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Formalin‐fixed, paraffin‐embedded (FFPE ), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here, we developed a pressure cycling technology (PCT )‐SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PC a) and diffuse large B‐cell lymphoma (DLBCL ) samples. We show that the proteome patterns of FFPE PC a tissue samples and their analogous fresh‐frozen (FF ) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PC a tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between 1 and 15 years in a biobank and show a high degree of the proteome pattern similarity between two types of histological regions in small FFPE samples, that is, punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of a certain degree of biological variations. Applying the method to two independent DLBCL cohorts, we identified myeloperoxidase, a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PC a and DLBCL have been discovered.
Lymphoepithelioma-like carcinoma of the bladder (LELC-B) is a rare histologic subtype characterized by strong immune cell (IC) infiltrates. A better prognosis and favorable response rates to immune checkpoint inhibitors have been described. We aimed to characterize the molecular profiles and IC infiltration of LELC-B for a better understanding of its therapeutic implications. We identified 11 muscle-invasive bladder cancer cases with pure and mixed LELC-B. Programmed cell death ligand-1 (PD-L1) expression and mismatch repair proteins were evaluated using immunohistochemistry. We calculated the tumor mutational burden and characterized mutational profiles using whole-exome DNA sequencing data. Transcriptomic signatures were detected using the NanoString nCounter PanCancer IO360 Panel. Multiplex immunofluorescence of tumor microenvironment (PD-L1, PanCK, α-SMA, vimentin, CD45, and Ki67) and T cells (CD4, CD3, PD-1, CD163, CD8, and FoxP3) was used to quantify cell populations. All LELC-B cases were highly positive for PD-L1 (median tumor proportion score/tumor cell, 70%; range, 20%-100%; median combined positive score, 100; range, 50-100) and mismatch repair proficient and negative for Epstein-Barr virus infection. IC infiltrates were characterized by a high CD8+ T-cell count and high PD-1/PD-L1 expression on immune and tumor cells. LELC-B showed upregulation of signaling pathways involved in IC response. Most common mutations were found in chromatin remodeling genes causing epigenetic dysregulation. All LELC-B cases showed high tumor mutational burden with a median of 39 mutations/Mb (IQR, 29-66 mutations/Mb). In conclusion, LELC-B is a highly immunogenic tumor, showing strong upregulation of PD-1/PD-L1 and making immune checkpoint inhibitors a promising treatment option.
hintergrund: Männer in Deutschland sterben früher als Frauen und nehmen weniger häufig Krebsvorsorgeuntersuchungen wahr.
Fragestellung: Ziel war die prospektive Evaluation einer „Movember-Gesundheitsinitiative“ am Universitätsklinikum Frankfurt (UKF) im November 2019.
Methoden: Im Rahmen der „Movember-Gesundheitsinitiative“ wurde allen männlichen Mitarbeitern des UKF ab dem 45. Lebensjahr und bei erstgradiger familiärer Vorbelastung eines Prostatakarzinoms ab dem 40. Lebensjahr im November 2019 gemäß S3-Leitlinien der Deutschen Gesellschaft für Urologie (DGU) eine Prostatakarzinom-Vorsorgeuntersuchung angeboten.
Ergebnisse: Insgesamt nahmen 14,4 % der Mitarbeiter teil. Eine familiäre Vorbelastung gaben insgesamt 14,0 % Teilnehmer an. Das mediane Alter betrug 54 Jahre. Der mediane PSA(prostataspezifisches Antigen)-Wert lag bei 0,9 ng/ml, der mediane PSA-Quotient bei 30 %. Bei 5 % (n = 6) zeigte sich ein suspekter Tastbefund in der DRU (digital-rektale Untersuchung). Nach Altersstratifizierung (≤ 50 vs. > 50 Lebensjahre) zeigten sich signifikante Unterschiede im medianen PSA-Wert (0,7 ng/ml vs. 1,0 ng/ml, p < 0,01) und der bereits zuvor durchgeführten urologischen Vorsorge (12,1 vs. 42,0 %, p < 0,01). Vier Teilnehmer (3,3 %) zeigten erhöhte Gesamt-PSA-Werte. Bei 32,2 % der Teilnehmer zeigte sich mindestens ein kontrollbedürftiger Befund. Insgesamt wurden 6 Prostatabiopsien durchgeführt. Hierbei zeigte sich in einem Fall ein intermediate-risk Prostatakarzinom (Gleason 3 + 4, pT3a, pPn1, pNx, R0).
