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 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.

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

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 The Role of VEGFA, COX2, HUR and CUGBP2 in Predicting the Response to Neoadjuvant Therapy in Rectal Cancer Patients

Medicina ◽  
2020 ◽  
Vol 56 (4) ◽  
pp. 192
Author(s):  
Henrikas Pauzas ◽  
Ugne Gyvyte ◽  
Tadas Latkauskas ◽  
Laura Kairevice ◽  
Paulius Lizdenis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rectal Cancer ◽  
Neoadjuvant Therapy ◽  
Predictive Value ◽  
Post Treatment ◽  
Treatment Changes ◽  
Pre Treatment ◽  
Cox2 Expression ◽  
Vegfa Gene

Background and objectives: The effectiveness of neoadjuvant therapy, which is commonly used for stage II-III rectal cancer (RC) treatment, is limited. Genes associated with the pathogenesis of RC could determine response to this treatment. Therefore, the aim of this study was to investigate the potential predictive value of VEGFA, COX2, HUR and CUGBP2 genes and the associations between post-treatment changes in gene expression and the efficacy of neoadjuvant therapy. Materials and Methods: Biopsies from RC and healthy rectal tissue of 28 RC patients were collected before neoadjuvant therapy and 6-8 weeks after neoadjuvant therapy. The expression levels of VEGFA, COX2, HUR, CUGBP2 genes were evaluated using a quantitative real-time polymerase chain reaction. Results: The results reveal a significantly higher expression of VEGFA, COX2 and HUR mRNA in RC tissue compared to healthy rectal tissue (p < 0.05), and elevated VEGFA gene expression in pre-treatment tissues was associated with a better response to neoadjuvant therapy based on T-stage downstaging (p < 0.05). The expression of VEGFA, HUR and CUGBP2 genes significantly decreased after neoadjuvant therapy (p < 0.05). Responders to treatment demonstrated a significantly stronger decrease of VEGFA and COX2 expression after neoadjuvant therapy than non-responders (p < 0.05). Conclusions: The findings of this study suggest that the pre-treatment VEGFA gene expression might have predictive value for the response to neoadjuvant therapy, while the post-treatment decrease in VEGFA and COX2 gene expression could indicate the effectiveness of neoadjuvant therapy in RC patients.

Can microsatellite status of colorectal cancer (CRC) be reliably assessed after neoadjuvant therapy?

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 1525-1525
Author(s):  
Eduardo Vilar Sanchez ◽  
William Wu ◽  
Gita Bhatia ◽  
Amanda Cuddy ◽  
Maureen M. Mork ◽  
...  
Keyword(s):  
Neoadjuvant Therapy ◽  
Genomic Instability ◽  
Clinical Data ◽  
Neoadjuvant Chemoradiation ◽  
Standard Test ◽  
Post Treatment ◽  
Gold Standard Test ◽  
Pre Treatment ◽  
Msi Analysis

1525 Background: Universal testing of resected CRC for Microsatellite Instability (MSI) status has been widely advocated. While PCR-based MSI analysis is the current gold standard test, immunohistochemistry (IHC) of mismatch repair (MMR) proteins is more commonly performed. At present, it remains un-established whether PCR-based MSI analysis remains reliable when performed on post-neoadjuvant treated specimens. Our goal was to examine the effect of neoadjuvant therapy on MSI analysis using both in vitro and clinical data. Methods: MSI analysis was performed using the standard panel of 7 markers. In vitro, MMR deficient (HCT116) and proficient (HCT116+Ch3) isogenic cell lines were exposed to 3 cycles of single agent 5-Fluorouracil, Oxaliplatin and Irinotecan and MSI analysis was tested after each cycle. To evaluate the induction of genomic instability, 3 additional coding microsatellite tracts in ATR, BLM and CHK1 were assessed by fragment analysis. In parallel, clinical data from 238 CRCs that were resected after neoadjuvant chemoradiation (n=191) or chemotherapy (n=47) between 9/2009 and 8/2011 were queried for MSI results. MSI analysis performed on paired pre-treatment and post-treatment resection tissues was compared. Results: No changes in MSI status were detected and there was no increase in genomic instability post-treatment in cell line models. In the clinical setting, pre-neoadjuvant MSI testing was limited by the availability of pre-treatment biopsy tissue. 3 patients found to be MMR proficient based on MSI analysis performed on pre-treatment biopsy remained microsatellite stable when analyzed on post-treatment resection tissue. 7 patients were MMR deficient based on MSI analysis performed on post-treatment resection tissue but most had strong clinical evidence to expect MMR deficiency. Conclusions: Based on both preclinical in vitro and clinical data, results of the MSI analysis does not appear to be affected by neoadjuvant therapy for both MMR proficient and deficient cases. In addition, preclinical results do not suggest that neoadjuvant chemoradiation induces an increase in genomic instability. Therefore, MSI analysis remains a reliable gold standard test on post-treatment specimens.

Impact of neoadjuvant HER2-directed therapy on HER2 status in breast cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e12130-e12130
Author(s):  
Nicholas Manguso ◽  
Jeffrey Johnson ◽  
Reva Kakkar Basho ◽  
Heather L. McArthur ◽  
Hisashi Tanaka ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Residual Disease ◽  
Pathologic Complete Response ◽  
Residual Tumor ◽  
Her2 Status ◽  
Her2 Positive ◽  
Her2 Breast Cancer ◽  
Copy Numbers ◽  
Pre Treatment

e12130 Background: Neoadjuvant chemotherapy (NAC) with HER2-directed therapy has become standard-of-care for most women with potentially curable HER2-positive (HER2+) breast cancer and is associated with a high pathologic complete response (pCR) rate. The HER2 status of residual disease after NAC is not well characterized and could potentially inform clinical decisions about additional systemic therapy. We describe tumoral HER2 status before and after NAC with HER2-directed therapy. Methods: An institutional database was screened to identify patients with stage 1-3 HER2+ breast cancer by fluorescence in situ hybridization (FISH) and/or immunohistochemistry (IHC) who received NAC with HER2-directed therapy followed by resection between 2011 and 2015. Clinicopathologic data was collected. Change in HER2 status by FISH and IHC following treatment was described. Results: 99 patients were identified. Median age was 49 years (range 26-85). Pre-treatment median HER2/CEP17 copy number ratio (CNR) for all tumors was 6.3 (range 1.9-20.7) by FISH and 84 (84.8%) tumors were IHC 3+. 44 (44.4%) patients achieved a pCR. Of the 55 patients with residual disease, 35 had sufficient residual tumor to evaluate HER2 status and 14/35 (40%) were HER2- by FISH and IHC (table). Tumors converting from HER2+ to HER2- had lower pre-treatment median HER2 copy numbers (11.9, range 4.6-22) compared to tumors that remained HER2+ (18.3, range 5.1-48.6; p=0.04) after neoadjuvant therapy. Additionally, pre-treatment median HER2/CEP17 CNR was lower among tumors that converted from HER2+ to HER2- (3.0, range 2.2-8.2) compared to those remaining HER2+ (6.8, range 2-15.7; p=0.02). Conclusions: While pCR rates are high with NAC and HER2-directed therapy, many patients still have residual tumor. In this cohort, 40% of patients with evaluable residual disease after NAC had HER2+ tumors that became HER2-. HER2 conversion was associated with lower pre-treatment HER2 copy numbers and HER2/CEP17 CNR. Conversion from HER2+ to HER2- in patients undergoing neoadjuvant therapy may have clinical significance and biological implications. [Table: see text]

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