Evaluation of the prognostic potential of histopathological subtyping in high-grade serous ovarian carcinoma.

High-grade serous ovarian carcinoma (HGSOC) can be categorized into four gene expression-based subtypes, with supposedly distinct prognoses and treatment responses. Murakami et al. translated these gene expression-based subtypes into the histopathological mesenchymal, immunoreactive, solid and proliferative, and papilloglandular subtypes, showing differences in survival outcomes. Miyagawa et al. refined these criteria to improve the interobserver concordance. The current retrospective study evaluated the interobserver variability and the prognostic differences between the histopathologic subtypes using the criteria of both Murakami et al. and Miyagawa et al. in 208 HGSOC cases. The mesenchymal subtype was considered first, followed by the immunoreactive subtype. Non-conforming cases were categorized as solid and proliferative or papilloglandular. The mesenchymal subtype was identified in 122 patients (58.7%) for both criteria. Using the criteria of Murakami et al., 10 cases (4.8%) were immunoreactive, 26 (12.5%) solid and proliferative, and 50 (24%) papilloglandular, with a concordance rate of 62.5% (κ = 0.34, p < .001). Using the Miyagawa et al. criteria, 23 cases (11%) were immunoreactive, 20 (9.6%) solid and proliferative, and 43 (20.7%) papilloglandular. No survival differences were observed between the subtypes. The fair reproducibility of the histopathological subtype classification of HGSOC and the lack of survival differences among these subtypes indicate the need for further refinement of the criteria and exploration of their correlation with overall survival outcomes before clinical application.

The Information Technology (IT) Infrastructure of the Multicenter Archipelago of Ovarian Cancer Research Biobank: A Potential Blueprint for Other Biobanks.

Objective: Biobanks play a crucial role in fundamental and translational research by storing valuable biomaterials and data for future analyses. However, the design of their information technology (IT) infrastructures is often customized to specific requirements, thereby lacking the ability to be used for biobanks comprising other (types of) diseases. This results in substantial costs, time, and efforts for each new biobank project. The Dutch multicenter Archipelago of Ovarian Cancer Research (AOCR) biobank has developed an innovative, reusable IT infrastructure capable of adaptation to various biobanks, thereby enabling cost-effective and efficient implementation and management of biobank IT systems. Methods and Results: The AOCR IT infrastructure incorporates preexisting biobank software, mainly managed by Health-RI. The web-based registration tool Ldot is used for secure storage and pseudonymization of patient data. Clinicopathological data are retrieved from the Netherlands Cancer Registry and the Dutch nationwide pathology databank (Palga), both established repositories, reducing administrative workload and ensuring high data quality. Metadata of collected biomaterials are stored in the OpenSpecimen system. For digital pathology research, a hematoxylin and eosin-stained slide from each patient's tumor is digitized and uploaded to Slide Score. Furthermore, adhering to the Findable, Accessible, Interoperable, and Reusable (FAIR) principles, genomic data derived from the AOCR samples are stored in cBioPortal. Conclusion: The IT infrastructure of the AOCR biobank represents a new standard for biobanks, offering flexibility to handle diverse diseases and types of biomaterials. This infrastructure bypasses the need for disease-specific, custom-built software, thereby being cost- and time-effective while ensuring data quality and legislative compliance. The adaptability of this infrastructure highlights its potential to serve as a blueprint for the development of IT infrastructures in both new and existing biobanks.

Obesity-associated changes in molecular biology of primary breast cancer.

Obesity is associated with an increased risk of developing breast cancer (BC) and worse prognosis in BC patients, yet its impact on BC biology remains understudied in humans. This study investigates how the biology of untreated primary BC differs according to patients' body mass index (BMI) using data from >2,000 patients. We identify several genomic alterations that are differentially prevalent in overweight or obese patients compared to lean patients. We report evidence supporting an ageing accelerating effect of obesity at the genetic level. We show that BMI-associated differences in bulk transcriptomic profile are subtle, while single cell profiling allows detection of more pronounced changes in different cell compartments. These analyses further reveal an elevated and unresolved inflammation of the BC tumor microenvironment associated with obesity, with distinct characteristics contingent on the estrogen receptor status. Collectively, our analyses imply that obesity is associated with an inflammaging-like phenotype. We conclude that patient adiposity may play a significant role in the heterogeneity of BC and should be considered for BC treatment tailoring.

