TMIC-14. TUMOR EVOLUTION OF GLIOMA INTRINSIC GENE EXPRESSION SUBTYPE ASSOCIATES WITH IMMUNOLOGICAL CHANGES IN THE MICROENVIRONMENT

SummaryWe leveraged IDH wild type glioblastomas and derivative neurospheres to define tumor-intrinsic transcription phenotypes. Transcriptomic multiplicity correlated with increased intratumoral heterogeneity and tumor microenvironment presence. In silico cell sorting demonstrated that M2 macrophages/microglia are the most frequent type of immune cells in the glioma microenvironment, followed by CD4 T lymphocytes and neutrophils. Hypermutation associated with CD8+ T cell enrichment. Longitudinal transcriptome analysis of 124 pairs of primary and recurrent gliomas showed expression subtype is retained in 53% of cases with no proneural to mesenchymal transition being apparent. Inference of the tumor microenvironment through gene signatures revealed a decrease in invading monocytes but a subtype dependent increase in M2 macrophages/microglia cells after disease recurrence. All expression datasets are accessible through http://recur.bioinfo.cnio.es/.SignificanceIDH wild type glioblastoma expression phenotypes have been related to tumor characteristics including genomic abnormalities and treatment response. We explored the intratumoral transcriptomic landscape, including a definition of tumor-intrinsic gene expression subtypes and how they relate to the different cellular components of the tumor immune environment. Comparison of matching primary and recurrent gliomas provided insights into the treatment-induced phenotypic tumor evolution. Proneural to mesenchymal transitions have long been suspected but were not apparent, while intratumoral heterogeneity was a predictor of subtype transition upon recurrence. Characterizing the evolving glioblastoma transcriptome en tumor microenvironment aids in designing more effective immunotherapy trials. Our study provides a comprehensive transcriptional and cellular landscape of IDH wild type GBM during treatment modulated tumor evolution.HighlightsNext generation GBM-intrinsic transcriptional subtypes: proneural, classical, mesenchymalM2 macrophages, CD4+ T-lymphocytes and neutrophils dominate glioblastoma microenvironmentSensitivity to radiotherapy may associate with M2 macrophage presenceCD8+ T cells are enriched in hypermutated GBMs at diagnosis and recurrence

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Intrinsic Gene Expression Profiles of Gliomas Are a Better Predictor of Survival than Histology

Yearbook of Neurology and Neurosurgery ◽

10.1016/s0513-5117(10)79306-6 ◽

2010 ◽

Vol 2010 ◽

pp. 113-114

Author(s):

J. Uhm

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Intrinsic Gene

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Abstract 808: Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology

10.1158/1538-7445.am10-808 ◽

2010 ◽

Author(s):

Lonneke Gravendeel ◽

Mathilde Kouwenhoven ◽

Olivier Gevaert ◽

Johan de Rooi ◽

Andrew Stubbs ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Intrinsic Gene

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“Intrinsic Gene Expression” subtypes correlated with grade and morphometric parameters reveal a high proportion of aggressive basal-like tumors among black women of African ancestry

Journal of Clinical Oncology ◽

10.1200/jco.2004.22.14_suppl.9509 ◽

2004 ◽

Vol 22 (14_suppl) ◽

pp. 9509-9509 ◽

Cited By ~ 5

Author(s):

O. I. Olopade ◽

F. O. Ikpatt ◽

J. J. Dignam ◽

A. Khramtsov ◽

M. Tetriakova ◽

...

Keyword(s):

Gene Expression ◽

Black Women ◽

African Ancestry ◽

Morphometric Parameters ◽

Intrinsic Gene

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Confirmation of the distinct molecular phenotype of inflammatory breast cancer compared to non-inflammatory breast cancer using Affymetrix-based genome-wide gene expression analysis

Journal of Clinical Oncology ◽

10.1200/jco.2007.25.18_suppl.21055 ◽

2007 ◽

Vol 25 (18_suppl) ◽

pp. 21055-21055

Author(s):

