Gerger, A. | Search bioRxiv

bioRxiv2022

Spatial tumour gene signature discriminates neoplastic from non-neoplastic compartments in colon cancer: unravelling predictive biomarkers for relapse

BackgroundTherapeutic management of stage II colon cancer remains difficult regarding the decision whether adjuvant chemotherapy should be administered or not. Low rates of recurrence are opposed to chemotherapy induced toxicity and current clinical features are limited in predicting disease relapse. Predictive biomarkers are urgently needed and we hypothesise that the spatial tissue composition of relapsed and non-relapsed colon cancer stage II patients reveals relevant biomarkers. MethodsThe spatial tissue composition of stage II colon cancer patients was examined by in situ sequencing technology with sub-cellular resolution. A panel of 175 genes was designed investigating specific cancer-associated processes and components of the tumour microenvironment. We identified a tumour gene signature to subclassify tissue into neoplastic and non-neoplastic tissue compartments based on spatial expression patterns generated by in situ sequencing (GTC-tool - Genes-To-Count). ResultsThe GTC-tool automatically identified tissue compartments that were used to quantify gene expression of biological processes upregulated within the neoplastic tissue in comparison to non-neoplastic tissue and within relapsed versus non-relapsed stage II colon patients. Three differentially expressed genes (FGFR2, MMP11 and OTOP2) in the neoplastic tissue compartments of relapsed patients in comparison to non-relapsed patients were identified predicting recurrence in stage II colon cancer. ConclusionsIn depth spatial in situ sequencing revealed novel potential predictive biomarkers for disease relapse in colon cancer stage II patients. Our developed open-access GTC-tool allows to accurately capture the tumour compartment and quantify spatial gene expression in colon cancer tissue.

cancer biology↗

bioRxiv2018

Inference of tumor cell-specific transcription factor binding from cell-free DNA

Alterations in transcription factors are important drivers of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. Here, we evaluated the feasibility of inferring transcription factor binding in solid tumors from their nucleosome footprint in circulating cell-free DNA. We developed a novel analysis pipeline to determine accessibility of transcription factor binding sites and applied it to 244 cell-free DNA samples from patients with prostate, breast and colon cancer. We observed patient-specific as well as tumor-specific patterns. Specifically, inferred binding patterns for the transcription factors AR, HOXB13, and NKX3-1 allowed us to classify patients by tumor type, including subtypes of prostate cancer, which has clinical implications for the management of patients. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable for clinical analysis.

cancer biology↗