• Breast cancer
• Endometrial protection
• Rapamycin
• Tamoxifen
• mTOR

• Humans
• Female
• Tamoxifen/adverse effects
• Tamoxifen/pharmacology
• Sirolimus/pharmacology
• Breast Neoplasms/drug therapy
• Breast Neoplasms/pathology
• Cell Proliferation/drug effects
• Endometrium/drug effects
• Endometrium/pathology
• Endometrium/metabolism
• Endometrium/cytology
• Apoptosis/drug effects
• TOR Serine-Threonine Kinases/metabolism
• Pilot Projects
• Antineoplastic Agents, Hormonal/adverse effects
• Signal Transduction/drug effects
• Cell Cycle/drug effects
• Adult
• Stromal Cells/drug effects
• Stromal Cells/metabolism

• JP21K09493 Japan Society for the Promotion of Science

• adenomyosis
• endometriosis
• everolimus
• fertility preservation
• hormonal resistance
• mTOR inhibitor
• rapamycin
• sirolimus

• Humans
• Female
• Endometriosis/drug therapy
• Endometriosis/metabolism
• TOR Serine-Threonine Kinases/antagonists & inhibitors
• TOR Serine-Threonine Kinases/metabolism
• MTOR Inhibitors/therapeutic use
• MTOR Inhibitors/pharmacology
• Signal Transduction/drug effects
• Animals
• Pregnancy

• Japan Society for the Promotion of Science
• 21K09493 JSPS KAKENHI

• Colon cancer
• Diet
• Gastrointestinal microbiome
• Transplant models

• C‑X‑C chemokine receptor type 4
• everolimus
• human epidermal growth factor receptor 3
• mammalian target of rapamycin
• metastasis
• triple‑negative breast cancer

• Humans
• Animals
• Mice
• Triple Negative Breast Neoplasms/genetics
• Proto-Oncogene Proteins c-akt/metabolism
• Everolimus/pharmacology
• Everolimus/therapeutic use
• Cell Proliferation
• Cell Line, Tumor
• TOR Serine-Threonine Kinases/metabolism
• Sirolimus/pharmacology
• Cell Movement
• Mammals/metabolism
• Receptors, CXCR4/genetics

• Cancer
• Microfluidics
• Xenograft
• organ-on-chip

• Animals
• Biomimetics/methods
• Cell Line, Tumor
• Disease Models, Animal
• Drug Discovery/methods
• Heterografts
• Humans
• Lab-On-A-Chip Devices
• Mice
• Microfluidic Analytical Techniques
• Neoplasms/drug therapy
• Neoplasms/pathology
• Xenograft Model Antitumor Assays

• colorectal cancer
• mouse model
• orthotopic model

The mammalian or mechanistic target of rapamycin (mTOR) pathway plays a crucial role in regulation of cell survival, metabolism, growth and protein synthesis in response to upstream signals in both normal physiological and pathological conditions, especially in cancer. Aberrant mTOR signaling resulting from genetic alterations from different levels of the signal cascade is commonly observed in various types of cancers. Upon hyperactivation, mTOR signaling promotes cell proliferation and metabolism that contribute to tumor initiation and progression. In addition, mTOR also negatively regulates autophagy via different ways. We discuss mTOR signaling and its key upstream and downstream factors, the specific genetic changes in the mTOR pathway and the inhibitors of mTOR applied as therapeutic strategies in eight solid tumors. Although monotherapy and combination therapy with mTOR inhibitors have been extensively applied in preclinical and clinical trials in various cancer types, innovative therapies with better efficacy and less drug resistance are still in great need, and new biomarkers and deep sequencing technologies will facilitate these mTOR targeting drugs benefit the cancer patients in personalized therapy.

• PI3K
• cancer
• inhibitor
• mTOR
• therapy

• Animals
• Antineoplastic Combined Chemotherapy Protocols/adverse effects
• Antineoplastic Combined Chemotherapy Protocols/therapeutic use
• Biomarkers
• Clinical Trials as Topic
• Humans
• Molecular Targeted Therapy
• Neoplasms/drug therapy
• Neoplasms/metabolism
• Neoplasms/pathology
• Protein Kinase Inhibitors/pharmacology
• Protein Kinase Inhibitors/therapeutic use
• Signal Transduction/drug effects
• TOR Serine-Threonine Kinases/antagonists & inhibitors
• TOR Serine-Threonine Kinases/metabolism
• Treatment Outcome

• Colorectal cancer
• Combinatorial
• Irinotecan
• PARP
• Rucaparib
• Synergy

The Aurora kinases are a family of serine/threonine kinases comprised of Aurora A, B, and C which execute critical steps in mitotic and meiotic progression. Alisertib (MLN8237) is an investigational Aurora A selective inhibitor that has demonstrated activity against a wide variety of tumor types in vitro and in vivo, including CRC.