Establishment of the Dutch Nationwide, Interdisciplinary Infrastructure and Biobank for Fundamental and Translational Ovarian Cancer Research: Archipelago of Ovarian Cancer Research.

OBJECTIVES: Ovarian cancer has the worst overall survival rate of all gynecologic malignancies. For the majority of patients, the 5-year overall survival rate of less than 50% has hardly improved over the last decades. To improve the outcome of patients with all subtypes of ovarian cancer, large-scale fundamental and translational research is needed. To accommodate these types of ovarian cancer research, we have established a Dutch nationwide, interdisciplinary infrastructure and biobank: the Archipelago of Ovarian Cancer Research (AOCR). The AOCR will facilitate fundamental and translational ovarian cancer research and enhance interdisciplinary, national, and international collaboration. DESIGN: The AOCR biobank is a prospective ovarian cancer biobank in which biomaterials are collected, processed, and stored in a uniform matter for future (genetic) scientific research. All 19 Dutch hospitals in which ovarian cancer surgery is performed participate and collaborate in the AOCR biobank. PARTICIPANTS/MATERIALS, SETTING, METHODS: Patients of 16 years and older with suspected or diagnosed ovarian, fallopian tube, or primary peritoneal cancer are recruited for participation. Patients who agree to participate give written informed consent for collection, storage, and issue of their biomaterials for future studies. After inclusion, different blood samples are taken at various predefined time points both before and during treatment. In case of a diagnostic paracentesis or biopsy, the residual biomaterials of these procedures are stored in the biobank. During surgery, primary tumor tissue and, if applicable, tissue from metastatic sites are collected and stored. From each patient, a representative histological hematoxylin and eosin stained slide is digitalized for research purposes, including reassessment by a panel of gynecologic pathologists. Clinical and pathological data are obtained on a per-study basis from Dutch registries. Research proposals for the issue of biomaterials and data are evaluated by both the Archipelago Scientific Committee and the Steering Committee. Researchers using the biomaterials from the AOCR biobank are encouraged to enrich the biobank with data and materials resulting from their analyses and experiments. LIMITATIONS: The implementation and first 4 years of collection are financed by an infrastructural grant from the Dutch Cancer Society. Therefore, the main limitation is that the costs for sustaining the biobank after the funding period will have to be covered. This coverage will come from incorporation of budget for biobanking in future grant applications and from fees from external researchers and commercial parties using the biomaterials stored in the AOCR biobank. Moreover, we will apply for grants aimed at sustaining and improving research infrastructures and biobanks. CONCLUSIONS: With the establishment of the Dutch nationwide, interdisciplinary Archipelago of Ovarian Cancer Research infrastructure and biobank, fundamental and translational research on ovarian cancer can be greatly improved. The ultimate aim of this infrastructure is that it will lead to improved diagnostics, treatment, and survival of patients with ovarian cancer.

Ten-year follow-up of the observational RASTER study, prospective evaluation of the 70-gene signature in ER-positive, HER2-negative, node-negative, early breast cancer.

INTRODUCTION: Prognostic gene expression signatures can be used in combination with classical clinicopathological factors to guide adjuvant chemotherapy decisions in ER-positive, HER2-negative breast cancer. However, long-term outcome data after introduction of genomic testing in the treatment decision-making process are limited. METHODS: In the prospective RASTER study, the tumours of 427 patients with cTanyN0M0 breast cancer were tested to assess the 70-gene signature (MammaPrint). The results were provided to their treating physician to be incorporated in the decision-making on adjuvant systemic therapy. Here, we report the long-term outcome of the 310 patients with ER-positive, HER2-negative tumours by clinical and genomic risk categories at a median follow-up of 10.3 years. RESULTS: Among the clinically high-risk patients, 45 (49%) were classified as genomically low risk. In this subgroup, at 10 years, distant recurrence free interval (DRFI) was similar between patients treated with (95.7% [95% CI 87.7-100]) and without (95.5% [95% CI 87.1-100]) chemotherapy. Within the group of clinically low-risk patients, 56 (26%) were classified as genomically high risk. Within the clinically low-risk group, beyond 5 years, a difference emerged between the genomically high- and low-risk subgroup resulting in a 10-year DRFI of 84.3% (95% CI 74.8-95.0) and 93.4% (95% CI 89.5-97.5), respectively. Interestingly, genomic ultralow-risk patients have a 10-year DRFI of 96.7% (95% CI 90.5-100), largely (79%) without systemic therapy. CONCLUSIONS: These data confirm that clinically high-risk, genomically low-risk tumours have an excellent outcome in the real-world setting of shared decision-making. Together with the updated results of the MINDACT trial, these data support the use of the MammaPrint, in ER-positive, HER2-negative, node-negative, clinically high-risk breast cancer patients. REGISTRY: ISRCTN71917916.