S. J. Van Laere ◽

I. Van der Auwera ◽

G. G. Van den Eynden ◽

X. Trinh ◽

P. Van Hummelen ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Gene Expression Profile ◽

Expression Profile ◽

Inflammatory Breast Cancer ◽

Principle Component Analysis ◽

Expression Data ◽

Data Set ◽

Principle Component ◽

Intrinsic Gene

21055 Background: We have shown with cDNA microarrays that inflammatory breast cancer (IBC) and non-IBC are distinct biological entities. The purpose of this study was to confirm our previous results using Affymetrix chips. Methods: RNA was extracted from 19 IBC samples and 42 non-stage matched non-IBC samples. RNA was hybridized onto Affymetrix HG U133 Plus 2.0 chips. Gene expression data were normalized using GCRMA and genes with a gene expression of at least 250 in 50% of the cases were filtered in. Hierarchical clustering and principle component analysis was executed. Identification of the different cell-of-origin subtypes in our expression data set was done using the intrinsic gene list. A NFkB signature, a MAPK signature and our own IBC signature were tested by clustering analysis. Results: Clustering using 11341 genes resulted in the identification of two clusters: one containing 14/19 IBC samples and a second containing 32/42 non-IBC (Pearson χ2; p<0.0001). Principle component analysis separated IBC from non-IBC samples along the first principle component. Interestingly, IBC samples more closely resemble T1 - T2 tumours than T3 - T4 tumours. Application of the intrinsic gene set to our IBC/non-IBC data set resulted in the classification of 14/19 IBC samples as basal-like or ErbB2-overexpressing tumours compared to only 4/42 non-IBC tumours (Pearson χ2; p<0.0001). Our own IBC signature was confronted with the new data set and performed well in separating IBC specimens form non-IBC specimens. Clustering identified three clusters from which one cluster contained 18 samples, including 12 IBC specimens (p<0.0001). Using the NFkB and MAPK signatures, similar results were obtained. Conclusions: These results confirm our findings that IBC is a distinct biologic phenotype, characterized by activation of NFkB, possibly through activation of MAPK's. IBC tumours more often demonstrate characteristics from basal-like and ErbB2-overexpressing breast tumours. The fact that IBC tumours are rapidly developing tumours instead of longstanding tumourigenic processes might explain the close resemblance of the IBC gene expression profile to the gene expression profile of T1 and T2 tumours. No significant financial relationships to disclose.

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Immune- and tumor-intrinsic gene expression profiles of response or resistance to tislelizumab as monotherapy or in combination with chemotherapy in non-small cell lung cancer (NSCLC).

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e15258 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e15258-e15258

Author(s):

Jayesh Desai ◽

Jie Wang ◽

Qing Zhou ◽

Jun Zhao ◽

Sanjeev Deva ◽

...

Keyword(s):

Gene Expression ◽

Dna Repair ◽

Clinical Benefit ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Rank Test ◽

