Literature DB >> 25658301

Strategies to improve the outcome in locally advanced pancreatic cancer.

C Späth1, U Nitsche, T Müller, C Michalski, M Erkan, B Kong, J Kleeff.   

Abstract

Pancreatic cancer is associated with the worst prognosis of all gastrointestinal malignancies. The major reasons for the dismal outcome are late diagnosis due to unspecific symptoms and aggressive tumor biology. Although highly effective chemotherapeutic options have emerged within the last decade, radical resection offers the only chance of cure. Only 10-20% of patients are resectable at presentation, and 30-40% present with borderline resectable or locally advanced/unresectable tumors. Even if resectable, the 5-year-survival rate after complete resections remains unsatisfactory, with less than 25%. This article gives an overview on current therapy standards as well as on new approaches especially for locally advanced tumors and outlines the importance of ongoing research to improve prognosis.

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Year:  2015        PMID: 25658301

Source DB:  PubMed          Journal:  Minerva Chir        ISSN: 0026-4733            Impact factor:   1.000


  5 in total

1.  Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer.

Authors:  Yosuke Iwatate; Hajime Yokota; Isamu Hoshino; Fumitaka Ishige; Naoki Kuwayama; Makiko Itami; Yasukuni Mori; Satoshi Chiba; Hidehito Arimitsu; Hiroo Yanagibashi; Wataru Takayama; Takashi Uno; Jason Lin; Yuki Nakamura; Yasutoshi Tatsumi; Osamu Shimozato; Hiroki Nagase
Journal:  PLoS One       Date:  2022-06-01       Impact factor: 3.752

2.  Molecular, morphological and survival analysis of 177 resected pancreatic ductal adenocarcinomas (PDACs): Identification of prognostic subtypes.

Authors:  Anna Melissa Schlitter; Angela Segler; Katja Steiger; Christoph W Michalski; Carsten Jäger; Björn Konukiewitz; Nicole Pfarr; Volker Endris; Markus Bettstetter; Bo Kong; Ivonne Regel; Jörg Kleeff; Günter Klöppel; Irene Esposito
Journal:  Sci Rep       Date:  2017-02-01       Impact factor: 4.379

3.  Machine learning with imaging features to predict the expression of ITGAV, which is a poor prognostic factor derived from transcriptome analysis in pancreatic cancer.

Authors:  Yosuke Iwatate; Hajime Yokota; Isamu Hoshino; Fumitaka Ishige; Naoki Kuwayama; Makiko Itami; Yasukuni Mori; Satoshi Chiba; Hidehito Arimitsu; Hiroo Yanagibashi; Wataru Takayama; Takashi Uno; Jason Lin; Yuki Nakamura; Yasutoshi Tatsumi; Osamu Shimozato; Hiroki Nagase
Journal:  Int J Oncol       Date:  2022-04-08       Impact factor: 5.650

4.  Opium use, cigarette smoking, and alcohol consumption in relation to pancreatic cancer.

Authors:  Ramin Shakeri; Farin Kamangar; Mehdi Mohamadnejad; Reza Tabrizi; Farhad Zamani; Ashraf Mohamadkhani; Sepideh Nikfam; Arash Nikmanesh; Masoud Sotoudeh; Rasoul Sotoudehmanesh; Bijan Shahbazkhani; Mohammad Reza Ostovaneh; Farhad Islami; Hossein Poustchi; Paolo Boffetta; Reza Malekzadeh; Akram Pourshams
Journal:  Medicine (Baltimore)       Date:  2016-07       Impact factor: 1.889

5.  Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.

Authors:  Yosuke Iwatate; Isamu Hoshino; Hajime Yokota; Fumitaka Ishige; Makiko Itami; Yasukuni Mori; Satoshi Chiba; Hidehito Arimitsu; Hiroo Yanagibashi; Hiroki Nagase; Wataru Takayama
Journal:  Br J Cancer       Date:  2020-07-21       Impact factor: 7.640

  5 in total

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