Towards risk-adapted perioperative treatment of gastroesophageal cancer
Authors: F. Lordick
Journal: Annals of Oncology (2018)

The Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) trial has defined perioperative platinum-fluorpyrimidine-based chemotherapy as standard of care for resectable gastroesophageal cancer (GC) more than 10 years ago [1.Cunningham D. Allum W.H. Stenning S.P. et al.Perioperative chemotherapy versus surgery alone for resectable gastroesophageal cancer.N Engl J Med. 2006; 355: 11-20Crossref PubMed Scopus (4661) Google Scholar, 2.Smyth E.C. Verheij M. Allum W. et al.Gastric cancer: eSMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.Ann Oncol. 2016; 27: v38-v49Abstract Full Text Full Text PDF PubMed Scopus (990) Google Scholar, 3.Lordick F. Mariette C. Haustermans K. et al.Oesophageal cancer: eSMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.Ann Oncol. 2016; 27: v50-v57Abstract Full Text Full Text PDF PubMed Scopus (603) Google Scholar]. This treatment leads to cure for approximately half of patients diagnosed in the Western World, which is significantly higher than with surgery alone. Investigators from the Royal Marsden Hospital and collaborators explored data from the MAGIC trial and investigated sampled tumor material. They demonstrated in a series of publications how much additional knowledge one can extract from a well-designed randomized controlled trial by ambitious and intelligent retrospective analyses. In one of their publications Smyth et al. recently reported that the ypN0 status was the only independent predictor of survival after neoadjuvant chemotherapy and resection [4.Smyth E.C. Fassan M. Cunningham D. et al.Effect of pathologic tumor response and nodal status on survival in the medical research council adjuvant gastric infusional chemotherapy trial.J Clin Oncol. 2016; 34: 2721-2727Crossref PubMed Scopus (171) Google Scholar]. Another analysis revealed that deficient tumor mismatch repair and high microsatellite instability were associated with a better prognosis in patients treated with surgery alone but with a worse prognosis in patients treated with chemotherapy and surgery [5.Smyth E.C. Wotherspoon A. Peckitt C. et al.Mismatch repair deficiency. Microsatellite instability, and survival: an exploratory analysis of the Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) Trial.JAMA Oncol. 2017; 3: 1197-1203Crossref PubMed Scopus (290) Google Scholar]. In their current article published in this issue of the Annals of Oncology, Smyth and co-authors report on a transcriptomic analysis leading to a prognostic 7-gene-signature identified in post-chemotherapy resection specimens from patients with localized GC [6.Smyth E.C. Nyamundanda G. Cunningham D. et al.A seven-Gene Signature assay improves prognostic risk stratification of perioperative chemotherapy treated gastroesophageal cancer patients from the MAGIC Trial.Ann Oncol. 2018; Abstract Full Text Full Text PDF Scopus (27) Google Scholar]. Formaline-fixed and paraffin-embedded tumor samples from the MAGIC trial were profiled for 200 genes using the nCounter® gene expression technology (NanoString Technologies, Seattle, WA, USA). Fourteen genes associated with overall survival (OS) in the perioperative chemotherapy group were identified using penalized Cox regression analysis. Standard Cox regression analysis on the selected genes resulted eventually in a panel of seven genes, named as GC-RiskAssigner signature. This signature is prognostic only for chemotherapy patients and not for surgery only patients. When patients from the MAGIC trial were dichotomized according to their risk, significant differences were seen between the high- and low-risk groups (median OS 10.2 months versus 80.9 months). Multivariate analysis including the nodal status confirmed that the seven-gene signature is an independent prognostic factor in the chemotherapy group. Validation in an independent cohort of 47 patients from two centers confirmed the prognostic value of the GC-RiskAssigner signature. Strong points of this outstanding translational study are (i) analysis of data and material collected from a well-conducted prospective randomized controlled trial, (ii) validation of the results in an independent patient cohort, (iii) the robust nCounter® methodology to investigate the tumor transcriptome from (iv) FFPE material, which reflects current routine practice of tumor storage and, finally, (v) solid biostatistics for data analysis. Some limitations, however, exist: (i) Only 202 samples with high-quality RNA from 503 patients randomized in MAGIC were available for this study. Fortunately, there was no significant difference in OS between patients who had tissue available included in this study and those who did not, which is reassuring that samples are representative for the whole cohort. (ii) While the MAGIC study recruited mainly patients with non-cardia GC, the epidemiology has changed in the Western hemisphere where nowadays more cancers located at the esophago-gastric junction (EGJ) are seen. This raises the question if the seven-gene GC RiskAssigner signature is of value also for EGJ cancer. It is re-assuring that the validation cohort of this study was in majority composed of patients with EGJ cancer. (iii) Another moving target is the perioperative chemotherapy regimen: according to recent results [7.Al-Batran S.