[Abstract unavailable

Osimertinib is an irreversible, third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that is highly selective for EGFR-activating mutations as well as the EGFR T790M mutation in patients with advanced non-small cell lung cancer (NSCLC) with EGFR oncogene addiction. Despite the documented efficacy of osimertinib in first- and second-line settings, patients inevitably develop resistance, with no further clear-cut therapeutic options to date other than chemotherapy and locally ablative therapy for selected individuals. On account of the high degree of tumour heterogeneity and adaptive cellular signalling pathways in NSCLC, the acquired osimertinib resistance is highly heterogeneous, encompassing EGFR-dependent as well as EGFR-independent mechanisms. Furthermore, data from repeat plasma genotyping analyses have highlighted differences in the frequency and preponderance of resistance mechanisms when osimertinib is administered in a front-line versus second-line setting, underlying the discrepancies in selection pressure and clonal evolution. This review summarises the molecular mechanisms of resistance to osimertinib in patients with advanced EGFR-mutated NSCLC, including MET/HER2 amplification, activation of the RAS–mitogen-activated protein kinase (MAPK) or RAS–phosphatidylinositol 3-kinase (PI3K) pathways, novel fusion events and histological/phenotypic transformation, as well as discussing the current evidence regarding potential new approaches to counteract osimertinib resistance.

MicroRNA-21 (miR-21) was reported to be overexpressed and contributes to invasion and gemcitabine resistance in pancreatic ductal adenocarcinoma (PDAC). The aim of this study was to evaluate whether miR-21 expression was associated with the overall survival (OS) of PDAC patients treated with gemcitabine and to provide mechanistic insights for new therapeutic targets. miR-21 expression was evaluated in cells (including 7 PDAC cell lines, 7 primary cultures, fibroblasts, and a normal pancreatic ductal cell line) and tissues (neoplastic specimens from 81 PDAC patients and normal ductal samples) isolated by laser microdissection. The role of miR-21 on the pharmacologic effects of gemcitabine was studied with a specific miR-21 precursor (pre-miR-21). Patients with high miR-21 expression had a significantly shorter OS both in the metastatic and in the adjuvant setting. Multivariate analysis confirmed the prognostic significance of miR-21. miR-21 expression in primary cultures correlated with expression in their respective tissues and with gemcitabine resistance. Pre-miR-21 transfection significantly decreased antiproliferative effects and apoptosis induction by gemcitabine, whereas matrix metalloproteinase (MMP)-2/MMP-9 and vascular endothelial growth factor expression were upregulated. Addition of inhibitors of phosphoinositide 3-kinase and mammalian target of rapamycin resulted in decrease of phospho-Akt and prevented pre-miR-21-induced resistance to the proapoptotic effects of gemcitabine. miR-21 expression correlated with outcome in PDAC patients treated with gemcitabine. Modulation of apoptosis, Akt phosphorylation, and expression of genes involved in invasive behavior may contribute to the role of miR-21 in gemcitabine chemoresistance and to the rational development of new targeted combinations. Cancer Res; 70(11); 4528-38. ©2010 AACR.

Gene expression analysis may help the management of cancer patients, allowing the selection of subjects responding to treatment. The aim of this study was the characterization of expression pattern of genes involved in gemcitabine activity in pancreas tumor specimens and its correlation with treatment outcome. The role of drug transport and metabolism on gemcitabine cytotoxicity was examined with specific inhibitors, whereas transcription analysis of human equilibrative nucleoside transporter-1 (hENT1), deoxycytidine kinase (dCK), 5V -nucleotidase (5V -NT), cytidine deaminase (CDA), and ribonucleotide reductase subunits M1 and M2 (RRM1 and RRM2) was done by quantitative reverse transcription-PCR in tumor tissue isolated by laser microdissection from surgical or biopsy samples of 102 patients. Association between clinical outcome and gene expression levels was estimated using Kaplan-Meier method and Cox's proportional hazards model. Transport and metabolism had a key role on gemcitabine sensitivity in vitro; moreover, hENT1, dCK, 5V -NT, CDA, RRM1, and RRM2 were detectable in most tumor specimens. hENT1 expression was significantly correlated with clinical outcome. Patients with high levels of hENT1 had a significantly longer overall survival [median, 25.7; 95% confidence interval (95% CI), 17.6-33.7 months in the higher expression tertile versus median, 8.5; 95% CI, 7.0-9.9 months in the lower expression tertile]. Similar results were obtained with disease-free survival and time to disease progression, and the multivariate analysis confirmed the prognostic significance of hENT1. This study suggests that the expression levels of hENT1 may allow the stratification of patients based on their likelihood of survival, thus offering a potential new tool for treatment optimization. (Cancer Res 2006; 66(7): 3928-35)

Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.

BackgroundPancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. The high risk of recurrence following surgical resection provides the rationale for adjuvant therapy. However, only a subset of patients benefit from adjuvant therapy. Identification of molecular markers to predict treatment outcome is therefore warranted. The aim of the present study was to evaluate whether expression of novel candidate biomarkers, including microRNAs, can predict clinical outcome in PDAC patients treated with adjuvant therapy.Methodology/Principal FindingsFormalin-fixed paraffin embedded specimens from a cohort of 82 resected Korean PDAC cases were analyzed for protein expression by immunohistochemistry and for microRNA expression using quantitative Real-Time PCR. Cox proportional hazards model analysis in the subgroup of patients treated with adjuvant therapy (N = 52) showed that lower than median miR-21 expression was associated with a significantly lower hazard ratio (HR) for death (HR = 0.316; 95%CI = 0.166–0.600; P = 0.0004) and recurrence (HR = 0.521; 95%CI = 0.280–0.967; P = 0.04). MiR-21 expression status emerged as the single most predictive biomarker for treatment outcome among all 27 biological and 9 clinicopathological factors evaluated. No significant association was detected in patients not treated with adjuvant therapy. In an independent validation cohort of 45 frozen PDAC tissues from Italian cases, all treated with adjuvant therapy, lower than median miR-21 expression was confirmed to be correlated with longer overall as well as disease-free survival. Furthermore, transfection with anti-miR-21 enhanced the chemosensitivity of PDAC cells.Conclusions SignificanceLow miR-21 expression was associated with benefit from adjuvant treatment in two independent cohorts of PDAC cases, and anti-miR-21 increased anticancer drug activity in vitro. These data provide evidence that miR-21 may allow stratification for adjuvant therapy, and represents a new potential target for therapy in PDAC.

Highly invasive tumor cells are characterized by a metabolic switch, known as the Warburg effect, from "normal" oxidative phosphorylation to increased glycolysis even under sufficiently oxygenated conditions. This dependence on glycolysis also confers a growth advantage to cells present in hypoxic regions of the tumor. One of the key enzymes involved in glycolysis, the muscle isoform of lactate dehydrogenase (LDH-A), is overexpressed by metastatic cancer cells and is linked to the vitality of tumors in hypoxia. This enzyme may be considered as a potential target for new anticancer agents, since its inhibition cuts cancer energetic and anabolic supply, thus reducing the metastatic and invasive potential of cancer cells. We have discovered new and efficient N-hydroxyindole-based inhibitors of LDH-A, which are isoform-selective (over LDH-B) and competitive with both the substrate (pyruvate) and the cofactor (NADH). The antiproliferative activity of these compounds was confirmed on a series of cancer cell lines, and they proved to be particularly effective under hypoxic conditions. Moreover, NMR experiments showed that these compounds are able to reduce the glucose-to-lactate conversion inside the cell.

Most of the current therapies against cancer, and also those against immune diseases or viral infections, consist of empirically designed combination strategies, combining a variety of therapeutic agents. Drug combinations are widely used because multiple drugs affect multiple targets and cell subpopulations. The primary aim is a mutual enhancement of the therapeutic effects, while other benefits may include decreased side effects and the delay or prevention of drug resistance. The large majority of combination regimens are being developed empirically and there are few experimental studies designed to explore thoroughly different drug combinations, using appropriate methods of analysis. However, the study of patterns of possible metabolic and biological interactions in preclinical models, as well as scheduling, should improve the development of most drug combinations. The definition of synergism is that the combination is more effective than each agent separately, e.g., one of the agents augments the actions of the second drug. The definition of antagonism is that the combination is less effective than the single agents, e.g. one of the agents counteracts the actions of the other. A combination can be studied by combining the two agents in various different ways, such as simultaneous or sequential combination schedules. It is essential to test the potency of a combination, before evaluation in the clinic, to prevent antagonistic actions. However, one should realize that an antagonistic action may be desired when toxicity is concerned, i.e. one drug decreases the side effects of another drug. Several attempts have been made to quantitatively measure the dose-effect relationship of each drug alone and its combinations and to determine whether a given combination would gain a synergistic effect. One of the most widely used ways to evaluate whether a combination is effective is the median-drug effect analysis method. Using this method, a combination index (CI) is calculated from drug cytotoxicity or growth inhibition curves. To calculate a CI, the computer software Calcusyn can be used, taking the entire shape of the growth inhibition curve into account for calculating whether a combination is synergistic, additive, or antagonistic. Here, we describe how combinations can be designed in vitro and how to analyze them using Calcusyn or Compusyn. Moreover, pitfalls, limitations, and advantages of using these combinations and Calcusyn/Compusyn are described.