Survival-associated heterogeneity of marker-defined perivascular cells in colorectal cancer

Perivascular cells (PC) were recently implied as regulators of metastasis and immune cell activity. Perivascular heterogeneity in clinical samples, and associations with other tumor features and outcome, remain largely unknown. Here we report a novel method for digital quantitative analyses of vessel characteristics and PC, which was applied to two collections of human metastatic colorectal cancer (mCRC). Initial analyses identified marker-defined subsets of PC, including cells expressing PDGFR-beta or alpha-SMA or both markers. PC subsets were largely independently expressed in a manner unrelated to vessel density and size. Association studies implied specific oncogenic mutations in malignant cells as determinants of PC status. Semi-quantitative and digital-image-analyses-based scoring of the NORDIC-VII cohort identified significant associations between low expression of perivascular PDGFR-alpha and -beta and shorter overall survival. Analyses of the SPCRC cohort confirmed these findings. Perivascular PDGFR-alpha and -beta remained independent factors for survival in multivariate analyses. Overall, our study identified host vasculature and oncogenic status as determinants of tumor perivascular features. Perivascular PDGFR-alpha and -beta were identified as novel independent markers predicting survival in mCRC. The novel methodology should be suitable for similar analyses in other tumor collections

The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types

Background: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed.Methods: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns.Findings: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR (95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59 (1.49-8.62)) associations of the tumour stroma fraction with survival.Interpretation: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance.</p

Prognostic Interactions between FAP plus Fibroblasts and CD8a+T Cells in Colon Cancer

Simple Summary In addition to malignant cells, tumors are composed also of other cell types including immune cells and fibroblasts. These cell types interact with each other and with the malignant cells. Prognosis associations have previously been demonstrated for CD8-positive immune cells. Recent studies suggest that fibroblasts can affect the function of immune cells. The aim of this study was to investigate if the fibroblast composition of tumors affected the prognosis association of CD8 immune cells. This study demonstrated that in colon cancer, CD8 prognosis associations was restricted to the group of tumors with high expression the FAP fibroblast marker. Our findings suggest continued mechanistic studies regarding crosstalk between FAP-positive fibroblasts and the different immune cell types; and also support the investigation of fibroblast/T-cell interactions for therapeutic purposes. Inter-case variations in immune cell and fibroblast composition are associated with prognosis in solid tumors, including colon cancer. A series of experimental studies suggest immune-modulatory roles of marker-defined fibroblast populations, including FAP-positive fibroblasts. These studies imply that the fibroblast status of tumors might affect the prognostic significance of immune-related features. Analyses of a population-based colon cancer cohort demonstrated good prognosis associations of FAP intensity and CD8a density. Notably, a significant prognostic interaction was detected between these markers (p = 0.013 in nonadjusted analyses and p = 0.003 in analyses adjusted for cofounding factors) in a manner where the good prognosis association of CD8 density was restricted to the FAP intensity-high group. This prognostic interaction was also detected in an independent randomized trial-derived colon cancer cohort (p = 0.048 in nonadjusted analyses). In the CD8-high group, FAP intensity was significantly associated with a higher total tumor density of FoxP3-positive immune cells and a higher ratio of epithelial-to-stromal density of CD8a T cells. The study presents findings relevant for the ongoing efforts to improve the prognostic performance of CD8-related markers and should be followed by additional validation studies. Furthermore, findings support, in general, earlier model-derived studies implying fibroblast subsets as clinically relevant modulators of immune surveillance. Finally, the associations between FAP intensity and specific immune features suggest mechanisms of fibroblast-immune crosstalk with therapeutic potential

Stromal FAP is an independent poor prognosis marker in non-small cell lung adenocarcinoma and associated with p53 mutation

