<p>Supplemental Methods, Figures 1-2, Table S1. Supplemental Methods providing details on the study cohort and the image analysis algorithm. Supp. Figure 1: A) Ki67 stained breast cancer tissue. B) Haematoxylin Signal derived from color deconvolution (1) and C) histogram showing frequencies (y axis) of specific heamatoxylin intensities (x axis) of the image background (red) and foreground (green). Arrows show representative locations of different intensity classes: no tissue (red), tissue but no cell nuclei (blue), Ki67 negative cell (green) and Ki67 positive cell nuclei (orange). Figure 2: Construction of the borderline between plausible and non-plausible thresholds by combining the threshold and the resulting ratio of positive cells. Supplementary table S1: Clinico-pathological data of the study cohort</p>
Abstract Recent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to ten human lung adenocarcinomas and ten normal control tissues. Our analyses revealed heterogeneous carcinoma cell transcriptomes reflecting histological grade and oncogenic pathway activities, and two distinct microenvironmental patterns. The immune-activated CP²E microenvironment was composed of cancer-associated myofibroblasts, proinflammatory monocyte-derived macrophages, plasmacytoid dendritic cells and exhausted CD8+ T cells, and was prognostically unfavorable. In contrast, the inert N³MC microenvironment was characterized by normal-like myofibroblasts, non-inflammatory monocyte-derived macrophages, NK cells, myeloid dendritic cells and conventional T cells, and was associated with a favorable prognosis. Microenvironmental marker genes and signatures identified in single-cell profiles had progonostic value in bulk tumor profiles. In summary, single-cell RNA profiling of lung adenocarcinoma provides additional prognostic information based on the microenvironment, and may help to predict therapy response and to reveal possible target cell populations for future therapeutic approaches.
Aims Whereas current cancer diagnosis largely relies on the well‐established organ and tissue typing of tumours, partially complemented by molecular properties, the comprehensive molecular profiling efforts of recent years have stimulated proposals for molecular reclassifications of tumours independently of anatomical origin. Proposals based only on mutational profiles show the least concordance with histotypes, whereas greater concordance is achieved when various genomic and proteomic data are included. Methods and results The most comprehensive molecular reclassification of tumours, by Hoadley et al ( Cell , 158 , 2014; 929) and Hoadley et al ( Cell , 173 , 2018; 291), integrated multi‐omics data, and proposes novel molecular tumour classes. To investigate the relationship between the proposed molecular classes and the original histological tumour types, we re‐examined the histomorphology of molecularly reclassified cases. Our results show that the claimed molecular reclassification is associated with and explainable by specific histological subtypes in 70% of the reclassified cases. Conclusion Therefore, in contrast to the proclaimed reclassification and independence of molecular and histological tumour types, our analysis demonstrates that comprehensive molecular profiling, which includes gene expression and methylation as well as proteomic profiling in addition to mutational analyses, is largely consistent with histomorphological tumour properties.
e13033 Background: Panel sequencing (PS) has become a standard-of-care in cancer diagnostics. More comprehensive analyses such as whole-exome (WES) or RNA sequencing (RNAseq) allow for the detection of rare and unknown genetic aberrations that are not covered by predefined assays. The clinical impact of targeted versus comprehensive genomic assays were analyzed in patients presented at the Charité Molecular Tumor Board (MTB). Methods: Patients (pts) with advanced and/or metastatic cancer for whom no standard therapy was available were discussed in the MTB to allocate diagnostic profiling and guide biomarker-based treatment (BBT). Pts had to be < 50 years of age or diagnosed with a rare tumor entity to undergo WES/RNAseq, performed on fresh tissue. If ineligible, standard PS was performed on archival tissue. BBT recommendations, ranked by pre-specified evidence levels, were made by the MTB and pts were followed up. Results: 228 patients (median age 49 years, 108 female and 120 male) were discussed in the MTB between January 2016 and February 2019. We assigned 73 and 155 pts to PS and WES/RNAseq and results were obtained for 78.1% (n = 57/73) and 54.8% (n = 85/155) pts, respectively. Sequencing failed for 11 (PS; 15.1%) and 62 (WES/RNAseq; 40%) pts, most commonly due to insufficient tissue (n = 29). Sequencing was ongoing in 5 (PS) and 8 (WES/RNAseq) pts at the time of analysis. A median of 2 BBTs were recommended for 75.4% (43/57) of PS (range r: 1-3) and 90.6% (77/85) of WES/RNAseq pts (r: 1-6) each. 22% (n = 17/77) of WES/RNAseq pts had ≥4 BBTs made by the MTB. Treatment was initiated in 30.2% (n = 13/43) of PS and 40.2% (n = 31/77) of WES/RNAseq pts. Clinical benefit rates (CBRs) were 23.1% (2 PR, 1 SD) for PS and 45.2% (2 CR, 3 PR, 9 SD) for WES/RNAseq pts. Overall survival data was immature at the time of analysis. Conclusions: Utilizing WES/RNAseq is a feasible approach to perform tumor profiling in a heterogeneous cohort. We here show a higher rate of pts receiving confident evidence-based treatment recommendations in the WES/RNAseq group and a higher rate of treatment initiation. The CBR nearly doubled in the WES/RNAseq cohort when compared to standard PS pts, thus emphasizing the need for larger comparative analyses to guide diagnostic decision-making.