CRC cell lines demonstrated varying sensitivity to alisertib with IC₅₀ values ranging from 0.06 to > 5 umol/L. Following exposure to alisertib we observed a decrease in pAurora A, B and C in four CRC cell lines. We also observed an increase in p53 and p21 in a sensitive p53 wildtype cell line in contrast to the p53 mutant cell line or the resistant cell lines. The addition of alisertib to standard CRC treatments demonstrated improvement over single agent arms; however, the benefit was largely less than additive, but not antagonistic.

Forty-seven CRC cell lines were exposed to alisertib and IC₅₀s were calculated. Twenty-one PDX models were treated with alisertib and the Tumor Growth Inhibition Index was assessed. Additionally, 5 KRAS wildtype and mutant PDX models were treated with alisertib as single agent or in combination with cetuximab or irinotecan, respectively.

Alisertib demonstrated anti-proliferative effects against CRC cell lines and PDX models. Our data suggest that the addition of alisertib to standard therapies in colorectal cancer if pursued clinically, will require further investigation of patient selection strategies and these combinations may facilitate future clinical studies.

• aurora kinase a
• colorectal cancer

We aimed to establish a prospectively enrolled colorectal cancer (CRC) cohort for targeted sequencing of primary tumors from CRC patients. In parallel, we established collateral PDC models from the matched primary tumor tissues, which may be later used as preclinical models for genome-directed targeted therapy experiments.

In all, we identified 27 SNVs in the 6 genes such as PIK3CA (N = 16), BRAF (N = 6), NRAS (N = 2), and CTNNB1 (N = 1), PTEN (N = 1), and ERBB2 (N = 1). RET-NCOA4 translocation was observed in one out of 105 patients (0.9%). PDC models were successfully established from 62 (55.4%) of the 112 samples. To confirm the genomic features of various tumor cells, we compared variant allele frequency results of the primary tumor and progeny PDCs. The Pearson correlation coefficient between the variants from primary tumor cells and PDCs was 0.881.

Between April 2014 and June 2015, 112 patients with CRC who underwent resection of the primary tumor were enrolled in the SMC Oncology Biomarker study. The PDC culture protocol was performed for all eligible patients. All of the primary tumors from the 112 patients who provided written informed consent were genomically sequenced with targeted sequencing. In parallel, PDC establishment was attempted for all sequenced tumors.

We have prospectively sequenced a CRC cohort of 105 patients and successfully established 62 PDC in parallel. Each genomically characterized PDCs can be used as a preclinical model especially in rare genomic alteration event.

• colorectal cancer
• patient-derived cell
• somatic mutation

• Everolimus
• Hepatocellular carcinoma
• Sirtuin 1
• TOR serine-threonine kinases
• Autophagy

• PEPCK-M
• glycolysis
• mTOR
• mitochondrial OXPHOS
• pancreatic neuroendocrine tumor

• acetaldehyde dehydrogenase
• alcohol
• colorectal cancer
• exposome
• metabolomics
• microbiome

• Animals
• Antipsychotic Agents/therapeutic use
• Behavior, Animal/drug effects
• Benserazide/pharmacology
• Disease Models, Animal
• Dose-Response Relationship, Drug
• Drug Combinations/pharmacology
• Drug Evaluation, Preclinical
• Hydrazines/pharmacology
• Levodopa/pharmacology
• Male
• Psychotropic Drugs/therapeutic use
• Rats
• Stereotyped Behavior/drug effects

• R29 EY011490 NEI NIH HHS
• R01 EY011490 NEI NIH HHS
• R24 AA022057 NIAAA NIH HHS
• U01 AA021724 NIAAA NIH HHS
• R01 AA021724 NIAAA NIH HHS

