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Abstract IA23: Variation in the immune cell infiltrate and expression of PD-L1 in sarcoma subtypes

2018· article· en· W2887696598 on OpenAlexaff
Irene L. Andrulis

Bibliographic record

VenueClinical Cancer Research · 2018
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsSinai Health SystemLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
Fundersnot available
KeywordsImmunohistochemistrySarcomaPathologyLeiomyosarcomaImmune systemImmune checkpointUndifferentiated Pleomorphic SarcomaCancer researchTumor microenvironmentMedicineSoft tissue sarcomaLiposarcomaImmunotherapyBiologyImmunology

Abstract

fetched live from OpenAlex

Abstract The presence of tumor-infiltrating lymphocytes (TILs) in the tumor microenvironment has been associated with clinical characteristics and prognosis in various cancers, although the role of TILs in sarcoma is unclear. Adult soft tissue sarcomas are a heterogeneous group of tumors that would benefit from the identification of new prognostic markers and novel therapeutic strategies. The purpose of this study was to determine whether there are specific subgroups of soft tissue sarcomas that contain TILs and/or express immune checkpoint proteins, and if so, the clinical importance. We performed immunohistochemistry (IHC) on sections from 99 tumors and found that certain soft tissue sarcomas such as leiomyosarcoma and liposarcoma exhibit little or no immune infiltrate and immune checkpoint proteins. In contrast, a subset of undifferentiated pleomorphic sarcomas (UPS) and myxofibrosarcomas contain TILs and express PD-L1 and PD-1. Evaluation of expression of PD-L1 by IHC has been controversial; however, we observed a significant positive correlation comparing the levels of PD-L1 determined by IHC on tumor sections and RT-qPCR of mRNA from quick frozen primary tumors. We detected PD-L1 expression in a well-characterized group of osteosarcomas in addition to UPS and myxofibrosarcoma. We are now integrating data from RNA-sequencing and next-generation sequencing to investigate the molecular differences in tumors with and without PD-L1 expression. These studies suggest that there may be individuals with specific sarcomas who may be good candidates to benefit from immunotherapies targeting PD-L1/PD-1 based on their tumor characteristics. Citation Format: Irene L. Andrulis. Variation in the immune cell infiltrate and expression of PD-L1 in sarcoma subtypes [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr IA23.

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)0.000
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.178
GPT teacher head0.496
Teacher spread0.318 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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