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Abstract PR03: Genetic mechanisms of immune evasion in colorectal cancer

2018· article· en· W2905648583 on OpenAlex
Marios Giannakis, Catherine S. Grasso, Daniel K. Wells, Tsuyoshi Hamada, Xinmeng Jasmine Mu, Michael J. Quist, Jonathan A. Nowak, Reiko Nishihara, Charles M. Connolly, Sachet A. Shukla, William M. Grady, David A. Wheeler, Catherine J. Wu, Jesse M. Zaretsky, Levi A. Garraway, Thomas J. Hudson, Charles S. Fuchs, Antoni Ribas, Riki Peters, Shuji Ogino

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Immunology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsMicrosatellite instabilityLoss of heterozygosityBiologyColorectal cancerImmune checkpointImmune systemCancer researchCancerExome sequencingHuman leukocyte antigenExomeTranscriptomeImmunotherapyGeneGeneticsAntigenMutationAlleleMicrosatelliteGene expression

Abstract

fetched live from OpenAlex

Abstract Background: Immune checkpoint blockade has shown activity in microsatellite-instability high (MSI-H) colorectal cancers (CRCs). However, despite a very high mutational and neoantigen load among virtually all MSI-H tumors, the response rate is around 40-50%. In addition, for the majority of CRCs, which are microsatellite stable (MSS), immune checkpoint inhibitors have so far proven ineffective. Thus, to better understand the genetic drivers of immune evasion in CRC, we integrated next generation sequencing data from over 1200 tumors with transcriptional and immunohistochemical measures of immune infiltration. Methods: We molecularly characterized 1,211 colorectal cancers, including 592 tumors from The Cancer Genome Atlas with whole exome sequencing (WES) and whole transcriptome (RNAseq) data and 619 cancers from two prospective cohort studies with WES and immunohistochemical (IHC) annotations. To identify driver gene alterations and their selection pressures specific to MSI-high tumors, we developed a statistical method to identify significantly mutated microsatellite tracts and we further developed a method to identify copy neutral loss of heterozygosity (CN-LOH) events. We used an established immune-gene transcriptional signature as well as IHC stains against specific subsets of immune-infiltrating cells to identify genetic events associated with immune evasion. Results: We demonstrated that WNT-signaling and immune-related genes are significantly mutated in colorectal cancer. In MSI-H CRCs, we found biallelic antigen-presentation machinery (APM) mutations in the HLA Class I genes, B2M and TAP2, in addition to recurrent mutations in NLRC5 and RFX5, which downregulated HLA Class I expression. In all CRCs, we showed that WNT-signaling activity and APC-biallelic mutations are inversely associated with both transcriptional and IHC measures of T-cell infiltration. Specifically, nuclear CTNNB1 expression was inversely correlated with overall tumor-infiltrating lymphocytes (p = 0.027), CD8+ subset of T-cells (p = 0.0019) and CD45RO+ subset of T-cells (0.0080). Meanwhile, colorectal tumors with biallelic disruptive mutations in APC had a significantly decreased activated T-cell transcriptional signature (p = 4e-12) relative to samples with no disruptive mutations in APC. We further showed that in MSS tumors, AXIN2 (a key WNT-signaling effector) super-enhancer hypomethylation, independent of the APC mutation status, was further associated with decreased T-cell activity. Conclusions: In this largest CRC genomic analysis to date, we identify genetic events that are associated with immune evasion in this disease. Specifically, we find evidence of immuno-editing in MSI-H tumors through disruptive mutations in APM. In the MSS and MSI-H subtype of CRCs, we use transcriptional and immunohistochemical orthogonal analyses to demonstrate exclusion of an effective immune infiltrate in CRC through an active WNT-signaling pathway. Our results shed light on the underlying molecular mechanisms of immune exclusion in CRC and have direct implications for novel combination immunotherapy trials for patients with this disease. This abstract is also being presented as Poster B23. Citation Format: Marios Giannakis, Catherine Grasso, Daniel Wells, Tsuyoshi Hamada, Xinmeng Jasmine Mu, Michael Quist, Jonathan Nowak, Reiko Nishihara, Charles M. Connolly, Sachet Shukla, William M. Grady, David Wheeler, Catherine J. Wu, Jesse Zaretsky, Levi Garraway, Thomas Hudson, Charles Fuchs, Antoni Ribas, Riki Peters, Shuji Ogino. Genetic mechanisms of immune evasion in colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr PR03.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.074
GPT teacher head0.411
Teacher spread0.337 · 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