Abstract Background: Thyroid transcription factor 1 (TTF-1) is expressed in 70% to 80% of lung adenocarcinomas (LUAD). Several papers revealed that TTF-1 expression is associated with better patient outcomes independent of the tumor stage. However, it is unknown whether the prognostic impact of TTF-1 only results from a different growth pattern (tumor grading) or is independently associated with a biologically more aggressive phenotype. Thus, we analyzed a large bi-centric cohort of LUAD to assume the true prognostic value of TTF-1 in relation to the tumor grade. Methods: We collected a large, real-life cohort of 447 patients with completely resected LUAD from two large-volume German lung cancer centers. TTF-1 status, evaluated by IHC, and tumor grading were correlated with clinical, pathologic, and molecular data, as well as patient outcomes. Kaplan-Meier curves were used for comparison of TTF-1 status and different tumor grades in terms of the DFS. The impact of TTF-1 was measured by univariate and multivariate Cox regression. Finally, a causal graph analysis was performed to identify and account for potential confounders to improve the statistical estimation of the predictive power of TTF-1 expression for DFS in comparison to the tumor grade. Results: Kaplan-Meier curves revealed that TTF-1 positivity is associated with longer DFS independent of tumor grade, whereas a strong association of DFS with the tumor grade is observed only in TTF-1-positive patients. In univariate analysis, TTF-1 positivity was associated with significantly longer DFS (median log HR -0.83 [-1.43; -0.20]; p=0.018), whereas higher tumor grade showed a non-significant association with shorter DFS (median log HR 0.30 [-0.58; 1.60]; p=0,62 for G1 to G2 and 0.68 [-0.24; 1.89]; p=0,34 for G2 to G3). In multivariate analysis, TTF-1 positivity resulted in a significantly longer DFS (median log HR -0.65 [-1.13; -0.09]; p=0.05) independent of all other parameters, including tumor grade. Applying the adjustment sets suggested by the causal graph analysis, the superiority of TTF-1 (median log HR -0.86 [-1.25; -0.41]) over tumor grade (median log HR 0.31 [-0.32; 1.30]/0.61[-0.07; 1.65]) in terms of prognostic power was confirmed. Conclusion: This study draws three important conclusions: Firstly, it indicates that the prognostic power of tumor grade is limited to TTF-1-positive patients. Secondly, it underlines the independent prognostic value of TTF-1 expression for DFS regardless of tumor grade. Finally, our analyses reveal that the effect size of TTF-1 surpasses that of tumor grade. To transfer the results directly into the clinical area, we recommend distinguishing between TTF-1-positive and TTF-1-negative LUADs in the pathological report. Tumor grading should only be applied to TTF-1-positive LUADs (TTF-1+/G1-3). TTF-1-negative LUADs should either not be graded or always be classified as high-grade (TTF-1-/G3). Citation Format: Simon Schallenberg, Gabriel Dernbach, Mihnea Dragomir, Georg Schlachtenberger, Kyrill Boschung, Corinna Friedrich, Kai Standvoss, Lukas Ruff, Philipp Anders, Christian Grohe, Winfried Randerath, Sabine Merkelbach-Bruse, Alexander Quaas, Matthias Heldwein, Ulrich Keilholz, Khosro Hekmat, Jens Rückert, Reinhard Büttner, David Horst, Frederick Klauschen, Nikolaj Frost. TTF-1 status in early-stage lung adenocarcinoma is an independent predictor of relapse and survival superior to tumor grading [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5221.
