Agreement between GLIM and PG-SGA for diagnosis of malnutrition depends on the screening tool used in GLIM.

BACKGROUND & AIM: The Global Leadership Initiative on Malnutrition (GLIM) has suggested a process for the diagnosis of malnutrition. The process consists of applying an existing screening tool for malnutrition screening, followed by malnutrition diagnostics, and finally categorization of malnutrition severity (moderate or severe) according to specific GLIM criteria. However, it is not known how well the GLIM process agrees with other diagnostic tools used in the current clinical practice. The aim of this study was to validate the GLIM process against the Patient Generated-Subjective Global Assessment (PG-SGA) when different screening tools were applied in the screening step of the GLIM process. METHODS: Colorectal cancer (CRC) patients from the ongoing CRC-NORDIET study were included. For the GLIM process, the patients were first screened for malnutrition using either 1) Nutritional risk screening, first 4 questions (NRS-2002-4Q), 2) Malnutrition Screening Tool (MST), 3) Malnutrition Universal Screening Tool (MUST) or 4) the PG-SGA short form (PG-SGA-SF). The GLIM malnutrition diagnosis was then based on combining the result from each of the screening methods with the etiological and phenotypic GLIM-criteria including weight loss, BMI and fat free mass. In parallel, the patients were diagnosed using the PG-SGA methodology categorizing the patients into either A: well nourished, B: moderately malnourished or C: severely malnourished. The four different GLIM based diagnoses were then validated against the diagnosis obtained by the PG-SGA tool. Sensitivity, specificity and positive predictive value (PPV) were calculated to evaluate validity. RESULTS: In total, 426 patients were included (mean age: 66, ±8 years) at a mean time of 166 (±56) days after surgery. The GLIM diagnosis based on the four different screening tools identified 10-24% of the patients to be malnourished, of which 3-8% were severely malnourished. The PG-SGA method categorized 15% as moderately malnourished (PG-SGA: category B) and no patients as severely malnourished (PG-SGA: category C). The agreement between the PG-SGA and GLIM process was in general low, but differed according to the tools: PG-SGA SF (sensitivity 47%, PPV 71%), MST (sensitivity 56%, PPV 47%), NRS-2002-4Q (sensitivity 63%, PPV 53%) and MUST (sensitivity 53%, PPV 34%). CONCLUSION: In this cross-sectional study of patients with CRC, the concordance between the GLIM-criteria and PG-SGA depended on the screening tool used in the GLIM process. Malnutrition frequency based on the GLIM process schould be reported with and without the use of a screening tool.

Aurora kinase A and B as new treatment targets in aromatase inhibitor-resistant breast cancer cells.

Aromatase inhibitors (AIs) are used for treatment of estrogen receptor α (ER)-positive breast cancer; however, resistance is a major obstacle for optimal outcome. This preclinical study aimed at identifying potential new treatment targets in AI-resistant breast cancer cells. Parental MCF-7 breast cancer cells and four newly established cell lines, resistant to the AIs exemestane or letrozole, were used for a functional kinase inhibitor screen. A library comprising 195 different compounds was tested for preferential growth inhibition of AI-resistant cell lines. Selected targets were validated by analysis of cell growth, cell cycle phase distribution, protein expression, and subcellular localization. We identified 24 compounds, including several inhibitors of Aurora kinases e.g., JNJ-7706621 and barasertib. Protein expression of Aurora kinase A and B was found upregulated in AI-resistant cells compared with MCF-7, and knockdown studies showed that Aurora kinase A was essential for AI-resistant cell growth. In AI-resistant cell lines, the clinically relevant Aurora kinase inhibitors alisertib and danusertib blocked cell cycle progression at the G2/M phase, interfered with chromosome alignment and spindle pole formation, and resulted in preferential growth inhibition compared with parental MCF-7 cells. Even further growth inhibition was obtained when combining the Aurora kinase inhibitors with the antiestrogen fulvestrant. Our study is the first to demonstrate that Aurora kinase A and B may be treatment targets in AI-resistant cells, and our data suggest that therapy targeting both ER and Aurora kinases may be a potent treatment strategy for overcoming AI resistance in breast cancer.

New cell culture model for aromatase inhibitor-resistant breast cancer shows sensitivity to fulvestrant treatment and cross-resistance between letrozole and exemestane.

Aromatase inhibitor (AI) treatment is first-line systemic treatment for the majority of postmenopausal breast cancer patients with estrogen receptor (ER)-positive primary tumor. Although many patients benefit from treatment, some will develop resistance, and models mimicking acquired resistance will be valuable tools to unravel the resistance mechanisms and to find new treatments and biomarkers. Cell culture models for acquired resistance to the three clinically relevant AIs letrozole, anastrozole and exemestane were developed by selection and expansion of colonies of MCF-7 breast cancer cells surviving long-term AI treatment under conditions where endogenous aromatase-mediated conversion of androgen to estrogen was required for growth. Four cell lines resistant to each of the AIs were established and characterized. Maintenance of ER expression and function was a general finding, but ER loss was seen in one of twelve cell lines. HER receptor expression was increased, in particular EGFR expression in letrozole-resistant cell lines. The AI-resistant cell lines had acquired ability to grow without aromatase-mediated conversion of testosterone to estradiol, but upon withdrawal of AI treatment, testosterone induced minor growth stimulation. Letrozole, exemestane and tamoxifen were able to abrogate the testosterone stimulation but could not reduce growth to below the level in standard growth medium with AI, demonstrating cross-resistance between letrozole, exemestane and tamoxifen. In contrast, fulvestrant totally blocked growth of the AI resistant cell lines both after withdrawal of AI and with AI treatment. These data show that ER is the main driver of growth of the AI-resistant cell lines and indicate ligand-independent activation of ER. Fulvestrant is an efficient treatment option for these AI-resistant breast cancer cells, and the cell lines will be useful tools to disclose the underlying molecular mechanism for resistance to the different AIs.

Sorafenib and nilotinib resensitize tamoxifen resistant breast cancer cells to tamoxifen treatment via estrogen receptor α.

Tamoxifen­resistant breast cancer is a major clinical problem and new treatment strategies are highly warranted. In this study, the multitargeting kinase inhibitors sorafenib and nilotinib were investigated as potential new treatment options for tamoxifen­resistant breast cancer. The two compounds inhibited cell growth, reduced expression of total estrogen receptor α (ER), Ser118-phosphorylated ER, FOXA1 and AIB1 and resensitized tamoxifen­resistant cells to tamoxifen. The ER downmodulator fulvestrant exerted strong growth inhibition of tamoxifen­resistant cells and addition of sorafenib and nilotinib could not further suppress growth, showing that sorafenib and nilotinib exerted growth inhibition via ER. In support of this, estradiol prevented sorafenib and nilotinib mediated growth inhibition. These results demonstrate that sorafenib and nilotinib act via ER and ER-associated proteins, indicating that these kinase inhibitors in combination with tamoxifen may be potential new treatments for tamoxifen­resistant breast cancer.