 0.0002, HR11.7. 95%CI3 3.2–43.4; JNK(−), p = 0.0302, HR4.4, 95%CI 1.2–16.6) and colon (NF-κB(+), p = 0.0038, HR36.9, 95%CI 3.2–426.0; JNK(−), p = 0.0098, HR3.2, 95%CI 1.3–7.7) cancers. These protein expression patterns also show strong discriminately power in gastric cancer patients for overall survival rate, suggesting a potential utility as prognostic or chemosensitivity markers. Baseline expression of these proteins using gastric cancer cell lines demonstrated the reciprocal patterns between NF-κB and JNK, while 5-FU exposure of these cell lines only induced NF-κB, suggesting that NF-κB plays a dominant role in the response to 5-FU. Subsequent siRNA experiments confirmed that gene knockdown of NF-κB increased 5-FU-specific sensitivity, whereas that of JNK did not affect the chemosensitivity. These results suggest that the expression of these proteins may aid in the decisions involved with adjuvant chemotherapy for gastrointestinal tract cancers.

BackgroundThe use of standard chemotherapy regimens has changed the application of chemosensitivity tests from all chemotherapy-eligible patients to those who have failed standard chemotherapy, which includes patients with highly advanced, relapsed, or chemoresistant tumors.MethodsWe evaluated a total of 43 advanced primary and relapsed gastric cancers for chemosensitivity based on drug dose response curves to improve the objectivity and quality of quantitative measurements. The dose response curves were classified based on seven expected patterns. Instead of a binary chemosensitivity evaluation, we ranked drug sensitivity according to curve shapes and comparison with the peak plasma concentration (ppc) of each drug.ResultsA total of 193 dose response curves were obtained. The overall informative rate was 67.4%, and 85.3% for cases that had a sufficient number of cells. Paclitaxel (PXL)and docetaxel tended to show a higher rank, while cisplatin (CIS) and 5-fluorouracil (5-FU) tended to show resistance, particularly among the 20 cases (46.5%) that had recurrent disease after receiving chemotherapy with CIS and S-1 (5-FU). As such, we speculate that the resistant pattern of the chemosensitivity test suggests that cells with acquired drug resistance were selected by chemotherapy. Indeed, we observed a change in the chemosensitivity pattern of a sample before and after chemotherapy in terms of PXL sensitivity, which was used after primary chemotherapy.ConclusionsThese results suggest that: (i) the dose–response pattern provides objective information for predicting chemosensitivity; and (ii) chemotherapy may select resistant cancer cell populations as a result of the therapy.