title: Anticancer drug clustering in lung cancer based on gene expression profiles and sensitivity database.
abstract: BACKGROUND
  The effect of current therapies in improving the survival of lung cancer patients remains far from satisfactory. It is consequently desirable to find more appropriate therapeutic opportunities based on informed insights. A molecular pharmacological analysis was undertaken to design an improved chemotherapeutic strategy for advanced lung cancer.
  
  
  METHODS
  We related the cytotoxic activity of each of commonly used anti-cancer agents (docetaxel, paclitaxel, gemcitabine, vinorelbine, 5-FU, SN38, cisplatin (CDDP), and carboplatin (CBDCA)) to corresponding expression pattern in each of the cell lines using a modified NCI program.
  
  
  RESULTS
  We performed gene expression analysis in lung cancer cell lines using cDNA filter and high-density oligonucleotide arrays. We also examined the sensitivity of these cell lines to these drugs via MTT assay. To obtain our reproducible gene-drug sensitivity correlation data, we separately analyzed two sets of lung cancer cell lines, namely 10 and 19. In our gene-drug correlation analyses, gemcitabine consistently belonged to an isolated cluster in a reproducible fashion. On the other hand, docetaxel, paclitaxel, 5-FU, SN-38, CBDCA and CDDP were gathered together into one large cluster.
  
  
  CONCLUSIONS
  These results suggest that chemotherapy regimens including gemcitabine should be evaluated in second-line chemotherapy in cases where the first-line chemotherapy did not include this drug. Gene expression-drug sensitivity correlations, as provided by the NCI program, may yield improved therapeutic options for treatment of specific tumor types.
authors.affiliation: The Fourth Department of Medicine, Nippon Medical School, 1-1-5, Sendagi, Bunkyo-ku, Tokyo, 113-8602, Japan. agemma@nms.ac.jp
authors.forename: Akihiko
authors.initials: A
authors.lastname: Gemma
authors.forename: Cai
authors.initials: C
authors.lastname: Li
authors.forename: Yuka
authors.initials: Y
authors.lastname: Sugiyama
authors.forename: Kuniko
authors.initials: K
authors.lastname: Matsuda
authors.forename: Yoko
authors.initials: Y
authors.lastname: Seike
authors.forename: Seiji
authors.initials: S
authors.lastname: Kosaihira
authors.forename: Yuji
authors.initials: Y
authors.lastname: Minegishi
authors.forename: Rintaro
authors.initials: R
authors.lastname: Noro
authors.forename: Michiya
authors.initials: M
authors.lastname: Nara
authors.forename: Masahiro
authors.initials: M
authors.lastname: Seike
authors.forename: Akinobu
authors.initials: A
authors.lastname: Yoshimura
authors.forename: Aki
authors.initials: A
authors.lastname: Shionoya
authors.forename: Akiko
authors.initials: A
authors.lastname: Kawakami
authors.forename: Naoki
authors.initials: N
authors.lastname: Ogawa
authors.forename: Haruka
authors.initials: H
authors.lastname: Uesaka
authors.forename: Shoji
authors.initials: S
authors.lastname: Kudoh
mesh_terms: D000964:Antimetabolites, Antineoplastic / Q000494:pharmacology* / Q000627:therapeutic use; D000970:Antineoplastic Agents / Q000494:pharmacology* / Q000627:therapeutic use*; D016208:Databases, Factual; D003841:Deoxycytidine / Q000031:analogs & derivatives* / Q000494:pharmacology / Q000627:therapeutic use; D004354:Drug Screening Assays, Antitumor / Q000706:statistics & numerical data; D020869:Gene Expression Profiling; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy* / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D014407:Tumor Cells, Cultured; D000093542:Gemcitabine
chemical_list: D000964:Antimetabolites, Antineoplastic; D000970:Antineoplastic Agents; D003841:Deoxycytidine; D000093542:Gemcitabine