Heat shock protein 90 (HSP90) stabilizes numerous oncoproteins and, therefore, its inhibition has emerged as a promising antineoplastic strategy for diverse malignancies. In this study, we determined the therapeutic effects and mechanisms of action of a specific HSP90 inhibitor, 17-dimethylamino-ethylamino-17-demethoxygeldanamycin (17-DMAG), in gastric cancer cell lines (AGS, SNU-1, and KATO-III), patient-derived tissues, and a mouse xenograft model. 17-DMAG exerted anticancer effects against gastric cancer cells, manifested by significantly decreased proliferation rates (P < 0.05) and increased expression of apoptotic markers. Flow cytometry using dichlorofluorescein (DCF) diacetate revealed that 17-DMAG dose-dependently increases reactive oxygen species (ROS) levels in gastric cancer cells. Inhibition of ROS by N-acetyl-L-cysteine (NAC) abrogated the proapoptotic effects of 17-DMAG, as demonstrated by the decreased expression of proapoptotic proteins. In addition, 17-DMAG dose- and time-dependently reduced the expression of antioxidants such as catalase and glutathione peroxidase (GPx). Moreover, 17-DMAG reduced the expression of nuclear respiratory factor (NRF)-1 and NRF-2, and prevented them from migrating from the cytoplasm to the nucleus dose-dependently. Finally, in a nude mouse xenograft model, the shrinkage of tumors was more prominent in mice treated with 17-DMAG than in control mice (P < 0.05). Taken altogether, our results suggest that 17-DMAG exerts potent antineoplastic activity against gastric cancer cells primarily by promoting ROS generation and suppressing antioxidant enzyme activities.

• 17-DMAG
• HSP90 inhibitor
• antioxidant enzymes
• reactive oxygen species
• stomach cancer

Pediatric high grade glioma (pHGGs), including sus-tentorial and diffuse intrinsic pontine gliomas, are known to have a very dismal prognosis. For instance, even an increased knowledge on molecular biology driving this brain tumor entity, there is no treatment able to cure those patients. Therefore, we were focusing on a translational pathway able to increase the cell resistance to treatment and to reprogram metabolically tumor cells, which are, then, adapting easily to a hypoxic microenvironment. To establish, the crucial role of the hypoxic pathways in pHGGs, we, first, assessed their protein and transcriptomic deregulations in a pediatric cohort of pHGGs and in pHGG's cell lines, cultured in both normoxic and hypoxic conditions. Secondly, based on the concept of a bi-therapy targeting in pHGGs mTORC1 (rapamycin) and HIF-1α (irinotecan), we hypothesized that the balanced expressions between RAS/ERK, PI3K/AKT and HIF-1α/HIF-2α/MYC proteins or genes may provide a modulation of the cell response to this double targeting. Finally, we could evidence three protein, genomic and metabolomic profiles of response to rapamycin combined with irinotecan. The pattern of highly sensitive cells to mTOR/HIF-1α targeting was linked to a MYC/ERK/HIF-1α over-expression and the cell resistance to a major hyper-expression of HIF-2α.

• HIF1alpha
• high grade glioma
• mTor
• pediatric
• targets

• NMR
• metabolomics
• osteoblasts
• osteosarcoma
• palladium anticancer drugs

• Bliss Independence
• Combination therapy
• Drug–drug interaction
• Loewe Additivity
• Optimal concentration

• clinical study
• rhabdomyosarcoma
• treatment

• Chemotherapy
• Colorectal cancer
• Irinotecan
• Obesity
• Pharmacokinetics
• SN-38
• Ugt1a1

Sorafenib-everolimus combination therapy may be more effective than sorafenib monotherapy for hepatocellular carcinoma (HCC). To better understand this effect, we comparatively profiled the metabolite composition of HepG2 cells treated with sorafenib, everolimus, and sorafenib-everolimus combination therapy.

A 2D HRMAS ¹H-NMR metabolomic approach was applied to identify the key differential metabolites in 3 experimental groups: sorafenib (5 μM), everolimus (5 μM), and combination therapy (5 μM sorafenib +5 μM everolimus). MetaboAnalyst 3.0 was used to perform pathway analysis.

All OPLS-DA models displayed good separation between experimental groups, high-quality goodness of fit (R2), and high-quality goodness of predication (Q2). Sorafenib and everolimus have differential effects with respect to amino acid, methane, pyruvate, pyrimidine, aminoacyl-tRNA biosynthesis, and glycerophospholipid metabolism. The addition of everolimus to sorafenib resulted in differential effects with respect to pyruvate, amino acid, methane, glyoxylate and dicarboxylate, glycolysis or gluconeogenesis, glycerophospholipid, and purine metabolism.

Sorafenib and everolimus have differential effects on HepG2 cells. Sorafenib preferentially affects glycerophospholipid and purine metabolism, while the addition of everolimus preferentially affects pyruvate, amino acid, and glucose metabolism. This phenomenon may explain (in part) the synergistic effects of sorafenib-everolimus combination therapy observed in vivo.

