MétaCan
Menu
Back to cohort

Abstract B048: Multiplex analysis of pancreatic, oesophageal and rectal adenocarcinoma: A cross-cancer approach on the impact of neoadjuvant therapy on the tumour microenvironment

2023· article· en· W4389241582 on OpenAlexaboutno aff
Leonard Richter

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
Fundersnot available
KeywordsTumor microenvironmentMedicineFOXP3Stromal cellPancreatic cancerImmune systemCancer researchCD8ImmunotherapyTumor-infiltrating lymphocytesColorectal cancerPathologyCancerImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction: The prognosis of gastrointestinal malignancies has improved significantly with the introduction of neoadjuvant therapy (neoTx). For rectal (RCa) and esophageal adenocarcinoma (OCa), neoTx has become the standard of care, resulting in tumor-downsizing and significantly prolonged patient survival. However, the effects of neoTx on the topographical interactions between different populations of tumor-infiltrating immune cells, the degree of intratumoral immune infiltration, the distance to tumor cells, as well as their spatial interactions with other important features of the tumor microenvironment (TME), are still unknown. In this cross-cancer histopathological profiling of the microenvironment of rectal and esophageal tumors, we aim to investigate the local effects of cytotoxic agents and determine whether these correspond to the pathological changes observed in pancreatic cancer (PCa). Methods In this study, we employed multiplex immunohistochemistry (mIHC) based on tyramide signal amplification (TSA) using OPAL® dyes and a customized 6-plex approach to characterize tumor-associated stromal features (CD11c, CD34, NCAM, PGP9.5, aSMA, PanCK) as well as tumor-infiltrating lymphoid (CD3, CD4, CD8, CD20, FOXP3, PanCK) and myeloid cell subsets (CD11b, CD33, CD68, CD208, HLA-DR, PanCK). FFPE samples from 60 neoadjuvantly treated RCa and 40 OCa patients and a matched cohort of primary resected patients were included in the analysis. Results In PCa, neoTx alters the TME by depleting pro-tumorigenic immune cells, such as myeloid-derived suppressor cells (MDSC) and regulatory T cells, and suppressing tumor-associated stromal activation, neural invasion, and microangiogenesis. In our current study, we generated three standardized 6-plex panels for comprehensive histopathologic analysis of the immune architecture and associated stromal features of neoadjuvantly treated RCa and OCa patients compared with primary resected patients. Lymphoid subpopulations included Th-cells, cytotoxic T-cells, regulatory T-cells, and B-cells, while MDSC, dendritic cells, M1- and M2-macrophages were analyzed in the myeloid panel within the same FFPE slide. Conclusion: Our findings highlight new differential cell identities in neoTx-treated PCa patients and confirm their suitability for optimizing future clinical immunotherapy trials. Our current approach validates multiplex-IHC approaches for histological profiling of FFPE tumor samples in RCa and OCa and demonstrates the importance of a deep topographic characterization to understand the TME composition of gastrointestinal malignancies after neoTx. Citation Format: Leonard Richter. Multiplex analysis of pancreatic, oesophageal and rectal adenocarcinoma: A cross-cancer approach on the impact of neoadjuvant therapy on the tumour microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B048.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.112
GPT teacher head0.412
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCancer Immunology ResearchSame topicCancer Immunotherapy and BiomarkersFrench-language works237,207