Raffaella Sordella

Bio: Raffaella Sordella is an academic researcher from Cold Spring Harbor Laboratory. The author has contributed to research in topics: Epidermal growth factor receptor & Erlotinib. The author has an hindex of 29, co-authored 50 publications receiving 17748 citations. Previous affiliations of Raffaella Sordella include Cornell University & Watson School of Biological Sciences.

Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib

Abstract: BACKGROUND Most patients with non-small-cell lung cancer have no response to the tyrosine kinase inhibitor gefitinib, which targets the epidermal growth factor receptor (EGFR). However, about 10 percent of patients have a rapid and often dramatic clinical response. The molecular mechanisms underlying sensitivity to gefitinib are unknown. METHODS We searched for mutations in the EGFR gene in primary tumors from patients with non-small-cell lung cancer who had a response to gefitinib, those who did not have a response, and those who had not been exposed to gefitinib. The functional consequences of identified mutations were evaluated after the mutant proteins were expressed in cultured cells. RESULTS Somatic mutations were identified in the tyrosine kinase domain of the EGFR gene in eight of nine patients with gefitinib-responsive lung cancer, as compared with none of the seven patients with no response (P<0.001). Mutations were either small, in-frame deletions or amino acid substitutions clustered around the ATP-binding pocket of the tyrosine kinase domain. Similar mutations were detected in tumors from 2 of 25 patients with primary non-small-cell lung cancer who had not been exposed to gefitinib (8 percent). All mutations were heterozygous, and identical mutations were observed in multiple patients, suggesting an additive specific gain of function. In vitro, EGFR mutants demonstrated enhanced tyrosine kinase activity in response to epidermal growth factor and increased sensitivity to inhibition by gefitinib. CONCLUSIONS A subgroup of patients with non-small-cell lung cancer have specific mutations in the EGFR gene, which correlate with clinical responsiveness to the tyrosine kinase inhibitor gefitinib. These mutations lead to increased growth factor signaling and confer susceptibility to the inhibitor. Screening for such mutations in lung cancers may identify patients who will have a response to gefitinib.

Gefitinib-Sensitizing EGFR Mutations in Lung Cancer Activate Anti-Apoptotic Pathways

Abstract: Gefitinib (Iressa, Astra Zeneca Pharmaceuticals) is a tyrosine kinase inhibitor that targets the epidermal growth factor receptor (EGFR) and induces dramatic clinical responses in nonsmall cell lung cancers (NSCLCs) with activating mutations within the EGFR kinase domain. We report that these mutant EGFRs selectively activate Akt and signal transduction and activator of transcription (STAT) signaling pathways, which promote cell survival, but have no effect on extracellular signal-regulated kinase signaling, which induces proliferation. NSCLC cells expressing mutant EGFRs underwent extensive apoptosis after small interfering RNA-mediated knockdown of the mutant EGFR or treatment with pharmacological inhibitors of Akt and STAT signaling and were relatively resistant to apoptosis induced by conventional chemotherapeutic drugs. Thus, mutant EGFRs selectively transduce survival signals on which NSCLCs become dependent; inhibition of those signals by gefitinib may contribute to the drug's efficacy.

Irreversible inhibitors of the EGF receptor may circumvent acquired resistance to gefitinib

Abstract: Non-small cell lung cancers (NSCLCs) with activating mutations in the kinase domain of the epidermal growth factor receptor (EGFR) demonstrate dramatic, but transient, responses to the reversible tyrosine kinase inhibitors gefitinib (Iressa) and erlotinib (Tarceva). Some recurrent tumors have a common secondary mutation in the EGFR kinase domain, T790M, conferring drug resistance, but in other cases the mechanism underlying acquired resistance is unknown. In studying multiple sites of recurrent NSCLCs, we detected T790M in only a small percentage of tumor cells. To identify additional mechanisms of acquired resistance to gefitinib, we used NSCLC cells harboring an activating EGFR mutation to generate multiple resistant clones in vitro. These drug-resistant cells demonstrate continued dependence on EGFR and ERBB2 signaling for their viability and have not acquired secondary EGFR mutations. However, they display increased internalization of ligand-activated EGFR, consistent with altered receptor trafficking. Although gefitinib-resistant clones are cross-resistant to related anilinoquinazolines, they demonstrate sensitivity to a class of irreversible inhibitors of EGFR. These inhibitors also show effective inhibition of signaling by T790M-mutant EGFR and killing of NSCLC cells with the T790M mutation. Both mechanisms of gefitinib resistance are therefore circumvented by irreversible tyrosine kinase inhibitors. Our findings suggest that one of these, HKI-272, may prove highly effective in the treatment of EGFR-mutant NSCLCs, including tumors that have become resistant to gefitinib or erlotinib.

