scholarly journals Oesophageal adenocarcinoma: In the era of extended lymphadenectomy, is the value of neoadjuvant therapy being attenuated?

2021 ◽  
Vol 13 (10) ◽  
pp. 1235-1244
Author(s):  
Jin-Soo Park ◽  
Hans Van der Wall ◽  
Catherine Kennedy ◽  
Gregory L Falk
Keyword(s):  
Neoadjuvant Therapy ◽  
Oesophageal Adenocarcinoma ◽  
Extended Lymphadenectomy

scholarly journals O7: APPARENT PATHOLOGICAL COMPLETE RESPONSE TO NEOADJUVANT THERAPY LEADS TO SELECTION OF TREATMENT RESISTANT CANCER STEM CELLS IN OESOPHAGEAL ADENOCARCINOMA

2021 ◽  
Vol 108 (Supplement_1) ◽  
Author(s):  
RC Walker ◽  
J Harrington ◽  
B Grace ◽  
M Lloyd ◽  
JP Byrne ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cancer Cells ◽  
Neoadjuvant Therapy ◽  
Rna Sequencing ◽  
Pathological Complete Response ◽  
Complete Response ◽  
Oesophageal Adenocarcinoma ◽  
Cell Populations ◽  
Stem Cell Markers ◽  
Resistance To Therapy

Abstract Introduction In oesophageal adenocarcinoma with an apparent pathological complete response (pCR) to neoadjuvant therapy (NAT) there remains debate as to whether oesophagectomy is required. Single Cell RNA sequencing (scRNAseq) enables identification and characterisation of cell populations at higher resolution than diagnostic techniques. Method ScRNAseq was used to determine transcriptomic profiles of cell populations in 24 OAC tumours and 13 matched normal samples. Five were also analysed using bulk RNA sequencing and high-precision mass spectrometry proteomics. Immunohistochemistry (IHC) was used to validate pCR. Paired scRNAseq analysis of pre-and post-treatment specimens from three further patients was used to compare transcriptomic profiles before and after NAT. Cancer cells (CCs) were assigned a cancer stem cell (CSC) score curated from published gene sets. Result We analysed a total of 22,738 single cells forming 29 different cell phenotypes. In two samples with apparent pCR, IHC staining, bulk RNA sequencing and proteomics of post-treatment samples failed to identify CCs. ScRNAseq, conversely, revealed persistent CCs (12/978 and 45/774). Transcriptomic analysis identified upregulation of stem cell markers and high CSC scores in these cells. Conclusion We have shown that CCs persist beneath the lower detection limit of standard approaches in apparent pCR. These cells express marker genes and expression programs consistent with CSCs. CSCs are a critical subpopulation that drive tumour initiation, growth, invasion, metastasis and resistance to therapy. These gene expression programs are not enriched in non-responders and straight to surgery samples. Oesophagus sparing treatment algorithms in pCR may subject patients to unnecessary risk of progression. Take-home message Cancer cells remain within tumours after apparent complete pathological response. These cells express stem cell markers associated with resistance to therapy and cancer progression.

scholarly journals Prospective cohort study of neoadjuvant therapy toxicity in the treatment of oesophageal adenocarcinoma

2018 ◽  
Vol 52 ◽  
pp. 126-130
Author(s):  
David Bunting ◽  
Richard Berrisford ◽  
Tim Wheatley ◽  
Lee Humphreys ◽  
Arun Ariyarathenam ◽  
...  
Keyword(s):  
Cohort Study ◽  
Neoadjuvant Therapy ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Oesophageal Adenocarcinoma

Predicting response to neoadjuvant therapy using image capture from diagnostic biopsies of oesophageal adenocarcinoma

