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Record W4408465074 · doi:10.1101/2025.03.10.642301

Aberrant NOTUM+ Program Induced in LGR5+ Crypt Base Columnar Cells Maintains an Immunosuppressive Niche in Colorectal Cancer

2025· preprint· en· W4408465074 on OpenAlexaff
Julian Chua, Arshdeep Kaur, Elleine Allapitan, Oliver F. Bathe, Parham Minoo, Arshad Ayyaz

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicColorectal and Anal Carcinomas
Canadian institutionsAlberta Children's HospitalAlberta Bone and Joint Health InstituteUniversity of CalgaryOntario Institute for Cancer Research
Fundersnot available
KeywordsLGR5CryptColorectal cancerNicheBase (topology)Aberrant crypt fociBiologyCancer researchCancerGeneticsColonic diseaseEcologyEndocrinologyMathematics

Abstract

fetched live from OpenAlex

Abstract Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, with treatment failure largely driven by cancer stem-like cells that resist conventional chemoradiation and subsequently initiate tumor recurrence. While immune checkpoint blockade is effective in microsatellite instability-high (MSI-H) CRCs, the majority of CRCs are microsatellite stable (MSS) and exhibit immune exclusion, rendering them refractory to immunotherapy. Here, we identify a previously uncharacterized cancer cell subtype, which we term cancerous Crypt Base Columnar (canCBC) cells. These cells transcriptionally resemble normal LGR5+ CBC cells but activate an aberrant WNT/β-catenin signalling inhibitory program, marked by NOTUM expression. We show that canCBC cells are specifically enriched in MSS tumors, where their presence correlates with reduced CD8⁺ T cell infiltration, broader immune exclusion, and a propensity for regional lymphatic dissemination. Consistently, targeted ablation of canCBCs enhances the tumor-clearing potential of CD8⁺ T cells. This study identifies a novel therapeutic target for overcoming immune exclusion and improving immunotherapy responses in MSS CRCs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicColorectal and Anal CarcinomasFrench-language works237,207