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Record W4220720369 · doi:10.3389/fimmu.2022.840198

Desmoplastic Reaction, Immune Cell Response, and Prognosis in Colorectal Cancer

2022· article· en· W4220720369 on OpenAlexfundno aff
Naohiko Akimoto, Juha P. Väyrynen, Melissa Zhao, Tomotaka Ugai, Kenji Fujiyoshi, Jennifer Borowsky, Rong Zhong, Koichiro Haruki, Kota Arima, Mai Chan Lau, Junko Kishikawa, Tyler S. Twombly, Yasutoshi Takashima, Mingyang Song, Xuehong Zhang, Kana Wu, Andrew T. Chan, Jeffrey A. Meyerhardt, Marios Giannakis, Jonathan A. Nowak, Shuji Ogino

Bibliographic record

VenueFrontiers in Immunology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
FundersGary Bennett Family FundNational Institutes of HealthHuazhong University of Science and TechnologyNational Cancer InstituteEntertainment Industry FoundationMitsukoshi Health and Welfare FoundationAmerican Association for Cancer ResearchAmerican Society of Clinical OncologyMassachusetts General HospitalConquer Cancer FoundationJapan Society for the Promotion of ScienceAmerican Cancer SocietyResearch Promotion FoundationStand Up To CancerUehara Memorial Foundation
KeywordsImmune systemColorectal cancerMedicineImmune reactionCancer researchOncologyImmunologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Background The relationships between tumor stromal features (such as desmoplastic reaction, myxoid stroma, and keloid-like collagen bundles) and immune cells in the colorectal carcinoma microenvironment have not yet been fully characterized. Methods In 908 tumors with available tissue among 4,465 incident colorectal adenocarcinoma cases in two prospective cohort studies, we examined desmoplastic reaction, myxoid stroma, and keloid-like collagen bundles. We conducted multiplex immunofluorescence for T cells [CD3, CD4, CD8, CD45RO (PTPRC), and FOXP3] and for macrophages [CD68, CD86, IRF5, MAF, and MRC1 (CD206)]. We used the inverse probability weighting method and the 4,465 incident cancer cases to adjust for selection bias. Results Immature desmoplastic reaction was associated with lower densities of intraepithelial CD3+CD8+CD45RO+ cells [multivariable odds ratio (OR) for the highest (vs. lowest) density category, 0.43; 95% confidence interval (CI), 0.29–0.62; Ptrend <0.0001] and stromal M1-like macrophages [the corresponding OR, 0.44; 95% CI, 0.28–0.70; Ptrend = 0.0011]. Similar relations were observed for myxoid stroma [intraepithelial CD3+CD8+CD45RO+ cells (Ptrend <0.0001) and stromal M1-like macrophages (Ptrend = 0.0007)] and for keloid-like collagen bundles (Ptrend <0.0001 for intraepithelial CD3+CD8+CD45RO+ cells). In colorectal cancer-specific survival analyses, multivariable-adjusted hazard ratios (with 95% confidence intervals) were 0.32 (0.23–0.44; Ptrend <0.0001) for mature (vs. immature) desmoplastic reaction, 0.25 (0.16–0.39; Ptrend <0.0001) for absent (vs. marked) myxoid stroma, and 0.12 (0.05–0.28; Ptrend <0.0001) for absent (vs. marked) keloid-like collagen bundles. Conclusions Immature desmoplastic reaction and myxoid stroma were associated with lower densities of tumor intraepithelial memory cytotoxic T cells and stromal M1-like macrophages, likely reflecting interactions between tumor, immune, and stromal cells in the colorectal tumor microenvironment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations30
Published2022
Admission routes1
Has abstractyes

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