Typing of pancreatic cancer-associated fibroblasts identifies different subpopulations.

World J Gastroenterol.

2018 Nov 09

Nielsen MFB, Mortensen MB, Detlefsen S.
PMID: 30416314 | DOI: 10.3748/wjg.v24.i41.4663

Abstract

AIM:

To determine whether it is possible to identify different immune phenotypic subpopulations of cancer-associated fibroblasts (CAFs) in pancreatic cancer (PC).

METHODS:

We defined four different stromal compartments in surgical specimens with PC: The juxtatumoural, peripheral, lobular and septal stroma. Tissue microarrays were produced containing all pre-defined PC compartments, and the expression of 37 fibroblast (FB) and 8 extracellular matrix (ECM) markers was evaluated by immunohistochemistry, immunofluorescence (IF), double-IF, and/or in situ hybridization. The compartment-specific mean labelling score was determined for each marker using a four-tiered scoring system. DOG1 gene expression was examined by quantitative reverse transcription PCR (qPCR).

RESULTS:

CD10, CD271, cytoglobin, DOG1, miR-21, nestin, and tenascin C exhibited significant differences in expression profiles between the juxtatumoural and peripheral compartments. The expression of CD10, cytoglobin, DOG1, nestin, and miR-21 was moderate/strong in juxtatumoural CAFs (j-CAFs) and barely perceptible/weak in peripheral CAFs (p-CAFs). The upregulation of DOG1 gene expression in PC compared to normal pancreas was verified by qPCR. Tenascin C expression was strong in the juxtatumoural ECM and barely perceptible/weak in the peripheral ECM. CD271 expression was barely perceptible in j-CAFs but moderate in the other compartments. Galectin-1 was stronger expressed in j-CAFs vs septal fibroblasts, PDGF-Rβ, tissue transglutaminase 2, and hyaluronic acid were stronger expressed in lobular fibroblasts vs p-CAFs, and plectin-1 was stronger expressed in j-CAFs vs l-FBs. The expression of the remaining 33 markers did not differ significantly when related to the quantity of CAFs/FBs or the amount of ECM in the respective compartments.

CONCLUSION:

Different immune phenotypic CAF subpopulations can be identified in PC, using markers such as cytoglobin, CD271, and miR-21. Future studies should determine whether CAF subpopulations have different functional properties.

Modelling TGFβR and Hh pathway regulation of prognostic matrisome molecules in ovarian cancer

iScience

2021 May 01

Delaine-Smith, R;Maniati, E;Malacrida, B;Nichols, S;Roozitalab, R;Jones, R;Lecker, L;Pearce, O;Knight, M;Balkwill, F;
| DOI: 10.1016/j.isci.2021.102674

In a multi-level ‘deconstruction’ of omental metastases, we previously identified a prognostic matrisome gene expression signature in high-grade serous ovarian cancer (HGSOC) and twelve other malignancies. Here, our aim was to understand how six of these extracellular matrix, ECM, molecules, COL11A1, COMP, FN1, VCAN, CTSB and COL1A1, are up-regulated in cancer. Using biopsies, we identified significant associations between TGFβR activity, Hedgehog signalling and these ECM molecules and studied the associations in mono-, co- and tri-culture. Activated omental fibroblasts produced more matrix than malignant cells, directed by TGFβR and Hedgehog signalling crosstalk. We ‘reconstructed’ omental metastases in tri-cultures of HGSOC cells, omental fibroblasts and adipocytes. This combination was sufficient to generate all six ECM proteins and the matrisome expression signature. TGFβR and Hedgehog inhibitor combinations attenuated fibroblast activation, gel and ECM remodelling in these models. The tri-culture model reproduces key features of omental metastases and allows study of diseased-associated ECM.

Integrated multi-omics reveals cellular and molecular interactions governing the invasive niche of basal cell carcinoma

Nature communications

2022 Aug 20

Yerly, L;Pich-Bavastro, C;Di Domizio, J;Wyss, T;Tissot-Renaud, S;Cangkrama, M;Gilliet, M;Werner, S;Kuonen, F;
PMID: 35986012 | DOI: 10.1038/s41467-022-32670-w

Tumors invade the surrounding tissues to progress, but the heterogeneity of cell types at the tumor-stroma interface and the complexity of their potential interactions hampered mechanistic insight required for efficient therapeutic targeting. Here, combining single-cell and spatial transcriptomics on human basal cell carcinomas, we define the cellular contributors of tumor progression. In the invasive niche, tumor cells exhibit a collective migration phenotype, characterized by the expression of cell-cell junction complexes. In physical proximity, we identify cancer-associated fibroblasts with extracellular matrix-remodeling features. Tumor cells strongly express the cytokine Activin A, and increased Activin A-induced gene signature is found in adjacent cancer-associated fibroblast subpopulations. Altogether, our data identify the cell populations and their transcriptional reprogramming contributing to the spatial organization of the basal cell carcinoma invasive niche. They also demonstrate the power of integrated spatial and single-cell multi-omics to decipher cancer-specific invasive properties and develop targeted therapies.

