Chemoprevention with low-dose aspirin, mesalazine, or both in patients with familial adenomatous polyposis without previous colectomy (J-FAPP Study IV): a multicentre, double-blind, randomised, two-by-two factorial design trial

Ishikawa, Hideki; Mutoh, Michihiro; Sato, Yasushi; Doyama, Hisashi; Tajika, Masahiro; Tanaka, Shinji; Horimatsu, Takahiro; Takeuchi, Yoji; Kashida, Hiroshi; Tashiro, Jun; Ezoe, Yasumasa; Nakajima, Takeshi; Ikematsu, Hiroaki; Hori, Shinichiro; Suzuki, Sadao; Otani, Takahiro; Takayama, Tetsuji; Ohda, Yoshio; Mure, Kanae; Wakabayashi, Keiji; Sakai, Toshiyuki

doi:10.1016/s2468-1253(21)00018-2

Cited by 55 publications

(65 citation statements)

References 23 publications

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“…Our studies proved that anti-HBV treatment can attenuate inflammation, decreased the risk of HCC occurrence, and prevent postoperative recurrence of HCC ( 93 , 95 ). Long-term use of non-steroidal anti-inflammatory drugs can also reduce the occurrence and recurrence of cancers ( 123 – 126 ). Targeting cancer stemness- and/or EMT-related signaling pathways might contribute to the eradication of malignant diseases ( 127 – 129 ).…”

Section: Discussionmentioning

confidence: 99%

Cancer Evo–Dev: A Theory of Inflammation-Induced Oncogenesis

Liu

Deng

et al. 2021

Front. Immunol.

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Chronic inflammation is a prerequisite for the development of cancers. Here, we present the framework of a novel theory termed as Cancer Evolution-Development (Cancer Evo-Dev) based on the current understanding of inflammation-related carcinogenesis, especially hepatocarcinogenesis induced by chronic infection with hepatitis B virus. The interaction between genetic predispositions and environmental exposures, such as viral infection, maintains chronic non-resolving inflammation. Pollution, metabolic syndrome, physical inactivity, ageing, and adverse psychosocial exposure also increase the risk of cancer via inducing chronic low-grade smoldering inflammation. Under the microenvironment of non-resolving inflammation, pro-inflammatory factors facilitate the generation of somatic mutations and viral mutations by inducing the imbalance between the mutagenic forces such as cytidine deaminases and mutation-correcting forces including uracil–DNA glycosylase. Most cells with somatic mutations and mutated viruses are eliminated in survival competition. Only a small percentage of mutated cells survive, adapt to the hostile environment, retro-differentiate, and function as cancer-initiating cells via altering signaling pathways. These cancer-initiating cells acquire stem-ness, reprogram metabolic patterns, and affect the microenvironment. The carcinogenic process follows the law of “mutation-selection-adaptation”. Chronic physical activity reduces the levels of inflammation via upregulating the activity and numbers of NK cells and lymphocytes and lengthening leukocyte telomere; downregulating proinflammatory cytokines including interleukin-6 and senescent lymphocytes especially in aged population. Anti-inflammation medication reduces the occurrence and recurrence of cancers. Targeting cancer stemness signaling pathways might lead to cancer eradication. Cancer Evo-Dev not only helps understand the mechanisms by which inflammation promotes the development of cancers, but also lays the foundation for effective prophylaxis and targeted therapy of various cancers.

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Section: Discussionmentioning

confidence: 99%

Cancer Evo–Dev: A Theory of Inflammation-Induced Oncogenesis

Liu

Deng

et al. 2021

Front. Immunol.

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“…Recently, Ishikawa et al (2021) performed a double-blind, placebo-controlled, multicenter trial in 104 patients (age: 16–70 years) with FAP for the effects of low-dose Aspirin (100 mg/day) and mesalazine (2 g/day) on the recurrence of colorectal polyps (J-FAPP Study IV). The primary endpoint was the incidence of colorectal polyps of at least 5 mm; treatment continued until 1 week before an 8-month colonoscopy.…”

Section: Colorectal Cancermentioning

confidence: 99%

Inflammation and Cancer: From the Development of Personalized Indicators to Novel Therapeutic Strategies

Ballerini¹,

Contursi

Bruno

et al. 2022

Front. Pharmacol.