M2 Macrophage ◽

Intrinsic Factors ◽

Expression Of Genes ◽

Intrinsic Gene

e15258 Background: Tislelizumab, an anti-PD-1 monoclonal antibody, showed clinical benefit for patients (pts) with NSCLC alone (NCT02407990, CTR20160872) and in combination with chemotherapy (NCT03432598). Gene expression profiles (GEP) associated with response and resistance to tislelizumab in these studies were assessed. Methods: The GEP of baseline tumor samples from 59 nonsquamous (NSQ) and 42 squamous (SQ) NSCLC pts treated with tislelizumab monotherapy (mono) as ≥1L treatment, and 16 NSQ and 21 SQ pts treated with tislelizumab plus chemotherapy (combo) as 1L treatment were assessed using the 1392-gene HTG GEP EdgeSeq panel. NSQ and SQ cohorts were analyzed separately due to distinct GEP features shown by PCA and t-SNE clustering. Results: Tislelizumab mono and combo showed antitumor activity in NSCLC (Table). In 80 biomarker-evaluable samples, inflamed tumor signatures (inflammatory GEP; antigen presentation GEP) were associated with longer overall survival (log-rank test, NSQ mono: P=0.04, 0.003; NSQ combo: P=0.05, 0.02; SQ combo: P=0.06, 0.06). Monotherapy non-responders (NRs) were clustered into 2 subgroups (NR1, NR2) with distinct GEPs. Compared with responders, NR1 had proliferation signatures (elevated cell cycle [CC] and DNA repair) in both NSQ ( P=0.2, 0.02) and SQ ( P=0.03, 0.4) cohorts, trending toward low inflamed tumor signatures. In NR pts receiving combo, CC and DNA repair signatures were not enriched, and high CC and DNA repair scores were observed in some SQ combo responders versus NRs ( P=0.2, 0.02). NR2 had higher M2 macrophage and Treg cell signatures versus responders in both NSQ and SQ mono, despite high inflamed tumor and low proliferation signatures. NR2 also had increased expression of genes related to immune regulation and angiogenesis, including PIK3CD, CCR2, CD244, IRAK3, and MAP4K1 ( P<0.05) in NSQ, and PIK3CD, CCR2, CD40, CD163, MMP12, VEGFC, and TEK ( P<0.05) in SQ. Conclusions: Clinical benefit in pts with NSCLC receiving tislelizumab (mono or combo) was associated with high inflamed tumor signatures, while elevated immune suppressive cell signatures may indicate resistance. High proliferation signatures were associated with resistance to monotherapy, but not to combination therapy. Both immune- and tumor-intrinsic factors may be considered for validation in future clinical trials. [Table: see text]

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Genomic characterization of preclinical models derived from primary and metastatic sites from rapid autopsy patients in PDMR.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e13506 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e13506-e13506

Author(s):

Li Chen ◽

Rajesh Patidar ◽

Biswajit Das ◽

Yvonne A Evrard ◽

Chris Alan Karlovich ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Driver Mutations ◽

Tumor Evolution ◽

Preclinical Model ◽

Expression Data ◽

Preclinical Models ◽

Rapid Autopsy ◽

Metastatic Sites ◽

Pdx Models

e13506 Background: The National Cancer Institute has developed a repository of preclinical models [Patient-Derived Models Repository (NCI PDMR, https://pdmr.cancer.gov )] including patient derived xenografts (PDXs), organoids (PDOrgs) and in vitro tumor cultures (PDCs) from patients with solid tumor cancer histologies. A subset of these preclinical models is derived from post-mortem collections from rapid autopsies representing the end point in disease progression. Clinical annotations and genomic datasets associated with these models provide a unique opportunity to study tumor evolution, mechanistic insights into the metastatic process, and treatment resistance. Methods: To date, 43 PDXs, 21 PDCs, and 23 PDOrgs using rapid autopsy specimens from 8 primary and 35 metastatic sites of 18 patients have been developed by the Biological Testing Branch (DTP, DCTD, NCI Frederick, MD) for the PDMR. Whole exome (WES) and total transcriptome (RNASeq) data were processed to generate mutation, copy number alteration (CNA) and gene expression data. Multi-model lineage trees were reconstructed based on putative somatic variants for all the models derived from all patients. The fraction of the genome affected by CNA was compared both within and across PDX models. Results: Most of the rapid autopsy PDX models (32/43) are derived from pancreatic adenocarcinoma (PAAD) patients (13/18), with metastatic specimens originating from sites including liver, colon, omentum, and lung. Driver mutations are present in all preclinical model specimens derived from the same patient. For instance, KRAS p.G12D is present in all patient-derived model specimens derived from PAAD patient 521955. The fraction of the genome affected by CNA remains stable within a PDX model across passages (n = 24, mean = 6.39%, sd = 5.90%). However, we found that this increased when comparing PDX models derived from metastatic sites versus the primary site (n = 19, mean = 16.92%, sd = 10.46%). This indicates presence of tumor heterogeneity between metastatic and primary sites. The lineage tree for models from patient 521955 indicates that one liver metastasis has a unique seeding event compared to the other 4 metastatic sites. Unsupervised clustering analysis on gene expression data also confirms the observed tumor site relationships. Conclusions: Our data demonstrate the potential use of these preclinical models available from the NCI PDMR. These models provide a unique resource for preclinical studies in tumor evolution, metastatic spread mediators, and drug resistance.

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