Impact of classical and basal-like molecular subtypes on overall survival in resected pancreatic cancer in the SPACIOUS-2 multicentre study.

BACKGROUND: The recently identified classical and basal-like molecular subtypes of pancreatic cancer impact on overall survival (OS). However, the added value of routine subtyping in both clinical practice and randomized trials is still unclear, as most studies do not consider clinicopathological parameters. This study examined the clinical prognostic value of molecular subtyping in patients with resected pancreatic cancer. METHODS: Subtypes were determined on fresh-frozen resected pancreatic cancer samples from three Dutch centres using the Purity Independent Subtyping of Tumours classification. Patient, treatment, and histopathological variables were compared between subtypes. The prognostic value of subtyping in (simulated) pre- and postoperative settings was assessed using Kaplan-Meier and Cox regression analyses. RESULTS: Of 199 patients with resected pancreatic cancer, 164 (82.4 per cent) were classified as the classical and 35 (17.6 per cent) as the basal-like subtype. Patients with a basal-like subtype had worse OS (11 versus 16 months (HR 1.49, 95 per cent c.i. 1.03 to 2.15; P = 0.035)) than patients with a classical subtype. In multivariable Cox regression analysis, including only clinical variables, the basal-like subtype was a statistically significant predictor for poor OS (HR 1.61, 95 per cent c.i. 1.11 to 2.34; P = 0.013). When histopathological variables were added to this model, the prognostic value of subtyping decreased (HR 1.49, 95 per cent c.i. 1.01 to 2.19; P = 0.045). CONCLUSION: The basal-like subtype was associated with worse OS in patients with resected pancreatic cancer. Adding molecular classification to inform on tumor biology may be used in patient stratification.

The impact of a pathologist's personality on the interobserver variability and diagnostic accuracy of predictive PD-L1 immunohistochemistry in lung cancer.

OBJECTIVES: Programmed death-ligand 1 (PD-L1) is the only approved predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). However, predictive PD-L1 immunohistochemistry is subject to interobserver variability. We hypothesized that a pathologist's personality influences the interobserver variability and diagnostic accuracy of PD-L1 immunoscoring. MATERIALS AND METHODS: Seventeen pathologists performed PD-L1 immunoscoring on 50 resected NSCLC tumors in three categories (<1%;1-49%;≥50%). Also, the pathologists completed a certified personality test (NEO-PI-r), assessing five personality traits: neuroticism, extraversion, openness, altruism and conscientiousness. RESULTS: The overall agreement among pathologists for a series of 47 tumors was substantial (kappa = 0.63). Of these, 23/47 (49%) tumors were entirely negative or largely positive, resulting in a kappa value of 0.93. The remaining 24/47 (51%) tumors had a PD-L1 score around the cutoff value, generating a kappa value of 0.32. Pathologists with high scores for conscientiousness (careful, diligent) had the least interobserver variability (r = 0.6, p = 0.009). Also, they showed a trend towards higher sensitivity (74% vs. 68%, p = 0.4), specificity (86% vs. 82%, p = 0.3) and percent agreement (83% vs. 79%, p = 0.3), although not significant. In contrast, pathologists with high scores for neuroticism (sensitive, anxious) had significantly lower specificity (80% vs. 87%, p = 0.03) and percent agreement (78% vs. 85%, p = 0.03). Also, a trend towards high interobserver variability (r = -0.3, p = 0.2) and lower sensitivity (68% vs. 74%, p = 0.3) was observed, although not significant. Pathologists with relatively high scores for conscientiousness scored fewer tumors PD-L1 positive at the ≥ 1% cut-off (r = -0.5, p = 0.03). In contrast, pathologists with relatively high scores for neuroticism score more tumors PD-L1 positive at ≥ 1% (r = 0.6, p = 0.017) and ≥ 50% cut-offs (r = 0.6, p = 0.009). CONCLUSIONS: This study is the first to demonstrate the impact of a pathologist's personality on the interobserver variability and diagnostic accuracy of immunostaining, in the context of PD-L1 in NSCLC. Larger studies are needed for validation of these findings.