Objectives Fibroblasts regulate tumor growth and immune surveillance. Here, we study FAP, PDGFβR and α-SMA fibroblast markers in a well-annotated clinical cohort of non–small-cell lung cancer (NSCLC) for analyses of associations with immune cell infiltration, mutation status and survival. Materials and Methods A well-annotated NSCLC cohort was subjected to IHC analyses of stromal expression of FAP, PDGFβR and α-SMA and of stromal CD8 density. Fibroblast markers-related measurements were analyzed with regard to potential associations with CD8 density, cancer genetic driver mutations, survival and PD-L1 expression in the whole NSCLC cohort and in subsets of patients. Results High stromal FAP expression was identified as an independent poor prognostic marker in the whole study population (HR 1.481; 95 % CI, 1.012–2.167, p = 0.023) and in the histological subset of adenocarcinoma (HR 1.720; 95 % CI, 1.126–2.627, p = 0.012). Among patients with adenocarcinoma, a particularly strong association of FAP with poor survival was detected in patients with low stromal CD8 infiltration, and in other subpopulations identified by specific clinical characteristics; elderly patients, females, non-smokers and patients with normal ECOG performance status. α-SMA expression was negatively associated with CD8 infiltration in non-smokers, but none of the fibroblast markers expression was associated with CD8 density in the whole study population. Significant associations were detected between presence of p53 mutations and high α-SMA (p = 0.003) and FAP expression (p &lt; 0.001). Conclusion The study identifies FAP intensity as a candidate independent NSCLC prognostic biomarker. The study also suggests continued analyses of the relationships between genetic driver mutations and the composition of tumor stroma, as well as continued probing of marker-defined fibroblasts as NSCLC subset-specific modifiers of immune surveillance and outcome.De två första författarna delar förstaförfattarskapet</p

Infiltration of NK and plasma cells is associated with a distinct immune subset in non‐small cell lung cancer

Immune cells of the tumor microenvironment are central but erratic targets for immunotherapy. The aim of this study was to characterize novel patterns of immune cell infiltration in non-small cell lung cancer (NSCLC) in relation to its molecular and clinicopathologic characteristics. Lymphocytes (CD3+, CD4+, CD8+, CD20+, FOXP3+, CD45RO+), macrophages (CD163+), plasma cells (CD138+), NK cells (NKp46+), PD1+, and PD-L1+ were annotated on a tissue microarray including 357 NSCLC cases. Somatic mutations were analyzed by targeted sequencing for 82 genes and a tumor mutational load score was estimated. Transcriptomic immune patterns were established in 197 patients based on RNA sequencing data. The immune cell infiltration was variable and showed only poor association with specific mutations. The previously defined immune phenotypic patterns, desert, inflamed, and immune excluded, comprised 30, 13, and 57% of cases, respectively. Notably, mRNA immune activation and high estimated tumor mutational load were unique only for the inflamed pattern. However, in the unsupervised cluster analysis, including all immune cell markers, these conceptual patterns were only weakly reproduced. Instead, four immune classes were identified: (1) high immune cell infiltration, (2) high immune cell infiltration with abundance of CD20+ B cells, (3) low immune cell infiltration, and (4) a phenotype with an imprint of plasma cells and NK cells. This latter class was linked to better survival despite exhibiting low expression of immune response-related genes (e.g. CXCL9, GZMB, INFG, CTLA4). This compartment-specific immune cell analysis in the context of the molecular and clinical background of NSCLC reveals two previously unrecognized immune classes. A refined immune classification, including traits of the humoral and innate immune response, is important to define the immunogenic potency of NSCLC in the era of immunotherapy. © 2021 The Authors. The Journal of Pathology published by John Wiley &amp; Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland

An idiosyncratic zonated stroma encapsulates desmoplastic liver metastases and originates from injured liver

Abstract A perimetastatic capsule is a strong positive prognostic factor in liver metastases, but its origin remains unclear. Here, we systematically quantify the capsule’s extent and cellular composition in 263 patients with colorectal cancer liver metastases to investigate its clinical significance and origin. We show that survival improves proportionally with increasing encapsulation and decreasing tumor-hepatocyte contact. Immunostaining reveals the gradual zonation of the capsule, transitioning from benign-like NGFRhigh stroma at the liver edge to FAPhigh stroma towards the tumor. Encapsulation correlates with decreased tumor viability and preoperative chemotherapy. In mice, chemotherapy and tumor cell ablation induce capsule formation. Our results suggest that encapsulation develops where tumor invasion into the liver plates stalls, representing a reparative process rather than tumor-induced desmoplasia. We propose a model of metastases growth, where the efficient tumor colonization of the liver parenchyma and a reparative liver injury reaction are opposing determinants of metastasis aggressiveness

Publisher correction: Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity

In this Article originally published, owing to a technical error, author affiliations were incorrectly assigned in the HTML version; the PDF was correct. These errors have now been corrected

Publisher Correction: Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity

In this Article originally published, owing to a technical error, author affiliations were incorrectly assigned in the HTML version; the PDF was correct. These errors have now been corrected

Publisher correction:Whole-tissue biopsy phenotyping of three-dimensional tumours reveals patterns of cancer heterogeneity

\u3cp\u3eIn this Article originally published, owing to a technical error, author affiliations were incorrectly assigned in the HTML version; the PDF was correct. These errors have now been corrected.\u3c/p\u3