TY  - JOUR
A1  - Kotlyar, Mischa J.
A1  - Krebs, Markus
A1  - Solimando, Antonio Giovanni
A1  - Marquardt, André
A1  - Burger, Maximilian
A1  - Kübler, Hubert
A1  - Bargou, Ralf
A1  - Kneitz, Susanne
A1  - Otto, Wolfgang
A1  - Breyer, Johannes
A1  - Vergho, Daniel C.
A1  - Kneitz, Burkhard
A1  - Kalogirou, Charis
T1  - Critical evaluation of a microRNA-based risk classifier predicting cancer-specific survival in renal cell carcinoma with tumor thrombus of the inferior vena cava
JF  - Cancers
N2  - (1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCC\(^{IVC}\)) represents a clinical high-risk setting. However, there is substantial heterogeneity within this patient subgroup regarding survival outcomes. Previously, members of our group developed a microRNA(miR)-based risk classifier — containing miR-21-5p, miR-126-3p and miR-221-3p expression — which significantly predicted the cancer-specific survival (CSS) of ccRCC\(^{IVC}\) patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCC\(^{IVC}\), we measured the expression levels of miR-21, miR-126, and miR-221 using qRT-PCR. The prognostic impact of clinicopathological parameters and miR expression were investigated via single-variable and multivariable Cox regression. Referring to the previously established risk classifier, we performed Kaplan–Meier analyses for single miR expression levels and the combined risk classifier. Cut-off values and weights within the risk classifier were taken from the previous study. (3) Results: miR-21 and miR-126 expression were significantly associated with lymphonodal status at the time of surgery, the development of metastasis during follow-up, and cancer-related death. In Kaplan–Meier analyses, miR-21 and miR-126 significantly impacted CSS in our cohort. Moreover, applying the miR-based risk classifier significantly stratified ccRCC\(^{IVC}\) according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCC\(^{IVC}\) cohort.
KW  - kidney cancer
KW  - RCC
KW  - venous infiltration
KW  - biomarker
KW  - miR
KW  - risk stratification
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-311040
SN  - 2072-6694
VL  - 15
IS  - 7
ER  - 
TY  - JOUR
A1  - Marquardt, André
A1  - Hartrampf, Philipp
A1  - Kollmannsberger, Philip
A1  - Solimando, Antonio G.
A1  - Meierjohann, Svenja
A1  - Kübler, Hubert
A1  - Bargou, Ralf
A1  - Schilling, Bastian
A1  - Serfling, Sebastian E.
A1  - Buck, Andreas
A1  - Werner, Rudolf A.
A1  - Lapa, Constantin
A1  - Krebs, Markus
T1  - Predicting microenvironment in CXCR4- and FAP-positive solid tumors — a pan-cancer machine learning workflow for theranostic target structures
JF  - Cancers
N2  - (1) Background: C-X-C Motif Chemokine Receptor 4 (CXCR4) and Fibroblast Activation Protein Alpha (FAP) are promising theranostic targets. However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database —  representing n = 9242 specimens from 29 tumor entities. CXCR4- and FAP-positive samples were assessed via StringDB cluster analysis, EnrichR, Metascape, and Gene Set Enrichment Analysis (GSEA). Findings were validated via correlation analyses in n = 1541 tumor samples. TIMER2.0 analyzed the association of CXCR4 / FAP expression and infiltration levels of immune-related cells. (3) Results: We identified entity-independent CXCR4 and FAP gene signatures representative for the majority of solid cancers. While CXCR4 positivity marked an immune-related microenvironment, FAP overexpression highlighted an angiogenesis-associated niche. TIMER2.0 analysis confirmed characteristic infiltration levels of CD8+ cells for CXCR4-positive tumors and endothelial cells for FAP-positive tumors. (4) Conclusions: CXCR4- and FAP-directed PET imaging could provide a non-invasive decision aid for entity-agnostic treatment of microenvironment in solid malignancies. Moreover, this machine learning workflow can easily be transferred towards other theranostic targets.
KW  - machine learning
KW  - tumor microenvironment
KW  - immune infiltration
KW  - angiogenesis
KW  - mRNA
KW  - miRNA
KW  - transcriptome
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-305036
SN  - 2072-6694
VL  - 15
IS  - 2
ER  -