Spatially organized multicellular immune hubs in human colorectal cancer

Cell

2021 Aug 24

Pelka, K;Hofree, M;Chen, JH;Sarkizova, S;Pirl, JD;Jorgji, V;Bejnood, A;Dionne, D;Ge, WH;Xu, KH;Chao, SX;Zollinger, DR;Lieb, DJ;Reeves, JW;Fuhrman, CA;Hoang, ML;Delorey, T;Nguyen, LT;Waldman, J;Klapholz, M;Wakiro, I;Cohen, O;Albers, J;Smillie, CS;Cuoco, MS;Wu, J;Su, MJ;Yeung, J;Vijaykumar, B;Magnuson, AM;Asinovski, N;Moll, T;Goder-Reiser, MN;Applebaum, AS;Brais, LK;DelloStritto, LK;Denning, SL;Phillips, ST;Hill, EK;Meehan, JK;Frederick, DT;Sharova, T;Kanodia, A;Todres, EZ;Jané-Valbuena, J;Biton, M;Izar, B;Lambden, CD;Clancy, TE;Bleday, R;Melnitchouk, N;Irani, J;Kunitake, H;Berger, DL;Srivastava, A;Hornick, JL;Ogino, S;Rotem, A;Vigneau, S;Johnson, BE;Corcoran, RB;Sharpe, AH;Kuchroo, VK;Ng, K;Giannakis, M;Nieman, LT;Boland, GM;Aguirre, AJ;Anderson, AC;Rozenblatt-Rosen, O;Regev, A;Hacohen, N;
PMID: 34450029 | DOI: 10.1016/j.cell.2021.08.003

Immune responses to cancer are highly variable, with mismatch repair-deficient (MMRd) tumors exhibiting more anti-tumor immunity than mismatch repair-proficient (MMRp) tumors. To understand the rules governing these varied responses, we transcriptionally profiled 371,223 cells from colorectal tumors and adjacent normal tissues of 28 MMRp and 34 MMRd individuals. Analysis of 88 cell subsets and their 204 associated gene expression programs revealed extensive transcriptional and spatial remodeling across tumors. To discover hubs of interacting malignant and immune cells, we identified expression programs in different cell types that co-varied across tumors from affected individuals and used spatial profiling to localize coordinated programs. We discovered a myeloid cell-attracting hub at the tumor-luminal interface associated with tissue damage and an MMRd-enriched immune hub within the tumor, with activated T cells together with malignant and myeloid cells expressing T cell-attracting chemokines. By identifying interacting cellular programs, we reveal the logic underlying spatially organized immune-malignant cell networks.

	Description
sense Example: Hs-LAG3-sense	Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe.
Intron# Example: Mm-Htt-intron2	Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection
Pool/Pan Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G)	A mixture of multiple probe sets targeting multiple genes or transcripts
No-XSp Example: Hs-PDGFB-No-XMm	Does not cross detect with the species (Sp)
XSp Example: Rn-Pde9a-XMm	designed to cross detect with the species (Sp)
O# Example: Mm-Islr-O1	Alternative design targeting different regions of the same transcript or isoforms
CDS Example: Hs-SLC31A-CDS	Probe targets the protein-coding sequence only
EnEm	Probe targets exons n and m
En-Em	Probe targets region from exon n to exon m
Retired Nomenclature
tvn Example: Hs-LEPR-tv1	Designed to target transcript variant n
ORF Example: Hs-ACVRL1-ORF	Probe targets open reading frame
UTR Example: Hs-HTT-UTR-C3	Probe targets the untranslated region (non-protein-coding region) only
5UTR Example: Hs-GNRHR-5UTR	Probe targets the 5' untranslated region only
3UTR Example: Rn-Npy1r-3UTR	Probe targets the 3' untranslated region only
Pan Example: Pool	A mixture of multiple probe sets targeting multiple genes or transcripts

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