Evaluation of Early Response to Preoperative Accelerated Partial Breast Irradiation (PAPBI) by Histopathology, Magnetic Resonance Imaging, and 18F-fluorodexoyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT).

PURPOSE: This study aimed to find indicators for early response to radiation therapy in breast cancer. These would be of help in tailoring treatment for individual patients. METHODS AND MATERIALS: We analyzed 66 patients with low-risk breast cancer (≥60 years; cT1-2pN0) treated within the Preoperative Accelerated Partial Breast Irradiation (PAPBI) trial. Patients received radiation therapy (RT; 10 x 4 Gray or 5 x 6 Gray), followed by a wide local excision after 6 weeks. Patients underwent magnetic resonance imaging (MRI) and 18F-fluorodexoyglucose (FDG) positron emission tomography/computed tomography (PET/CT) before RT and 5 weeks after RT, before surgery. We assessed the response to PAPBI using a histopathologic assessment and correlated this with responses on MRI and FDG PET/CT. We calculated the positive predictive values (PPVs) of MRI and PET/CT as the number of true positives (complete response on MRI/normalized at visual evaluation on PET/CT and pathologic complete response) divided by the number of patients with a complete response on MRI/normalized at visual evaluation on PET/CT. Similarly, the negative predictive values (NPVs) of MRI and PET/CT were calculated. RESULTS: The pathologic response was (nearly) complete in 15 (23%) of the 66 patients and partially complete in 28 (42%). The remaining 23 patients (35%) were nonresponders. The PPV of MRI (Response evaluation criteria in solid tumors [RECIST]) was 87.5% and the NPV was 85%. The PPV and NPV of PET/CT were 25% and 92%, respectively. CONCLUSIONS: The most accurate method to predict a response and residual disease after preoperative RT in low-risk breast cancer was MRI, using RECIST.

A case-control study to identify molecular risk factors for local recurrence in young breast cancer patients.

PURPOSE: To investigate risk factors for local recurrence (LR) after breast conserving therapy in young breast cancer patients randomized in the "Young Boost Trial". MATERIAL & METHODS: In the "Young Boost Trial" 2421 patients ≤50 years old were randomized between a 16 Gy and 26 Gy boost after breast conserving surgery and whole breast radiation (50 Gy). We performed a case-control study comparing patients who developed a LR (cases) and for each of them three control patients free of recurrence (controls). Clinicopathological factors, copy number- and gene expression profiles of primary tumors were compared between cases and controls, and between primary tumors and local recurrences. RESULTS: The cumulative 5-year LR rate was 1.07% (95% CI 0.72-1.59%) and 10-year LR rate 2.56% (1.81-3.62%). Analysis of a subset of primary tumors and local recurrences showed similar histopathological characteristics (n = 15), copy number (n = 13) and gene expression profiles (n = 14). Basal subtype was strongly associated with LR in univariable and multivariable analysis. Gains of CCND1 were identified more frequently among controls, while more frequent gains of FGFR1 and IGF1R were observed among cases. Upregulation of genes involved in the p53-pathway was observed in recurring tumors compared to non-recurring tumors. We could not identify a genomic classifier for LR. CONCLUSIONS: All investigated local recurrences were true genomic recurrences. Although differences in copy number variation and gene expression pathways were observed in recurring tumors compared to non-recurring tumors, no genomic classifier for LR could be identified.

Pathological validation and prognostic potential of quantitative MRI in the characterization of pancreas cancer: preliminary experience.

