Morphoproteomic Characterization of Lung Squamous Cell Carcinoma Fragmentation, a Histological Marker of Increased Tumor Invasiveness

Casanova, Ruben; Xia, Daniel; Rulle, Undīne; Nanni, Paolo; Grossmann, Jonas; Vrugt, Bart; Wettstein, Reto; Ballester-Ripoll, Rafael; Astolfo, Alberto; Weder, Walter; Moch, Holger; Stampanoni, Marco; Beck, Andrew H.; Soltermann, Alex

doi:10.1158/0008-5472.can-16-2363

Cited by 16 publications

(15 citation statements)

References 42 publications

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“…predictive biomarker research). Finally, the large impact of SI on survival in our cohorts supports its further investigation, potentially as a component of a revised prognostic grading score for lung SCCs, in combination with measures of tumor budding/fragmentation and keratinization 3 , 7 , 36 .…”

Section: Discussionsupporting

confidence: 53%

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Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma

Xia

Casanova

Machiraju

et al. 2018

Sci Rep

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The goal of this study is to use computational pathology to help guide the development of human-based prognostic H&E biomarker(s) suitable for research and potential clinical use in lung squamous cell carcinoma (SCC). We started with high-throughput computational image analysis with tissue microarrays (TMAs) to screen for histologic features associated with patient overall survival, and found that features related to stromal inflammation were the most strongly prognostic. Based on this, we developed an H&E stromal inflammation (SI) score. The prognostic value of the SI score was validated by two blinded human observers on two large cohorts from a single institution. The SI score was found to be reproducible on TMAs (Spearman rho = 0.88 between the two observers), and highly prognostic (e.g. hazard ratio = 0.32; 95% confidence interval: 0.19–0.54; p-value = 2.5 × 10−5 in multivariate analyses), particularly in comparison to established histologic biomarkers. Guided by downstream molecular/biomarker correlation studies starting with TCGA cases, we investigated the hypothesis that epithelial PD-L1 expression modified the prognostic value of SI. Our research demonstrates that computational pathology can be an efficient hypothesis generator for human pathology research, and support the histologic evaluation of SI as a prognostic biomarker in lung SCCs.

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Section: Discussionsupporting

confidence: 53%

“…These include features related to higher-order tissue architecture (e.g. the pattern of cancer infiltration 7 ), relational features (e.g. the presence of tumor in blood vessels), features that cannot be assessed on small TMAs (e.g.…”

Section: Discussionmentioning

confidence: 99%

Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma

Xia

Casanova

Machiraju

et al. 2018

Sci Rep

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“…Antibodies used for IHC are listed in supplementary material, Table S1. Quantification of staining intensities was performed using Fiji .…”

Section: Methodsmentioning

confidence: 99%

IL‐8 and CXCR1 expression is associated with cancer stem cell‐like properties of clear cell renal cancer

Corrò

Healy

Engler

et al. 2019

The Journal of Pathology

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Recent studies suggest that clear cell renal cell carcinoma (ccRCC) possesses a rare population of cancer stem cells (CSCs) that might contribute to tumor heterogeneity, metastasis and therapeutic resistance. Nevertheless, their relevance for renal cancer is still unclear. In this study, we successfully isolated CSCs from established human ccRCC cell lines. CSCs displayed high expression of the chemokine IL‐8 and its receptor CXCR1. While recombinant IL‐8 significantly increased CSC number and properties in vitro , CXCR1 inhibition using an anti‐CXCR1 antibody or repertaxin significantly reduced these features. After injection into immune‐deficient mice, CSCs formed primary tumors that metastasized to the lung and liver. All xenografted tumors in mice expressed high levels of IL‐8 and CXCR1. Furthermore, IL‐8/CXCR1 expression significantly correlated with decreased overall survival in ccRCC patients. These results suggest that the IL‐8/CXCR1 phenotype is associated with CSC‐like properties in renal cancer. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

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“…For the CN cohort, a color threshold was used to segment malignant tumor tissue (brown positive signal) from its surrounding desmoplastic stroma (blue-grey counterstain) using Fiji [19], as described [17]. Morphologic parameters of the segmented tumor tissue were retrieved for each tumor specimen and computed as following: 1. percentage of vital tumor cells (cTu.Percentage = tumor cells area/[tumor cells area + stroma area]*100), 2. total surface covered by vital tumor cells (cTu.Area), 3. size of the largest vital tumor fragment (cTu.Size.max), 4. total number of vital tumor fragments (cTu.Fragments), defined as disconnected carcinoma fragment larger than 800 μm 2 , separated by stroma.…”

Section: Image Processing and Regression Scoringmentioning

confidence: 99%

“…We have previously developed an image analysis approach to quantify tumor fragmentation [17] in lung squamous cell carcinoma (LSCC), the second most common histological subtype of NSCLC [18]. This structural feature was associated with increased tumor invasion and poor prognosis.…”

Section: Introductionmentioning

confidence: 99%

Enhanced prognostic stratification of neoadjuvant treated lung squamous cell carcinoma by computationally-guided tumor regression scoring

Casanova

Leblond

et al. 2020

Lung Cancer

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Introduction: The amount of residual tumor burden after neoadjuvant chemotherapy is an important prognosticator, but for non-small cell lung carcinoma (NSCLC), no official regression scoring system is yet established. Computationally derived histological regression scores could provide unbiased and quantitative readouts to complement the clinical assessment of treatment response. Methods: Histopathologic tumor regression was microscopically assessed on whole cases in a neoadjuvant chemotherapy-treated cohort (NAC, n = 55 patients) of lung squamous cell carcinomas (LSCC). For each patient, the slide showing the least pathologic regression was selected for subsequent computational analysis and histological features were quantified: percentage of vital tumor cells (cTu.Percentage), total surface covered by vital tumor cells (cTu.Area), area of the largest vital tumor fragment (cTu.Size.max), and total number of vital tumor fragments (cTu.Fragments). A chemo-naïve LSCC cohort (CN, n = 104) was used for reference. For 23 of the 55 patients [ 18 F]-Fluorodeoxyglucose (FDG) PET/CT measurements of maximum standard uptake value (SUV max), background subtracted lesion activity (BSL) and background subtracted volume (BSV) were correlated with pathologic regression. Survival analysis was carried out using Cox regression and receiver operating characteristic (ROC) curve analysis using a 3-years cutoff. Results: All computational regression parameters significantly correlated with relative changes of BSV FDG PET/ CT values after neoadjuvant chemotherapy. ROC curve analysis of histological parameters of NAC patients showed that cTu.Percentage was the most accurate prognosticator of overall survival (ROC curve AUC = 0.77, pvalue = 0.001, Cox regression HR = 3.6, p = 0.001, variable cutoff < = 30 %). Conclusions: This study demonstrates the prognostic relevance of computer-derived histopathologic scores. Additionally, the analysis carried out on slides displaying the least pathologic regression correlated with overall pathologic response and PET/CT values. This might improve the objective histopathologic assessment of tumor response in neoadjuvant setting.

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Morphoproteomic Characterization of Lung Squamous Cell Carcinoma Fragmentation, a Histological Marker of Increased Tumor Invasiveness

Cited by 16 publications

References 42 publications

Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma

Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma

IL‐8 and CXCR1 expression is associated with cancer stem cell‐like properties of clear cell renal cancer

Enhanced prognostic stratification of neoadjuvant treated lung squamous cell carcinoma by computationally-guided tumor regression scoring

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