Protein Interaction Mapping in C. elegans Using Proteins Involved in Vulval Development

Abstract: Protein interaction mapping using large-scale two-hybrid analysis has been proposed as a way to functionally annotate large numbers of uncharacterized proteins predicted by complete genome sequences. This approach was examined in Caenorhabditis elegans, starting with 27 proteins involved in vulval development. The resulting map reveals both known and new potential interactions and provides a functional annotation for approximately 100 uncharacterized gene products. A protein interaction mapping project is now feasible for C. elegans on a genome-wide scale and should contribute to the understanding of molecular mechanisms in this organism and in human diseases.

Amplification of MET may identify a subset of cancers with extreme sensitivity to the selective tyrosine kinase inhibitor PHA-665752

Abstract: The success of molecular targeted therapy in cancer may depend on the selection of appropriate tumor types whose survival depends on the drug target, so-called “oncogene addiction.” Preclinical approaches to defining drug-responsive subsets are needed if initial clinical trials are to be directed at the most susceptible patient population. Here, we show that gastric cancer cells with high-level stable chromosomal amplification of the growth factor receptor MET are extraordinarily susceptible to the selective inhibitor PHA-665752. Although MET activation has primarily been linked with tumor cell migration and invasiveness, the amplified wild-type MET in these cells is constitutively activated, and its continued signaling is required for cell survival. Treatment with PHA-665752 triggers massive apoptosis in 5 of 5 gastric cancer cell lines with MET amplification but in 0 of 12 without increased gene copy numbers (P = 0.00016). MET amplification may thus identify a subset of epithelial cancers that are uniquely sensitive to disruption of this pathway and define a patient group that is appropriate for clinical trials of targeted therapy using MET inhibitors.

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Abstract: Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy.

Abstract: Receptor tyrosine kinase genes were sequenced in nonsmall cell lung cancer (NSCLC) and matched normal tissue. Somatic mutations of the epidermal growth factor receptor gene EGFR were found in 15 of 58 unselected tumors from Japan and 1 of 61 from the United States. Treatment with the EGFR kinase inhibitor gefitinib (Iressa) causes tumor regression in some patients with NSCLC, more frequently in Japan. EGFR mutations were found in additional lung cancer samples from U.S. patients who responded to gefitinib therapy and in a lung adenocarcinoma cell line that was hypersensitive to growth inhibition by gefitinib, but not in gefitinibinsensitive tumors or cell lines. These results suggest that EGFR mutations may predict sensitivity to gefitinib. Protein kinase activation by somatic mutation or

Gefitinib or Carboplatin–Paclitaxel in Pulmonary Adenocarcinoma

Abstract: METHODS In this phase 3, open-label study, we randomly assigned previously untreated patients in East Asia who had advanced pulmonary adenocarcinoma and who were nonsmokers or former light smokers to receive gefitinib (250 mg per day) (609 patients) or carboplatin (at a dose calculated to produce an area under the curve of 5 or 6 mg per milliliter per minute) plus paclitaxel (200 mg per square meter of body-surface area) (608 patients). The primary end point was progression-free survival. RESULTS The 12-month rates of progression-free survival were 24.9% with gefitinib and 6.7% with carboplatin–paclitaxel. The study met its primary objective of showing the noninferiority of gefitinib and also showed its superiority, as compared with carboplatin– paclitaxel, with respect to progression-free survival in the intention-to-treat population (hazard ratio for progression or death, 0.74; 95% confidence interval [CI], 0.65 to 0.85; P<0.001). In the subgroup of 261 patients who were positive for the epidermal growth factor receptor gene (EGFR) mutation, progression-free survival was significantly longer among those who received gefitinib than among those who received carboplatin–paclitaxel (hazard ratio for progression or death, 0.48; 95% CI, 0.36 to 0.64; P<0.001), whereas in the subgroup of 176 patients who were negative for the mutation, progression-free survival was significantly longer among those who received carboplatin–paclitaxel (hazard ratio for progression or death with gefitinib, 2.85; 95% CI, 2.05 to 3.98; P<0.001). The most common adverse events were rash or acne (in 66.2% of patients) and diarrhea (46.6%) in the gefitinib group and neurotoxic effects (69.9%), neutropenia (67.1%), and alopecia (58.4%) in the carboplatin–paclitaxel group. CONCLUSIONS Gefitinib is superior to carboplatin–paclitaxel as an initial treatment for pulmonary adenocarcinoma among nonsmokers or former light smokers in East Asia. The presence in the tumor of a mutation of the EGFR gene is a strong predictor of a better outcome with gefitinib. (ClinicalTrials.gov number, NCT00322452.)

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

Abstract: The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.