Patient stratification based on biological variation in pancreatic ductal adenocarcinoma (PDAC) subtypes could help to improve clinical outcome. However, noninvasive assessment of the entire tumor microenvironment remains challenging. In this study, we investigate the biological basis of dynamic contrast-enhanced (DCE), intravoxel incoherent motion (IVIM), and R2*-derived magnetic resonance imaging (MRI) parameters for the noninvasive characterization of the PDAC tumor microenvironment and evaluate their prognostic potential in PDAC patients. Patients diagnosed with treatment-naïve resectable PDAC underwent MRI. After resection, a whole-mount tumor slice was analyzed for collagen fraction, vessel density, and hypoxia and matched to the MRI parameter maps. MRI parameters were correlated to immunohistochemistry-derived tissue characteristics and evaluated for prognostic potential. Thirty patients were included of whom 21 underwent resection with whole-mount histology available in 15 patients. DCE Ktrans and ve , ADC, and IVIM D correlated with collagen fraction. DCE kep and IVIM f correlated with vessel density and R2* with tissue hypoxia. Based on MRI, two main PDAC phenotypes could be distinguished; a stroma-high phenotype demonstrating high vessel density and high collagen fraction and a stroma-low phenotype demonstrating low vessel density and low collagen fraction. Patients with the stroma-high phenotype (high kep and high IVIM D, n = 8) showed longer overall survival (not reached vs. 14 months, P = 0.001, HR = 9.1, P = 0.004) and disease-free survival (not reached vs. 2 months, P < 0.001, HR 9.3, P = 0.003) compared to the other patients (n = 22). Median follow-up was 41 (95% CI: 36-46) months. MRI was able to accurately characterize tumor collagen fraction, vessel density, and hypoxia in PDAC. Based on imaging parameters, a subgroup of patients with significantly better prognosis could be identified. These first results indicate that stratification-based MRI-derived biomarkers could help to tailor treatment and improve clinical outcome and warrant further research.

High-grade mesenchymal pancreatic ductal adenocarcinoma drives stromal deactivation through CSF-1.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by an abundance of stroma. Multiple molecular classification efforts have identified a mesenchymal tumor subtype that is consistently characterized by high-grade growth and poor clinical outcome. The relation between PDAC stroma and tumor subtypes is still unclear. Here, we aimed to identify how PDAC cells instruct the main cellular component of stroma, the pancreatic stellate cells (PSCs). We found in primary tissue that high-grade PDAC had reduced collagen deposition compared to low-grade PDAC. Xenografts and organotypic co-cultures established from mesenchymal-like PDAC cells featured reduced collagen and activated PSC content. Medium transfer experiments using a large set of PDAC cell lines revealed that mesenchymal-like PDAC cells consistently downregulated ACTA2 and COL1A1 expression in PSCs and reduced proliferation. We identified colony-stimulating factor 1 as the mesenchymal PDAC-derived ligand that deactivates PSCs, and inhibition of its receptor CSF1R was able to counteract this effect. In conclusion, high-grade PDAC features stroma that is low in collagen and activated PSC content, and targeting CSF1R offers direct options to maintain a tumor-restricting microenvironment.

Unsupervised class discovery in pancreatic ductal adenocarcinoma reveals cell-intrinsic mesenchymal features and high concordance between existing classification systems.

Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of all common cancers. However, divergent outcomes exist between patients, suggesting distinct underlying tumor biology. Here, we delineated this heterogeneity, compared interconnectivity between classification systems, and experimentally addressed the tumor biology that drives poor outcome. RNA-sequencing of 90 resected specimens and unsupervised classification revealed four subgroups associated with distinct outcomes. The worst-prognosis subtype was characterized by mesenchymal gene signatures. Comparative (network) analysis showed high interconnectivity with previously identified classification schemes and high robustness of the mesenchymal subtype. From species-specific transcript analysis of matching patient-derived xenografts we constructed dedicated classifiers for experimental models. Detailed assessments of tumor growth in subtyped experimental models revealed that a highly invasive growth pattern of mesenchymal subtype tumor cells is responsible for its poor outcome. Concluding, by developing a classification system tailored to experimental models, we have uncovered subtype-specific biology that should be further explored to improve treatment of a group of PDAC patients that currently has little therapeutic benefit from surgical treatment.

Response to Preoperative Radiation Therapy in Relation to Gene Expression Patterns in Breast Cancer Patients.

