Supplementary Material for: Dynamic profiling of the immune tumor microenvironment in locally advanced gastric cancer treated with perioperative chemotherapy Article Swipe

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Irene Pecora , Clara Ugolini , Riccardo Giannini , Mirella Giordano , Caterina Vivaldi , Monica Lencioni , S. Santi , Valentina Massa , Giovanni Pallabazzer , Silvia Catanese , Francesca Salani , Belluomini M.A. , Enrico Vasile , Chiara Cremolini , Gabriella Fontanini , Gianluca Masi , Lorenzo Fornaro ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.6084/m9.figshare.23500872

Introduction: In locally advanced gastric cancer (GC), FLOT represents the standard perioperative regimen and combination with immunotherapy is under investigation. However, the role of immune tumor microenvironment (TME) is poorly recognized in this setting. We aimed to study TME characteristics and dynamics during FLOT. Methods: Paired biopsy (PRE) and surgical (POST) samples of 25 patients treated with FLOT were prospectively analyzed. After collection of clinic-pathological data, NanoString analyses were performed. The primary objective of the study was to assess the changes induced by chemotherapy in POST compared to PRE samples. Results: The unsupervised hierarchical method analysis clearly distinguished PRE and POST samples, even though some cases showed high immune gene expression at baseline. When POST samples were compared with PRE, a differential expression in hyper-expressed gene sets related to cytotoxicity, T-cell functions, complement system, tumor necrosis factor-superfamily, cell cycle and regulation was recognized. Downstaging of the primary tumor (T-regression, measured by pathologic compared to clinical T stage) was the covariate most frequently associated with these changes. Using the immune cell profiling, cases with T-regression reported a significant increase of T, CD8+ T and B-cells and a decrease in mast cells, while non-responders demonstrated an increase of T, B, cytotoxic and mast cells. Conclusion: Our analysis shows that FLOT significantly influences immune TME of GC. While relevant modifications preferentially occur in tumors showing primary tumor regression, response to treatment seems to be associated with a specific immune profile.

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Profiling (computer programming) Tumor microenvironment Medicine Chemotherapy Perioperative Immune system Cancer Oncology Cancer research Internal medicine Immunology Computer science Surgery Operating system

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Type: dataset
Language: en
Landing Page: https://doi.org/10.6084/m9.figshare.23500872
OA Status: gold
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OpenAlex ID: https://openalex.org/W4394367722

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DOI: https://doi.org/10.6084/m9.figshare.23500872

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Title: Supplementary Material for: Dynamic profiling of the immune tumor microenvironment in locally advanced gastric cancer treated with perioperative chemotherapy

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Language: en

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Publication year: 2023

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Publication date: 2023-01-01

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Authors: Irene Pecora, Clara Ugolini, Riccardo Giannini, Mirella Giordano, Caterina Vivaldi, Monica Lencioni, S. Santi, Valentina Massa, Giovanni Pallabazzer, Silvia Catanese, Francesca Salani, Belluomini M.A., Enrico Vasile, Chiara Cremolini, Gabriella Fontanini, Gianluca Masi, Lorenzo Fornaro

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Landing page: https://doi.org/10.6084/m9.figshare.23500872

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Concepts: Profiling (computer programming), Tumor microenvironment, Medicine, Chemotherapy, Perioperative, Immune system, Cancer, Oncology, Cancer research, Internal medicine, Immunology, Computer science, Surgery, Operating system

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abstract_inverted_index.complement	132
abstract_inverted_index.expression	110, 122
abstract_inverted_index.frequently	161
abstract_inverted_index.functions,	131
abstract_inverted_index.influences	209
abstract_inverted_index.pathologic	151
abstract_inverted_index.performed.	69
abstract_inverted_index.profiling,	170
abstract_inverted_index.recognized	30
abstract_inverted_index.regulation	140
abstract_inverted_index.represents	8
abstract_inverted_index.Conclusion:	202
abstract_inverted_index.Downstaging	143
abstract_inverted_index.combination	14
abstract_inverted_index.recognized.	142
abstract_inverted_index.regression,	224
abstract_inverted_index.significant	176
abstract_inverted_index.T-regression	173
abstract_inverted_index.chemotherapy	83
abstract_inverted_index.demonstrated	192
abstract_inverted_index.differential	121
abstract_inverted_index.hierarchical	93
abstract_inverted_index.unsupervised	92
abstract_inverted_index.Introduction:	0
abstract_inverted_index.cytotoxicity,	129
abstract_inverted_index.distinguished	97
abstract_inverted_index.immunotherapy	16
abstract_inverted_index.modifications	216
abstract_inverted_index.perioperative	11
abstract_inverted_index.prospectively	59
abstract_inverted_index.significantly	208
abstract_inverted_index.(T-regression,	148
abstract_inverted_index.investigation.	19
abstract_inverted_index.non-responders	191
abstract_inverted_index.preferentially	217
abstract_inverted_index.characteristics	39
abstract_inverted_index.hyper-expressed	124
abstract_inverted_index.microenvironment	26
abstract_inverted_index.clinic-pathological	64
abstract_inverted_index.factor-superfamily,	136
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	17
citation_normalized_percentile