Schlussfolgerungung: Im Rahmen der UKF-Movember-Gesundheitsinitiative 2019 konnten durch ein Vorsorgeangebot 121 Männer für eine Prostatakrebs-Vorsorge inklusive PSA-Testung gewonnen werden. Auffällige/kontrollbedürftige Befunde zeigten sich bei 32,2 %. Bei einem Mitarbeiter wurde ein therapiebedürftiges Prostatakarzinom entdeckt und therapiert.
Background: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efcient diagnostic algorithms.
Methods: Retrospectively, 106 prostate tissue samples from 48 patients (mean age,
66 ± 6.6 years) were included in the study. Patients sufered from prostate cancer (n = 38) or benign prostatic hyperplasia (n = 10) and were treated with radical prostatectomy or Holmium laser enucleation of the prostate, respectively. We constructed tissue microarrays (TMAs) comprising representative malignant (n = 38) and benign (n = 68) tissue cores. TMAs were processed to histological slides, stained, digitized and assessed for the applicability of machine learning strategies and open–source tools in diagnosis of prostate cancer. We applied the software QuPath to extract features for shape, stain intensity, and texture of TMA cores for three stainings, H&E, ERG, and PIN-4. Three machine learning algorithms, neural network (NN), support vector machines (SVM), and random forest (RF), were trained and cross-validated with 100 Monte Carlo random splits into 70% training set and 30% test set. We determined AUC values for single color channels, with and without optimization of hyperparameters by exhaustive grid search. We applied recursive feature elimination to feature sets of multiple color transforms.
Results: Mean AUC was above 0.80. PIN-4 stainings yielded higher AUC than H&E and
ERG. For PIN-4 with the color transform saturation, NN, RF, and SVM revealed AUC of 0.93 ± 0.04, 0.91 ± 0.06, and 0.92 ± 0.05, respectively. Optimization of hyperparameters improved the AUC only slightly by 0.01. For H&E, feature selection resulted in no increase of AUC but to an increase of 0.02–0.06 for ERG and PIN-4.
Conclusions: Automated pipelines may be able to discriminate with high accuracy between malignant and benign tissue. We found PIN-4 staining best suited for classifcation. Further bioinformatic analysis of larger data sets would be crucial to evaluate the reliability of automated classifcation methods for clinical practice and to evaluate potential discrimination of aggressiveness of cancer to pave the way to automatic precision medicine.
Background: To test the value of immunohistochemistry (IHC) staining in prostate biopsies for changes in biopsy results and its impact on treatment decision-making. Methods: Between January 2017–June 2020, all patients undergoing prostate biopsies were identified and evaluated regarding additional IHC staining for diagnostic purpose. Final pathologic results after radical prostatectomy (RP) were analyzed regarding the effect of IHC at biopsy. Results: Of 606 biopsies, 350 (58.7%) received additional IHC staining. Of those, prostate cancer (PCa) was found in 208 patients (59.4%); while in 142 patients (40.6%), PCa could be ruled out through IHC. IHC patients harbored significantly more often Gleason 6 in biopsy (p < 0.01) and less suspicious baseline characteristics than patients without IHC. Of 185 patients with positive IHC and PCa detection, IHC led to a change in biopsy results in 81 (43.8%) patients. Of these patients with changes in biopsy results due to IHC, 42 (51.9%) underwent RP with 59.5% harboring ≥pT3 and/or Gleason 7–10. Conclusions: Patients with IHC stains had less suspicious characteristics than patients without IHC. Moreover, in patients with positive IHC and PCa detection, a change in biopsy results was observed in >40%. Patients with changes in biopsy results partly underwent RP, in which 60% harbored significant PCa.
Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition single-shot turbo spin-echo (HASTE), T2w turbo spin-echo (TSE), T2w fluid-attenuated inversion recovery (FLAIR), T2 map and T1-weighted (T1w) TSE. Images were resampled to isotropic voxels. Fruits were segmented. The workflow was repeated by a second reader and the first reader after a pause of one month. We applied PyRadiomics to extract 107 radiomic features per fruit and sequence from seven feature classes. We calculated concordance correlation coefficients (CCC) and dynamic range (DR) to obtain measurements of feature robustness. Intraclass correlation coefficient (ICC) was calculated to assess intra- and inter-observer reproducibility. We calculated Gini scores to test the pairwise discriminative power specific for the features and MRI sequences. We depict Bland Altmann plots of features with top discriminative power (Mann–Whitney U test). Shape features were the most robust feature class. T2 map was the most robust imaging technique (robust features (rf), n = 84). HASTE sequence led to the least amount of rf (n = 20). Intra-observer ICC was excellent (≥ 0.75) for nearly all features (max–min; 99.1–97.2%). Deterioration of ICC values was seen in the inter-observer analyses (max–min; 88.7–81.1%). Complete robustness across all sequences was found for 8 features. Shape features and T2 map yielded the highest pairwise discriminative performance. Radiomics validity depends on the MRI sequence and feature class. T2 map seems to be the most promising imaging technique with the highest feature robustness, high intra-/inter-observer reproducibility and most promising discriminative power.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
Tumor recurrence and drug resistance are responsible for poor prognosis in colorectal cancer (CRC). DNA mismatch repair (MMR) deficiency or elevated interleukin-8 (IL-8) levels are characteristics of CRCs, which have been independently correlated with treatment resistance to common therapies. We recently demonstrated significantly impaired therapeutical response and increased IL-8 release of CRC cell lines with reduced expression of MMR protein MLH1 as well as cytoskeletal non-erythrocytic spectrin alpha II (SPTAN1). In the present study, decreased intratumoral MLH1 and SPTAN1 expression in CRCs could be significantly correlated with enhanced serum IL-8. Furthermore, using stably reduced SPTAN1-expressing SW480, SW620 or HT-29 cell lines, the RAS-mediated RAF/MEK/ERK pathway was analyzed. Here, a close connection between low SPTAN1 expression, increased IL-8 secretion, enhanced extracellular-signal-regulated kinase (ERK) phosphorylation and a mesenchymal phenotype were detected. The inhibition of ERK by U0126 led to a significant reduction in IL-8 secretion, and the combination therapy of U0126 with FOLFOX optimizes the response of corresponding cancer cell lines. Therefore, we hypothesize that the combination therapy of FOLFOX and U0126 may have great potential to improve drug efficacy on this subgroup of CRCs, showing decreased MLH1 and SPTAN1 accompanied with high serum IL-8 in affected patients.
Penile squamous cell carcinomas are rare tumor entities throughout Europe. Early lymphonodal spread urges for aggressive therapeutic approaches in advanced tumor stages. Therefore, understanding tumor biology and its microenvironment and correlation with known survival data is of substantial interest in order to establish treatment strategies adapted to the individual patient. Fifty-five therapy naïve squamous cell carcinomas, age range between 41 and 85 years with known clinicopathological data, were investigated with the use of tissue microarrays (TMA) regarding the tumor-associated immune cell infiltrate density (ICID). Slides were stained with antibodies against CD3, CD8 and CD20. An image analysis software was applied for evaluation. Data were correlated with clinicopathological characteristics and overall survival. There was a significant increase of ICID in squamous cell carcinomas of the penis in relation to tumor adjacent physiological tissue. Higher CD3-positive ICID was significantly associated with lower tumor stage in our cohort. The ICID was not associated with overall survival. Our data sharpens the view on tumor-associated immune cell infiltrate in penile squamous cell carcinomas with an unbiased digital and automated cell count. Further investigations on the immune cell infiltrate and its prognostic and possible therapeutic impact are needed.
Background: The impact of MRI-lesion targeted (TB) and systematic biopsy (SB) Gleason score (GS) as a predictor for final pathological GS still remains unclear. Methods: All patients with TB + SB, and subsequent radical prostatectomy (RP) between 01/2014-12/2020 were analyzed. Rank correlation coefficient predicted concordance with pathological GS for patients’ TB and SB GS, as well as for the combined effect of SB + TB. Results: Of 159 eligible patients, 77% were biopsy naïve. For SB taken in addition to TB, a Spearman’s correlation of +0.33 was observed regarding final GS. Rates of concordance, upgrading, and downgrading were 37.1, 37.1 and 25.8%, respectively. For TB, a +0.52 correlation was computed regarding final GS. Rates of concordance, upgrading and downgrading for TB biopsy GS were 45.9, 33.3, and 20.8%, respectively. For the combination of SB + TB, a correlation of +0.59 was observed. Rates of concordance, upgrading and downgrading were 49.7, 15.1 and 35.2%, respectively. The combined effect of SB + TB resulted in a lower upgrading rate, relative to TB and SB (both p < 0.001), but a higher downgrading rate, relative to TB (p < 0.01). Conclusions: GS obtained from TB provided higher concordance and lower upgrading and downgrading rates, relative to SB GS with regard to final pathology. The combined effect of SB + TB led to the highest concordance rate and the lowest upgrading rate.