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Colorectal (CRC) and hepatocellular carcinoma (HCC) are associated with chronic inflammation, which plays a role in tumor development and malignant progression. An unmet medical need in these settings is the availability of sensitive and specific noninvasive biomarkers. Their use will allow surveillance of high-risk populations, early detection, and monitoring of disease progression. Moreover, the characterization of specific fingerprints of patients with nonalcoholic fatty liver disease (NAFLD) without or with nonalcoholic steatohepatitis (NASH) at the early stages of liver fibrosis is necessary. Some lines of evidence show the contribution of platelets to intestinal and liver inflammation. Thus, low-dose Aspirin, an antiplatelet agent, reduces CRC and liver cancer incidence and mortality. Aspirin also produces antifibrotic effects in NAFLD. Activated platelets can trigger chronic inflammation and tissue fibrosis via the release of soluble mediators, such as thromboxane (TX) A2 and tumor growth factor (TGF)-β, and vesicles containing genetic material (including microRNA). These platelet-derived products contribute to cyclooxygenase (COX)-2 expression and prostaglandin (PG)E2 biosynthesis by tumor microenvironment cells, such as immune and endothelial cells and fibroblasts, alongside cancer cells. Enhanced COX-2-dependent PGE2 plays a crucial role in chronic inflammation and promotes tumor progression, angiogenesis, and metastasis. Antiplatelet agents can indirectly prevent the induction of COX-2 in target cells by inhibiting platelet activation. Differently, selective COX-2 inhibitors (coxibs) block the activity of COX-2 expressed in the tumor microenvironment and cancer cells. However, coxib chemopreventive effects are hampered by the interference with cardiovascular homeostasis via the coincident inhibition of vascular COX-2-dependent prostacyclin biosynthesis, resulting in enhanced risk of atherothrombosis. A strategy to improve anti-inflammatory agents’ use in cancer prevention could be to develop tissue-specific drug delivery systems. Platelet ability to interact with tumor cells and transfer their molecular cargo can be employed to design platelet-mediated drug delivery systems to enhance the efficacy and reduce toxicity associated with anti-inflammatory agents in these settings. Another peculiarity of platelets is their capability to uptake proteins and transcripts from the circulation. Thus, cancer patient platelets show specific proteomic and transcriptomic expression profiles that could be used as biomarkers for early cancer detection and disease monitoring.

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“…For example, ATC group A07 (Antidiarrheals) has relatively few approved drugs in total (Supplementary Figure 6), but DTI-Voodoo predicts several candidate targets from proteins with a PHD-type zinc finger domain (IPR001965). For example, the drug mesalazine, used to treat inflammatory bowel disease but with an apoptosis-inducing and chemopreventative effect in colon cancer (Bus et al, 1999;Ishikawa et al, 2021); DTI-Voodoo predicts mesalazine to interact with five proteins with PHDtype zinc finger domain: BRPF1, TRIM33, BAZ1A, RSF1, and DPF2. Overexpression of RSF1 is associated with poor prognosis in colorectal cancer, and knock-down of RSF1 leads to decrease of cell proliferation (Liu et al, 2012), indicating that, in addition to its antiinflammatory effects, mesalazine may act through inhibition of RSF1 in its chemopreventative effects on colon cancer.…”

Section: Pharmacological Noveltymentioning

confidence: 99%

DTI-Voodoo: machine learning over interaction networks and ontology-based background knowledge predicts drug–target interactions

Hinnerichs

Hoehndorf

2021

Bioinformatics

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Motivation In silico drug–target interaction (DTI) prediction is important for drug discovery and drug repurposing. Approaches to predict DTIs can proceed indirectly, top-down, using phenotypic effects of drugs to identify potential drug targets, or they can be direct, bottom-up and use molecular information to directly predict binding affinities. Both approaches can be combined with information about interaction networks. Results We developed DTI-Voodoo as a computational method that combines molecular features and ontology-encoded phenotypic effects of drugs with protein–protein interaction networks, and uses a graph convolutional neural network to predict DTIs. We demonstrate that drug effect features can exploit information in the interaction network whereas molecular features do not. DTI-Voodoo is designed to predict candidate drugs for a given protein; we use this formulation to show that common DTI datasets contain intrinsic biases with major effects on performance evaluation and comparison of DTI prediction methods. Using a modified evaluation scheme, we demonstrate that DTI-Voodoo improves significantly over state of the art DTI prediction methods. Availability DTI-Voodoo source code and data necessary to reproduce results are freely available at https://github.com/THinnerichs/DTI-VOODOO. Supplementary information Supplementary data are available at Bioinformatics online.

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Chemoprevention with low-dose aspirin, mesalazine, or both in patients with familial adenomatous polyposis without previous colectomy (J-FAPP Study IV): a multicentre, double-blind, randomised, two-by-two factorial design trial

Cited by 55 publications

References 23 publications

Cancer Evo–Dev: A Theory of Inflammation-Induced Oncogenesis

Cancer Evo–Dev: A Theory of Inflammation-Induced Oncogenesis

Inflammation and Cancer: From the Development of Personalized Indicators to Novel Therapeutic Strategies

DTI-Voodoo: machine learning over interaction networks and ontology-based background knowledge predicts drug–target interactions

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