Literature DB >> 33678606

Differential and longitudinal immune gene patterns associated with reprogrammed microenvironment and viral mimicry in response to neoadjuvant radiotherapy in rectal cancer.

Anna Wilkins1,2, Elisa Fontana3,4, Gift Nyamundanda3, Chanthirika Ragulan3, Yatish Patil3, David Mansfield1, Jennifer Kingston5, Fiona Errington-Mais5, Daniel Bottomley5, Katharina von Loga3,6, Hannah Bye3,6, Paul Carter3,6, Emma Tinkler-Hundal5, Amir Noshirwani5, Jessica Downs7, Magnus Dillon1, Sandra Demaria8, David Sebag-Montefiore5, Kevin Harrington1, Nick West5, Alan Melcher1, Anguraj Sadanandam9.   

Abstract

BACKGROUND: Rectal cancers show a highly varied response to neoadjuvant radiotherapy/chemoradiation (RT/CRT) and the impact of the tumor immune microenvironment on this response is poorly understood. Current clinical tumor regression grading systems attempt to measure radiotherapy response but are subject to interobserver variation. An unbiased and unique histopathological quantification method (change in tumor cell density (ΔTCD)) may improve classification of RT/CRT response. Furthermore, immune gene expression profiling (GEP) may identify differences in expression levels of genes relevant to different radiotherapy responses: (1) at baseline between poor and good responders, and (2) longitudinally from preradiotherapy to postradiotherapy samples. Overall, this may inform novel therapeutic RT/CRT combination strategies in rectal cancer.
METHODS: We generated GEPs for 53 patients from biopsies taken prior to preoperative radiotherapy. TCD was used to assess rectal tumor response to neoadjuvant RT/CRT and ΔTCD was subjected to k-means clustering to classify patients into different response categories. Differential gene expression analysis was performed using statistical analysis of microarrays, pathway enrichment analysis and immune cell type analysis using single sample gene set enrichment analysis. Immunohistochemistry was performed to validate specific results. The results were validated using 220 pretreatment samples from publicly available datasets at metalevel of pathway and survival analyses.
RESULTS: ΔTCD scores ranged from 12.4% to -47.7% and stratified patients into three response categories. At baseline, 40 genes were significantly upregulated in poor (n=12) versus good responders (n=21), including myeloid and stromal cell genes. Of several pathways showing significant enrichment at baseline in poor responders, epithelial to mesenchymal transition, coagulation, complement activation and apical junction pathways were validated in external cohorts. Unlike poor responders, good responders showed longitudinal (preradiotherapy vs postradiotherapy samples) upregulation of 198 immune genes, reflecting an increased T-cell-inflamed GEP, type-I interferon and macrophage populations. Longitudinal pathway analysis suggested viral-like pathogen responses occurred in post-treatment resected samples compared with pretreatment biopsies in good responders.
CONCLUSION: This study suggests potentially druggable immune targets in poor responders at baseline and indicates that tumors with a good RT/CRT response reprogrammed from immune "cold" towards an immunologically "hot" phenotype on treatment with radiotherapy. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Entities:  

Keywords:  gastrointestinal neoplasms; gene expression profiling; immunotherapy; macrophages; tumor microenvironment

Mesh:

Year:  2021        PMID: 33678606      PMCID: PMC7939016          DOI: 10.1136/jitc-2020-001717

Source DB:  PubMed          Journal:  J Immunother Cancer        ISSN: 2051-1426            Impact factor:   13.751


  43 in total

Review 1.  Role of Local Radiation Therapy in Cancer Immunotherapy.

Authors:  Sandra Demaria; Encouse B Golden; Silvia C Formenti
Journal:  JAMA Oncol       Date:  2015-12       Impact factor: 31.777

2.  Adjusting batch effects in microarray expression data using empirical Bayes methods.

Authors:  W Evan Johnson; Cheng Li; Ariel Rabinovic
Journal:  Biostatistics       Date:  2006-04-21       Impact factor: 5.899

3.  hypeR: an R package for geneset enrichment workflows.