2021 ◽  
Vol 47 (1) ◽  
pp. e4
Author(s):  
Saqib Rahman ◽  
Joe Early ◽  
Matt De Vries ◽  
Megan Lloyd ◽  
Ben Grace ◽  
...  
Keyword(s):  
Neoadjuvant Therapy ◽  
Oesophageal Adenocarcinoma ◽  
Image Capture ◽  
Diagnostic Biopsies

scholarly journals O29: PREDICTING RESPONSE TO NEOADJUVANT THERAPY IN OESOPHAGEAL ADENOCARCINOMA PRE-TREATMENT BIOPSIES

2021 ◽  
Vol 108 (Supplement_1) ◽  
Author(s):  
M Lloyd ◽  
F Izadi ◽  
S Rahman ◽  
R Walker ◽  
A Hayden ◽  
...  
Keyword(s):  
Pilot Study ◽  
Neoadjuvant Therapy ◽  
Small Sample Size ◽  
Expression Profiles ◽  
Locally Advanced ◽  
Small Sample ◽  
Oesophageal Adenocarcinoma ◽  
Tumour Regression ◽  
Precision Therapy ◽  
Pre Treatment

Abstract Aims We currently cannot predict which patients with locally advanced oesophageal adenocarcinoma will be amongst the 15-20% to gain a clinically important response to neoadjuvant therapy (NAT). This pilot study aimed to identify differentially expressed genes from oesophageal adenocarcinoma pre-treatment biopsies between responders and non-responders to NAT and develop methodology for predicting response. Method Response to NAT was assessed pathologically using Tumour Regression Grading (TRG). Pre-treatment formalin-fixed paraffin embedded samples were analysed with two nuclease protection assays (EdgeSeq, HTG = Oncology Biomarker Panel (OBP) and Precision Immuno-Oncology Panel (PIP)). Sequencing was performed on the NextSeq500 (Illumina). Result Whilst there was no difference in pre-treatment characteristics, responders (TRG1-2, n=26) had significantly better post-treatment pathology and overall survival than non-responders (TRG4-5, n=30). Genes up-regulated in responders were involved in regulating cell cycling, whereas genes up-regulated in non-responders were involved in cytokine signalling and the immune response. Neuronal artificial network models could predict response to NAT with overall accuracy of 73% and 68% for the OBP and PIP, respectively, which is promising considering the small sample size. As no model will be 100% accurate, we developed a model that could take patient's views into consideration with an adjustable probability threshold for classification. Conclusion This pilot study informs a biologically sound hypothesis for the basis of response to NAT and suggests prediction from pre-treatment biopsies may be possible using EdgeSeq. We now aim to validate these results in a larger study to inform a bespoke classifier of response to enable delivery of precision therapy. Take-home message In oesophageal adenocarcinoma, responders and non-responders to neoadjuvant therapy have different expression profiles. Through using EdgeSeq in larger studies, we may be able to predict which patients will respond to treatment, allowing for delivery of precision therapy.

FA06.03: THE EFFECT OF LYMPH NODE HARVEST UPON MORTALITY FROM OESOPHAGECTOMY FOR OESOPHAGEAL ADENOCARCINOMA: NATIONAL POPULATION-BASED COHORT STUDY

2018 ◽  
Vol 31 (Supplement_1) ◽  
pp. 12-12
Author(s):  
Sheraz Markar ◽  
Mira Varagunam ◽  
Hugh Mackenzie ◽  
Christian Brand ◽  
David Cromwell ◽  
...  
Keyword(s):  
Cohort Study ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Neoadjuvant Therapy ◽  
Conflicts Of Interest ◽  
Population Based ◽  
Change Points ◽  
Oesophageal Adenocarcinoma ◽  
Lymph Node Harvest ◽  
National Population