-E. Homann N. Schmalenberg H. et al.Perioperative chemotherapy with docetaxel, oxaliplatin, and fluorouracil/leucovorin (FLOT) versus epirubicin, cisplatin, and fluorouracil or capecitabine (ECF/ECX) for resectable gastric or gastroesophageal junction (GEJ) adenocarcinoma (FLOT4-AIO): a multicenter, randomized phase 3 trial.J Clin Oncol. 2017; 35: 4004Google Scholar], docetaxel in combination with oxaliplatin and 5-fluorouracil plus folinic acid is used for locally advanced GC in many centers. Validation of the GC RiskAssigner in a FLOT-treated patient population is warranted. (iv) The gene signature itself could be criticized as a pre-specified approach to gene selection was used. However, several of the selected genes include known candidates for predicting adverse survival outcomes in GC, including EGFR and CD44v8.10. (v) The sample size of this study is modest and (vi) investigations are based on post-surgical material alone. Ideal would be a pre-operative test to guide treatment from the beginning. But extraction of DNA and RNA from pre-chemotherapy biopsy samples is challenging and limits the applicability of molecular stratification for making pre-operative treatment decisions. Smyth et al. demonstrated that the GC RiskAsigner signature identified in post-chemotherapy resection specimens from patients with GC can help to predict prognosis in patients who have been treated with perioperative chemotherapy. Will we eventually move to multidimensional risk assessment in patients with curable GC? Nodal status pre- and post-chemotherapy, gene expression and DNA mismatch repair status are good candidates for risk stratification and personalization of pre- and postoperative therapy. Importantly, before implementation of such factors will become ready for clinical practice, findings from retrospective studies in specific patient cohorts need to be tested in prospective clinical trials. Biological validation studies and interventional trials are needed more than ever. Academic study networks have to deal with this request and should install platforms for risk- and biology-stratified studies in this disease setting. One open question at the current time is: what alternative treatment options do we have for patients in the GC RiskAssigner high-risk group? Is more intensive adjuvant therapy the way to go? Or is any novel adjuvant treatment like immunotherapy effective? The novel EORTC (European Organisation for Research and Treatment of Cancer) 7107-GITCG study (NCT 03443856) is investigating this approach, although patient selection does not yet take into account the GC RiskAssigner but could validate it. Beyond that, ex vivo models for testing chemo-sensitivity is gaining momentum [8.Vlachogiannis G. Hedayat S. Vatsiou A. et al.Patient-derived organoids model treatment response of metastatic gastrointestinal cancers.Science. 2018; 359: 920-926Crossref PubMed Scopus (842) Google Scholar, 9.Koerfer J. Kallendrusch S. Merz F. et al.Organotypic slice cultures of human gastric and esophagogastric junction cancer.Cancer Med. 2016; 5: 1444-1453Crossref PubMed Scopus (46) Google Scholar, 10.Sönnichsen R. Hennig L. Blaschke V. et al.Individual Susceptibility Analysis Using Patient-derived Slice Cultures of Colorectal Carcinoma.Clin Colorectal Cancer. 2018; 17: e189-e199Abstract Full Text Full Text PDF PubMed Scopus (18) Google Scholar]. Drugs tested effective in organoids or tumor slice cultures from pre-chemotherapy samples may be good candidates for postoperative treatment of patients at high risk of relapse. In addition, in vivo tests for drug sensitivity by sequential metabolic imaging [11.Lordick F. Ott K. Krause B.J. et al.PET to assess early metabolic response and to guide treatment of adenocarcinoma of the oesophagogastric junction: the MUNICON phase II trial.Lancet Oncol. 2007; 8: 797-805Abstract Full Text Full Text PDF PubMed Scopus (663) Google Scholar] or assessment of circulating tumor DNA [12.Hamakawa T. Kukita Y. Kurokawa Y. et al.Monitoring gastric cancer progression with circulating tumour DNA.Br J Cancer. 2015; 112: 352-356Crossref PubMed Scopus (78) Google Scholar, 13.Leal A. van Grieken N.C.T. Phallen J. et al.Circulating tumor DNA dynamics in resectable gastric cancer.J Clin Oncol. 2018; 36: 4069Crossref Google Scholar, 14.Parikh A.R. Corcoran RB. Monitoring resistance through liquid biopsy.Ann Oncol. 2018; 29: 8-11Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar] may guide future personalized risk-adapted treatment of GC. None declared.