Dataset Information

Characterization of the immune cell landscape in CRC: Clinical implications of tumour-infiltrating leukocytes in early- and late-stage CRC.

ABSTRACT:

Introduction

Colorectal cancer (CRC) is the third leading cause of cancer-related deaths globally. Tumour-infiltrating leukocytes play an important role in cancers, including CRC. We therefore sought to characterize the impact of tumour-infiltrating leukocytes on CRC prognosis.

Methods

To determine whether the immune cell profile within CRC tissue could influence prognosis, we employed three computational methodologies (CIBERSORT, xCell and MCPcounter) to predict abundance of immune cell types, based on gene expression. This was done using two patient cohorts, TCGA and BC Cancer Personalized OncoGenomics (POG).

Results

We observed significant differences in immune cell composition between CRC and normal adjacent colon tissue, as well as differences in based on method of analysis. Evaluation of survival based on immune cell types revealed dendritic cells as a positive prognostic marker, consistently across methodologies. Mast cells were also found to be a positive prognostic marker, but in a stage-dependent manner. Unsupervised cluster analysis demonstrated that significant differences in immune cell composition has a more pronounced effect on prognosis in early-stage CRC, compared to late-stage CRC. This analysis revealed a distinct group of individuals with early-stage CRC which have an immune infiltration signature that indicates better survival probability.

Conclusions

Taken together, characterization of the immune landscape in CRC has provided a powerful tool to assess prognosis. We anticipate that further characterization of the immune landscape will facilitate use of immunotherapies in CRC.

SUBMITTER: Bazzi ZA

PROVIDER: S-EPMC9945970 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Characterization of the immune cell landscape in CRC: Clinical implications of tumour-infiltrating leukocytes in early- and late-stage CRC.

Bazzi Zainab Ali ZA Sneddon Sophie S Zhang Peter G Y PGY Tai Isabella T IT

Frontiers in immunology 20230208

<h4>Introduction</h4>Colorectal cancer (CRC) is the third leading cause of cancer-related deaths globally. Tumour-infiltrating leukocytes play an important role in cancers, including CRC. We therefore sought to characterize the impact of tumour-infiltrating leukocytes on CRC prognosis.<h4>Methods</h4>To determine whether the immune cell profile within CRC tissue could influence prognosis, we employed three computational methodologies (CIBERSORT, xCell and MCPcounter) to predict abundance of immu ...[more]

PMID: 36846019

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Project description:Colorectal cancer (CRC) is one of the most frequently occurring cancers, but prognostic biomarkers identifying patients at risk of recurrence are still lacking. In this study, we aimed to investigate in more detail the spatial relationship between intratumoural T cells, cancer cells, and cancer cell hallmarks, as prognostic biomarkers in stage III colorectal cancer patients. We conducted multiplexed imaging of 56 protein markers at single cell resolution on resected fixed tissue from stage III CRC patients who received adjuvant 5-fluorouracil-based chemotherapy. Images underwent segmentation for tumour, stroma and immune cells, and cancer cell 'state' protein marker expression was quantified at a cellular level. We developed a Python package for estimation of spatial proximity, nearest neighbour analysis focusing on cancer cell - T cell interactions at single-cell level. In our discovery cohort (MSK), we processed 462 core samples (total number of cells: 1,669,228) from 221 adjuvant 5FU-treated stage III patients. The validation cohort (HV) consisted of 272 samples (total number of cells: 853,398) from 98 stage III CRC patients. While there were trends for an association between percentage of cytotoxic T cells (across the whole cancer core), it did not reach significance (Discovery cohort: p = 0.07, Validation cohort: p = 0.19). We next benchmarked our region-based nearest neighbourhood approach to determine the spatial relationships between cytotoxic T cells, helper T cells and cancer cell clusters. In the both cohorts, we found that lower distance between cytotoxic T cells, T helper cells and cancer cells was significantly associated with increased disease-free survival. An unsupervised trained model that clustered tumours based on the median distance between immune cells and cancer cells, as well as protein expression profiles, successfully classified patients into low-risk and high-risk groups (Discovery cohort: p = 0.01, Validation cohort: p = 0.003).

Project description:BackgroundThis study was to explore the infiltration pattern of immune cells in the prostate cancer (PCa) microenvironment and evaluate the possibility of specific infiltrating immune cells as potential prognostic biomarkers in PCa.MethodsInfiltrating percentage of 22 immune cells were extracted from 27 normalized datasets by CIBERSORT algorithm. Samples with CIBERSORT p-value < 0.05 were subsequently merged and divided into normal or tumor groups. The differences of 22 immune cells between normal and tumor tissues were analyzed along with potential infiltrating correlations among 22 immune cells and Gleason grades. SNV data from TCGA was used to calculate the TMB score. A univariate and multivariate regression were used to evaluate the prognostic effects of immune cells in PCa.ResultsTen immune cells with significant differences were identified, including seven increased and three decreased infiltrating immune cells from 190 normal prostate tissues and 537 PCa tissues. Among them, the percentage of infiltration of resting NK cells increased the most, whereas the percentage of infiltration of resting mast cells decreased the most. In normal tissues, CD8+ T cells had the strongest infiltrating correlation with monocytes, while activated NK cells and naive B cells were the highest in PCa tissues. Moreover, the infiltration of five immune cells was significantly associated with TMB score and mutations of immune gene change the infiltration of immune cells. The Area Under Curve (AUC) of the multivariate regression model for the five- and 10-year survival prediction of PCa reached 0.796 and 0.862. The validation cohort proved that the model was reproducible.ConclusionsThis study demonstrated that different infiltrating immune cells in prostate cancer, especially higher infiltrating M1 macrophages and neutrophils in PCa tissue, are associated with patients' prognosis, suggesting that these two immune cells might be potential targets for PCa diagnosis and prognosis of treatment.

Dataset Information

Characterization of the immune cell landscape in CRC: Clinical implications of tumour-infiltrating leukocytes in early- and late-stage CRC.

Introduction

Methods

Results

Conclusions

Publications

Characterization of the immune cell landscape in CRC: Clinical implications of tumour-infiltrating leukocytes in early- and late-stage CRC.

Similar Datasets

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