Stromal-Based Signatures for the Classification of Gastric Cancer
©2016 American Association for Cancer Research..
Treatment of metastatic gastric cancer typically involves chemotherapy and monoclonal antibodies targeting HER2 (ERBB2) and VEGFR2 (KDR). However, reliable methods to identify patients who would benefit most from a combination of treatment modalities targeting the tumor stroma, including new immunotherapy approaches, are still lacking. Therefore, we integrated a mouse model of stromal activation and gastric cancer genomic information to identify gene expression signatures that may inform treatment strategies. We generated a mouse model in which VEGF-A is expressed via adenovirus, enabling a stromal response marked by immune infiltration and angiogenesis at the injection site, and identified distinct stromal gene expression signatures. With these data, we designed multiplexed IHC assays that were applied to human primary gastric tumors and classified each tumor to a dominant stromal phenotype representative of the vascular and immune diversity found in gastric cancer. We also refined the stromal gene signatures and explored their relation to the dominant patient phenotypes identified by recent large-scale studies of gastric cancer genomics (The Cancer Genome Atlas and Asian Cancer Research Group), revealing four distinct stromal phenotypes. Collectively, these findings suggest that a genomics-based systems approach focused on the tumor stroma can be used to discover putative predictive biomarkers of treatment response, especially to antiangiogenesis agents and immunotherapy, thus offering an opportunity to improve patient stratification. Cancer Res; 76(9); 2573-86. ©2016 AACR.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2016 |
|---|---|
| Erschienen: |
2016 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:76 |
|---|---|
| Enthalten in: |
Cancer research - 76(2016), 9 vom: 01. Mai, Seite 2573-86 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Uhlik, Mark T [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Biomarkers, Tumor |
|---|
| Anmerkungen: |
Date Completed 24.07.2017 Date Revised 30.10.2017 published: Print Citation Status MEDLINE |
|---|
| doi: |
10.1158/0008-5472.CAN-16-0022 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM260513067 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM260513067 | ||
| 003 | DE-627 | ||
| 005 | 20231224193549.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231224s2016 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1158/0008-5472.CAN-16-0022 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n0868.xml |
| 035 | |a (DE-627)NLM260513067 | ||
| 035 | |a (NLM)27197264 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Uhlik, Mark T |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Stromal-Based Signatures for the Classification of Gastric Cancer |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 24.07.2017 | ||
| 500 | |a Date Revised 30.10.2017 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a ©2016 American Association for Cancer Research. | ||
| 520 | |a Treatment of metastatic gastric cancer typically involves chemotherapy and monoclonal antibodies targeting HER2 (ERBB2) and VEGFR2 (KDR). However, reliable methods to identify patients who would benefit most from a combination of treatment modalities targeting the tumor stroma, including new immunotherapy approaches, are still lacking. Therefore, we integrated a mouse model of stromal activation and gastric cancer genomic information to identify gene expression signatures that may inform treatment strategies. We generated a mouse model in which VEGF-A is expressed via adenovirus, enabling a stromal response marked by immune infiltration and angiogenesis at the injection site, and identified distinct stromal gene expression signatures. With these data, we designed multiplexed IHC assays that were applied to human primary gastric tumors and classified each tumor to a dominant stromal phenotype representative of the vascular and immune diversity found in gastric cancer. We also refined the stromal gene signatures and explored their relation to the dominant patient phenotypes identified by recent large-scale studies of gastric cancer genomics (The Cancer Genome Atlas and Asian Cancer Research Group), revealing four distinct stromal phenotypes. Collectively, these findings suggest that a genomics-based systems approach focused on the tumor stroma can be used to discover putative predictive biomarkers of treatment response, especially to antiangiogenesis agents and immunotherapy, thus offering an opportunity to improve patient stratification. Cancer Res; 76(9); 2573-86. ©2016 AACR | ||
| 650 | 4 | |a Journal Article | |
| 650 | 7 | |a Biomarkers, Tumor |2 NLM | |
| 650 | 7 | |a Vascular Endothelial Growth Factor A |2 NLM | |
| 700 | 1 | |a Liu, Jiangang |e verfasserin |4 aut | |
| 700 | 1 | |a Falcon, Beverly L |e verfasserin |4 aut | |
| 700 | 1 | |a Iyer, Seema |e verfasserin |4 aut | |
| 700 | 1 | |a Stewart, Julie |e verfasserin |4 aut | |
| 700 | 1 | |a Celikkaya, Hilal |e verfasserin |4 aut | |
| 700 | 1 | |a O'Mahony, Marguerita |e verfasserin |4 aut | |
| 700 | 1 | |a Sevinsky, Christopher |e verfasserin |4 aut | |
| 700 | 1 | |a Lowes, Christina |e verfasserin |4 aut | |
| 700 | 1 | |a Douglass, Larry |e verfasserin |4 aut | |
| 700 | 1 | |a Jeffries, Cynthia |e verfasserin |4 aut | |
| 700 | 1 | |a Bodenmiller, Diane |e verfasserin |4 aut | |
| 700 | 1 | |a Chintharlapalli, Sudhakar |e verfasserin |4 aut | |
| 700 | 1 | |a Fischl, Anthony |e verfasserin |4 aut | |
| 700 | 1 | |a Gerald, Damien |e verfasserin |4 aut | |
| 700 | 1 | |a Xue, Qi |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Jee-Yun |e verfasserin |4 aut | |
| 700 | 1 | |a Santamaria-Pang, Alberto |e verfasserin |4 aut | |
| 700 | 1 | |a Al-Kofahi, Yousef |e verfasserin |4 aut | |
| 700 | 1 | |a Sui, Yunxia |e verfasserin |4 aut | |
| 700 | 1 | |a Desai, Keyur |e verfasserin |4 aut | |
| 700 | 1 | |a Doman, Thompson |e verfasserin |4 aut | |
| 700 | 1 | |a Aggarwal, Amit |e verfasserin |4 aut | |
| 700 | 1 | |a Carter, Julia H |e verfasserin |4 aut | |
| 700 | 1 | |a Pytowski, Bronislaw |e verfasserin |4 aut | |
| 700 | 1 | |a Jaminet, Shou-Ching |e verfasserin |4 aut | |
| 700 | 1 | |a Ginty, Fiona |e verfasserin |4 aut | |
| 700 | 1 | |a Nasir, Aejaz |e verfasserin |4 aut | |
| 700 | 1 | |a Nagy, Janice A |e verfasserin |4 aut | |
| 700 | 1 | |a Dvorak, Harold F |e verfasserin |4 aut | |
| 700 | 1 | |a Benjamin, Laura E |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Cancer research |d 1945 |g 76(2016), 9 vom: 01. Mai, Seite 2573-86 |w (DE-627)NLM000001740 |x 1538-7445 |7 nnns |
| 773 | 1 | 8 | |g volume:76 |g year:2016 |g number:9 |g day:01 |g month:05 |g pages:2573-86 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1158/0008-5472.CAN-16-0022 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 76 |j 2016 |e 9 |b 01 |c 05 |h 2573-86 | ||