Abstract Background In an era of increased utilisation of multimodality treatment for oesophageal adenocarcinoma the role of radical lymphadenectomy remains controversial. The objectives of this population-based cohort study were to evaluate the influence of lymph node harvest upon short- and long-term mortality following oesophagectomy for oesophageal adenocarcinoma, with subset analysis of patients receiving neoadjuvant therapy. Methods The UK National Oesophago-Gastric Cancer Audit (NOGCA) was used to identify suitable patients operated on between 1st April 2012 and 31st March 2016. Logistic regression of confounders was used to generate predicted mortality probabilities for utilisation in Risk-Adjusted Cumulative Sum (RA-CUSUM) analysis to identify the lymph node harvest change-points associated with changes in one-, two- and three-year mortality. Results Within the three-year study period, 3883 patients were included of these 2192 patients (56%) received neoadjuvant chemotherapy. For all patients there were non-significant change-points in 1-, 2-, and 3-year mortality at 19, 27 and 19 lymph nodes respectively. For patients receiving neoadjuvant therapy change-point analysis did show statistically significant reductions in 2-year mortality (44.9% before to 39.2% after 19 lymph nodes; P = 0.017) and 3-year mortality (55.0% before to 47.4% after 20 lymph nodes; P = 0.035). 30-day and 90-day mortality and anastomotic leak were not significantly by lymph node harvest of greater than 19 lymph nodes. Conclusion The results of this national population-based cohort study suggest that at least 20 lymph nodes should be harvested during oesophagectomy given the prognostic importance in oesophageal adenocarcinoma, and the benefits to improve pathological staging of the patient and appropriately allocate adjuvant therapy. Disclosure All authors have declared no conflicts of interest.

Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma Pre-Treatment Biopsies

2019 ◽  
Vol 45 (11) ◽  
pp. 2212
Author(s):  
Megan Lloyd ◽  
Fereshteh Izadi ◽  
Rob Walker ◽  
Annette Hayden ◽  
Jack Harrington ◽  
...  
Keyword(s):  
Neoadjuvant Therapy ◽  
Oesophageal Adenocarcinoma ◽  
Pre Treatment

scholarly journals O4 Neural network image capture to predict response of oesophageal adenocarcinoma to neoadjuvant therapy

2021 ◽  
Vol 108 (Supplement_5) ◽  
Author(s):  
S Rahman ◽  
J Early ◽  
B Sharpe ◽  
M Lloyd ◽  
B Grace ◽  
...  
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Neoadjuvant Therapy ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Oesophageal Adenocarcinoma ◽  
Tumour Regression ◽  
Tumour Regression Grade ◽  
Pre Treatment ◽  
Diagnostic Biopsies

Abstract Introduction Locally advanced oesophageal adenocarcinoma is typically treated with neoadjuvant chemotherapy (NACT) or chemoradiotherapy (NACRT) followed by surgery. Significant benefit to neoadjuvant treatment however is confined to a minority of patients (<25%) and there are no reliable means of establishing prior to treatment in whom this benefit will occur. In this study, we assessed the utility of features extracted from high-resolution digital microscopy of pre-treatment biopsies in predicting response to neoadjuvant therapy in a machine-learning based modelling framework. Method A total of 102 cases were included in the study. Pre-treatment clinical information, including TNM staging, was obtained, along with diagnostic biopsies. Diagnostic biopsies were converted into high-resolution whole slide-images and features extracted using a pre-trained convolutional neural network (Xception). Elastic net regression models were then trained and validated with bootstrapping with 1000 resampled datasets. The response was considered according to Mandard tumour regression grade (TRG). Result There were 45 (44.1%) responders (TRG1-2) and 57 (57%) non-responders (TRG3-5) in the dataset. 34 patients (33.3%) received NACT and 68 (66.7%) received NACRT. A model trained with RNA-seq data achieved fair performance only in predicting response (AUC 0.598 95% CI 0.593–0.603), which was far exceeded by use of segmented diagnostic biopsy images (AUC 0.872 95% CI 0.869–0.875), which also produced well calibrated predictions of risk. Conclusion Despite using a small dataset, impressive performance in classifying response to neoadjuvant treatment can be achieved, particularly using automated image classification. Further study to refine the methodology is required before expansion to clinical settings. Take-home Message Response to neoadjuvant treatment for oesophageal cancer can be predicted from diagnostic biopsies

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