MALDI mass spectrometry imaging - Diagnostic pathways and metabolites for renal tumor entities

BACKGROUND Correct tumor subtyping of primary renal tumors is essential for treatment decision in daily routine. Most of the tumors can be classified on morphology alone. Nevertheless, some diagnoses are difficult and further investigations are needed for correct tumor subtyping. Beside histochemical investigations high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can detect new diagnostic biomarkers and hence improve the diagnostic. PATIENTS AND METHODS Formalin-fixed paraffin embedded (FFPE) tissue specimens from clear cell renal cell carcinoma (ccRCC, n=552), papillary RCC (pRCC, n=122), chromophobe RCC (chRCC, n=108) and renal Oncocytoma (rO, n=71) were analyzed by high mass resolution matrix-assisted laser desorption/ionization (MALDI) fourier-transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). SPACiAL pipeline was executed for automated co-registration of histological and molecular features. Pathway enrichment and pathway topology analysis were performed to determine significant differences between RCC subtypes. RESULTS We discriminated the four histological subtypes (ccRCC, pRCC, chRCC and rO) and established the subtype specific pathways and metabolic profiles. RO showed an enrichment of pentose phosphate, taurine and hypotaurine, glycerophospholipid, amino sugar and nucleotide sugar, fructose and mannose, glycine, serine and threonine pathways. ChRCC is defined by enriched pathways including the amino sugar and nucleotide sugar, fructose and mannose, glycerophospholipid, taurine and hypotaurine, glycine, serine and threonine pathways. Pyrimidine, amino sugar and nucleotide sugar, glycerophospholipid and glutathione pathways are enriched in ccRCC. Furthermore, we detected enriched phosphatidylinositol and glycerophospholipid pathways in pRCC. CONCLUSION In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85,13%. Furthermore, we detected tumor specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and in biomarker detection

MALDI Mass Spectrometry Imaging—Prognostic Pathways and Metabolites for Renal Cell Carcinomas

High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan–Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes

The role of claudin-6 in chromophobe renal cell carcinoma

Background. The prognostic value of Claudin-6 (CLDN6) in non clear cell renal cell carcinoma (RCC) is still unclear. Aim. To evaluate the prognostic impact of CLDN6 expression in a large cohort of chromophobe RCC (chRCC). Material and Methods. Patients who underwent renal surgery due to chRCC were recruited. Clinical data were retrospectively evaluated. Tumor specimens were analyzed for CLDN6 expression by immunohistochemistry. Results. 81 chRCC patients were eligible for analysis, thereof 10 (12.3%) patients were positive for CLDN6. No significant associations were found for CLDN6 expression and clinical attributes in patients with chRCC. Kaplan-Meier analysis revealed no differences in overall survival (OS) for patients with CLDN6- compared to CLDN6+ tumors (87.0% versus 62.5%; p=0.174). Conclusion. In chRCC CLDN6 expression is not associated with parameters of aggressiveness or survival. Due to the rare incidence of chRCC further studies with larger cohorts are warranted

Expression of PD-1 and CTLA-4 Are Negative Prognostic Markers in Renal Cell Carcinoma

Immuno-oncological therapy with checkpoint inhibition (CI) has become a new standard treatment in metastatic renal cell carcinoma (RCC), but the prognostic value of the expression of CI therapy target molecules is still controversial. 342 unselected consecutive RCC tumor samples were analyzed regarding their PD-1, PD-L1, and CTLA-4 expression by immunohistochemistry (IHC). The prognostic values for cancer-specific survival (CSS) and overall survival (OS) were analyzed for those not exposed to CI therapy. The expression of PD-1 in tumor-infiltrating mononuclear cells (TIMC) and PD-L1 in tumor cells was detected in 9.4% and 12.3%, respectively (Immune reactive score (IRS) > 0). Furthermore, PD-L1 expression in TIMC (IRS > 0) and CTLA-4 expression in TIMC (>1% positive cells) was detected in 4.8% and 6.3%. PD-1 expression and CTLA-4 expression were significantly associated with a worse OS and CSS in log rank survival analysis and univariate Cox regression analysis. CTLA-4 expression is a prognostic marker that is independently associated with a worse outcome in multivariate Cox regression analysis in the whole cohort (OS: p = 0.013; CSS: p = 0.048) as well as in a non-metastatic subgroup analysis (OS: p = 0.028; CSS: p = 0.022). Patients with combined CTLA-4 expression and PD-1-expression are at highest risk in OS and CSS. In RCC patients, PD-1 expression in TIMC and CTLA-4 expression in TIMC are associated with a worse OS and CSS. The combination of PD-1 expression in TIMC and CTLA-4 expression in TIMC might identify high risk patients. This is, to our knowledge, the first description of CTLA-4 expression to be a prognostic marker in RCC