Authors:  Anthony Federico; Stefano Monti
Journal:  Bioinformatics       Date:  2020-02-15       Impact factor: 6.937

4.  A gene atlas of the mouse and human protein-encoding transcriptomes.

Authors:  Andrew I Su; Tim Wiltshire; Serge Batalov; Hilmar Lapp; Keith A Ching; David Block; Jie Zhang; Richard Soden; Mimi Hayakawa; Gabriel Kreiman; Michael P Cooke; John R Walker; John B Hogenesch
Journal:  Proc Natl Acad Sci U S A       Date:  2004-04-09       Impact factor: 11.205

5.  The Molecular Signatures Database (MSigDB) hallmark gene set collection.

Authors:  Arthur Liberzon; Chet Birger; Helga Thorvaldsdóttir; Mahmoud Ghandi; Jill P Mesirov; Pablo Tamayo
Journal:  Cell Syst       Date:  2015-12-23       Impact factor: 10.304

6.  Signal transducer and activator of transcription 1 regulates both cytotoxic and prosurvival functions in tumor cells.

Authors:  Nikolai N Khodarev; Andy J Minn; Elena V Efimova; Thomas E Darga; Edwardine Labay; Michael Beckett; Helena J Mauceri; Bernard Roizman; Ralph R Weichselbaum
Journal:  Cancer Res       Date:  2007-10-01       Impact factor: 12.701

7.  Inferring tumour purity and stromal and immune cell admixture from expression data.

Authors:  Kosuke Yoshihara; Maria Shahmoradgoli; Emmanuel Martínez; Rahulsimham Vegesna; Hoon Kim; Wandaliz Torres-Garcia; Victor Treviño; Hui Shen; Peter W Laird; Douglas A Levine; Scott L Carter; Gad Getz; Katherine Stemke-Hale; Gordon B Mills; Roel G W Verhaak
Journal:  Nat Commun       Date:  2013       Impact factor: 14.919

8.  The Prosigna gene expression assay and responsiveness to adjuvant cyclophosphamide-based chemotherapy in premenopausal high-risk patients with breast cancer.

Authors:  Maj-Britt Jensen; Anne-Vibeke Lænkholm; Torsten O Nielsen; Jens Ole Eriksen; Pernille Wehn; Tressa Hood; Namratha Ram; Wesley Buckingham; Sean Ferree; Bent Ejlertsen
Journal:  Breast Cancer Res       Date:  2018-07-27       Impact factor: 6.466

9.  A Novel Statistical Method to Diagnose, Quantify and Correct Batch Effects in Genomic Studies.

Authors:  Gift Nyamundanda; Pawan Poudel; Yatish Patil; Anguraj Sadanandam
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

10.  CD68- and CD163-positive tumor infiltrating macrophages in non-metastatic breast cancer: a retrospective study and meta-analysis.

Authors:  Chao Ni; Liu Yang; Qiuran Xu; Hongjun Yuan; Wei Wang; Wenjie Xia; Dihe Gong; Wei Zhang; Kun Yu
Journal:  J Cancer       Date:  2019-07-23       Impact factor: 4.207

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  3 in total

1.  Patient Derived Organoids Confirm That PI3K/AKT Signalling Is an Escape Pathway for Radioresistance and a Target for Therapy in Rectal Cancer.

Authors:  Kasun Wanigasooriya; Joao D Barros-Silva; Louise Tee; Mohammed E El-Asrag; Agata Stodolna; Oliver J Pickles; Joanne Stockton; Claire Bryer; Rachel Hoare; Celina M Whalley; Robert Tyler; Toritseju Sillo; Christopher Yau; Tariq Ismail; Andrew D Beggs
Journal:  Front Oncol       Date:  2022-07-04       Impact factor: 5.738

Review 2.  Kickstarting Immunity in Cold Tumours: Localised Tumour Therapy Combinations With Immune Checkpoint Blockade.

Authors:  Elizabeth Appleton; Jehanne Hassan; Charleen Chan Wah Hak; Nanna Sivamanoharan; Anna Wilkins; Adel Samson; Masahiro Ono; Kevin J Harrington; Alan Melcher; Erik Wennerberg
Journal:  Front Immunol       Date:  2021-10-18       Impact factor: 7.561

Review 3.  Can Radiotherapy Empower the Host Immune System to Counterattack Neoplastic Cells? A Systematic Review on Tumor Microenvironment Radiomodulation.

Authors:  Federico Iori; Alessio Bruni; Salvatore Cozzi; Patrizia Ciammella; Francesca Di Pressa; Luca Boldrini; Carlo Greco; Valerio Nardone; Viola Salvestrini; Isacco Desideri; Francesca De Felice; Cinzia Iotti
Journal:  Curr Oncol       Date:  2022-06-30       Impact factor: 3.109

  3 in total

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