Aurora A kinase and MEK inhibitors induce different, and potentially complementary, effects on the cell cycle of malignant cells, suggesting a rational basis for utilizing these agents in combination. In this work, the combination of an Aurora A kinase and MEK inhibitor was evaluated in pre-clinical colorectal cancer models, with a focus on identifying a subpopulation in which it might be most effective. Increased synergistic activity of the drug combination was identified in colorectal cancer cell lines with concomitant KRAS and PIK3CA mutations. Anti-proliferative effects were observed upon treatment of these double-mutant cell lines with the drug combination, and tumor growth inhibition was observed in double-mutant human tumor xenografts, though effects were variable within this subset. Additional evaluation suggests that degree of G2/M delay and p53 mutation status affect apoptotic activity induced by combination therapy with an Aurora A kinase and MEK inhibitor in KRAS and PIK3CA mutant colorectal cancer. Overall, in vitro and in vivo testing was unable to identify a subset of colorectal cancer that was consistently responsive to the combination of a MEK and Aurora A kinase inhibitor.

• Aurora A kinase
• KRAS mutation
• MEK
• PIK3CA
• alisertib
• colorectal cancer
• human tumor xenografts
• trametinib

Urothelial bladder carcinoma (UBC) is heterogeneous in its pathology and clinical behaviour. Evaluation of prognostic and predictive biomarkers is necessary, in order to produce personalised treatment options. The present study used immunohistochemistry to evaluate UBC sections containing tumour and non-tumour areas from 76 patients, for the detection of p-mTOR, CD31 and D2-40 (blood and lymphatic vessels identification, respectively). Of the non-tumour and tumour sections, 36 and 20% were scored positive for p-mTOR expression, respectively. Immunoexpression was observed in umbrella cells from non-tumour urothelium, in all cell layers from non-muscle-invasive (NMI) tumours (including expression in superficial cells), and in spots of cells from muscle-invasive (MI) tumours. Positive expression decreased from non-tumour to tumour urothelium, and from pT1/pTis to pT3/pT4 tumours; however, the few pT3/pT4 positive cases had worse survival rates, with 5-year disease-free survival being significantly lower. Angiogenesis occurrence was impaired in pT3/pT4 tumours that did not express p-mTOR. In conclusion, p-mTOR expression in non-tumour umbrella cells is likely a reflection of their metabolic plasticity, and extension to the inner layers of the urothelium in NMI tumours is consistent with an enhanced malignant potential. The expression in cell spots in a few MI tumours and absence of expression in the remaining tumours is intriguing and requires further research. Additional studies regarding the up- and downstream effectors of the mTOR pathway should be conducted.

• p-mTOR
• pattern of expression
• umbrella cells
• urothelial bladder cancer

• Chemotherapy
• Colorectal cancer
• Drug resistance
• Mechanistic target of rapamycin inhibitor
• Mechanistic target of rapamycin pathway

• Animals
• Anti-Inflammatory Agents, Non-Steroidal/therapeutic use
• Antineoplastic Agents/therapeutic use
• Autophagy
• Colorectal Neoplasms/drug therapy
• Colorectal Neoplasms/genetics
• Colorectal Neoplasms/metabolism
• Drug Resistance, Neoplasm
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic
• Gene Regulatory Networks
• Humans
• MAP Kinase Signaling System
• Metformin/therapeutic use
• Models, Biological
• Prognosis
• Signal Transduction
• Sirolimus/therapeutic use
• TOR Serine-Threonine Kinases/metabolism
• Tumor Suppressor Protein p53/metabolism
• Wnt Proteins/metabolism

Metabolomics is a relatively new technique that is gaining importance very rapidly. MRS-based metabolomics, in particular, is becoming a useful tool in the study of body fluids, tissue biopsies and whole organisms. Advances in analytical techniques and data analysis methods have opened a new opportunity for such technology to contribute in the field of diagnostics. In the MRS approach to the diagnosis of disease, it is important that the analysis utilizes all the essential information in the spectra, is robust, and is non-subjective. Although some of the data analytic methods widely used in chemical and biological sciences are sketched, a more extensive discussion is given of a 5-stage Statistical Classification Strategy. This proposes powerful feature selection methods, based on, for example, genetic algorithms and novel projection techniques. The applications of MRS-based metabolomics in breast cancer, prostate cancer, colorectal cancer, pancreatic cancer, hepatobiliary cancers, gastric cancer, and brain cancer have been reviewed. While the majority of these applications relate to body fluids and tissue biopsies, some in vivo applications have also been included. It should be emphasized that the number of subjects studied must be sufficiently large to ensure a robust diagnostic classification. Before MRS-based metabolomics can become a widely used clinical tool, however, certain challenges need to be overcome. These include manufacturing user-friendly commercial instruments with all the essential features, and educating physicians and medical technologists in the acquisition, analysis, and interpretation of metabolomics data.

• cancer
• classification
• diagnosis
• magnetic resonance spectroscopy
• metabolomics