Mass spectrometry imaging differentiates chromophobe renal cell carcinoma and renal oncocytoma with high accuracy

Background: While subtyping of the majority of malignant chromophobe renal cell carcinoma (cRCC) and benign renal oncocytoma (rO) is possible on morphology alone, additional histochemical, immunohistochemical or molecular investigations are required in a subset of cases. As currently used histochemical and immunohistological stains as well as genetic aberrations show considerable overlap in both tumors, additional techniques are required for differential diagnostics. Mass spectrometry imaging (MSI) combining the detection of multiple peptides with information about their localization in tissue may be a suitable technology to overcome this diagnostic challenge. Patients and Methods: Formalin-fixed paraffin embedded (FFPE) tissue specimens from cRCC (n=71) and rO (n=64) were analyzed by MSI. Data were classified by linear discriminant analysis (LDA), classification and regression trees (CART), k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF) algorithm with internal cross validation and visualized by t-distributed stochastic neighbor embedding (t-SNE). Most important variables for classification were identified and the classification algorithm was optimized. Results: Applying different machine learning algorithms on all m/z peaks, classification accuracy between cRCC and rO was 85%, 82%, 84%, 77% and 64% for RF, SVM, KNN, CART and LDA. Under the assumption that a reduction of m/z peaks would lead to improved classification accuracy, m/z peaks were ranked based on their variable importance. Reduction to six most important m/z peaks resulted in improved accuracy of 89%, 85%, 85% and 85% for RF, SVM, KNN, and LDA and remained at the level of 77% for CART. t-SNE showed clear separation of cRCC and rO after algorithm improvement. Conclusion: In summary, we acquired MSI data on FFPE tissue specimens of cRCC and rO, performed classification and detected most relevant biomarkers for the differential diagnosis of both diseases. MSI data might be a useful adjunct method in the differential diagnosis of cRCC and rO

In Situ Metabolomics Expands the Spectrum of Renal Tumours Positive on Tc-99(m)-sestamibi Single Photon Emission Computed Tomography/Computed Tomography Examination

Background: Definite noninvasive characterisation of renal tumours positive on Tc-99m-sestamibi single photon emission computed tomography/computed tomography (SPECT/CT) examination including renal oncocytomas (ROs), hybrid oncocytic chromophobe tumours (HOCTs), and chromophobe renal cell carcinoma (chRCC) is currently not feasible. Objective: To investigate whether combined Tc-99m-sestamibi SPECT/CT and in situ metabolomic profiling can accurately characterise renal tumours exhibiting Tc-99m-sestamibi uptake. Design, setting, and participants: A tissue microarray analysis of 33 tumour samples from 28 patients was used to investigate whether their in situ metabolomic status correlates with their features on Tc-99m-sestamibi SPECT/CT examination. In order to validate emerging data, an independent cohort comprising 117 tumours was subjected to matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI MSI). Outcome measurements and statistical analysis: MALDI MSI data analysis and image generation were facilitated by FlexImaging v. 4.2, while k-means analysis by SCiLS Lab software followed by R-package CARRoT analysis was used for assessing the highest predictive power in the differential of RO versus chRCC. Heatmap-based clustering, sparse partial least-squares discriminant analysis, and volcano plots were created with MetaboAnalyst 3.0. Results and limitations: We identified a discriminatory metabolomic signature for Tc-99m-sestamibi SPECT/CT-positive Birt-Hogg-Dube-associated HOCTs versus other renal oncocytic tumours. Metabolomic differences were also evident between Tc-99m-sestamibi-positive and Tc-99m-sestamibi-negative chRCCs, prompting additional expert review; two of three Tc-99m-sestamibi-positive chRCCs were reclassified as low-grade oncocytic tumours (LOTs). Differences were identified between distal-derived tumours from those of proximal tubule origin, including differences between ROs and chRCCs. Conclusions: The current study expands the spectrum of Tc-99m-sestamibi SPECT/CT-positive renal tumours, encompassing ROs, HOCTs, LOTs, and chRCCs, and supports the feasibility of in situ metabolomic profiling in the diagnostics and classification of renal tumours. Patient summary: For preoperative evaluation of solid renal tumours, Tc-99m-sestamibi single photon emission computed tomography/computed tomography (SPECT/CT) is a novel examination method. To increase diagnostic accuracy, we propose that Tc-99m-sestamibi-positive renal tumours should be biopsied and followed by a combined histometabolomic analysis. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of European Association of Urology