PURPOSE: We aimed to study radiation-induced gene expression changes and to identify differences in gene expression between patients with and without response to radiation therapy (RT) for invasive breast cancer with the purpose of exploring whether a predictive signature could be developed. Such a signature could assist in optimizing individualized locoregional treatment. METHODS AND MATERIALS: RNA-seq using next-generation sequencing was performed on fresh frozen samples from pretreatment biopsies and post-RT surgery specimens from patients with low-risk breast cancer treated within the multicenter preoperative accelerated partial breast irradiation trial. Patients were treated with preoperative RT (10 × 4 Gy in 10 days or 5 × 6 Gy in 5 days) and a lumpectomy 6 weeks thereafter. The response of the tumor to RT was evaluated by pathologic assessment. To analyze the gene expression data, unsupervised and supervised clustering was performed. Gene expression profiles were compared between biopsies of responders and nonresponders and between samples before and after RT. RESULTS: Ninety-four samples from 77 patients were analyzed: 68 pretreatment biopsies and 26 post-RT surgery specimens. Six patients had a (near) complete pathologic response, 3 patients had a good response, 32 patients had a partial response, and 22 patients had no or very limited response. Comparing patients with and without response to RT, 25 genes were significantly differentially expressed and were not linked to a pathway. Comparison of samples before and after RT identified significant changes in gene expression. Genes involved in p53 signaling, TNFA1 signaling, apoptosis, epithelial mesenchymal transition, and inflammatory response were upregulated. Genes involved in mitotic spindle, G2M checkpoint, and E2F targets were downregulated. CONCLUSIONS: Radiation-induced gene expression changes mainly involved p53 signaling, cell cycle regulation, DNA repair, and inflammatory response. No clinically significant differences could be identified in gene expression between patients with and without response to RT.

Multicentre study on the consistency of PD-L1 immunohistochemistry as predictive test for immunotherapy in non-small cell lung cancer.

AIMS: Investigate the impact of interlaboratory- and interobserver variability of immunohistochemistry on the assessment of programmed death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC). METHODS: Two tissue microarrays (TMAs) were constructed from 50 (TMA-A) and 51 (TMA-B) resected NSCLC cases, and distributed among eight centres. Immunostaining for PD-L1 was performed using Agilent's 22C3 pharmDx Assay (pharmDx) and/or a 22C3 laboratory developed test (LDT). The interlaboratory variability of staining- and interobserver variability of scoring for PD-L1 were assessed in selected critical samples (samples at the cut-off of positivity) and non-critical samples. Also, PD-L1 epitope deterioration in time in stored unstained slides was analysed. Krippendorff's alpha values (0=maximal, 1=no variability) were calculated as measure for variability. RESULTS: For interlaboratory variability of immunostaining, the percentage of PD-L1 positive cases among centres ranged 40%-51% (1% cut-off) and 23%-30% (50% cut-off). Alpha values at 1% cut-off were 0.88 (pharmDx) and 0.87 (LDT) and at 50% cut-off 0.82 (pharmDx) and 0.95 (LDT). Interobserver variability of scoring resulted in PD-L1 positive cases ranging 29%-55% (1% cut-off) and 14%-30% (50% cut-off) among pathologists. Alpha values were at 1% cut-off 0.83 (TMA-A) and 0.66 (TMA-B), and at 50% cut-off 0.77 (TMA-A) and 0.78 (TMA-B). Interlaboratory variability of staining was higher (p<0.001) in critical samples than in non-critical samples at 50% cut-off. Furthermore, PD-L1 epitope deterioration in unstained slides was observed after 12 weeks. CONCLUSIONS: The results provide insight in factors contributing to variability of immunohistochemical assessment of PD-L1, and contribute to more reliable predictive testing for PD-L1.

Circulating tumor DNA quantity is related to tumor volume and both predict survival in metastatic pancreatic ductal adenocarcinoma.

Circulating tumor DNA (ctDNA) is assumed to reflect tumor burden and has been suggested as a tool for prognostication and follow-up in patients with metastatic pancreatic ductal adenocarcinoma (mPDAC). However, the prognostic value of ctDNA and its relation with tumor burden has yet to be substantiated, especially in mPDAC. In this retrospective analysis of prospectively collected samples, cell-free DNA from plasma samples of 58 treatment-naive mPDAC patients was isolated and sequenced using a custom-made pancreatobiliary NGS panel. Pathogenic mutations were detected in 26/58 (44.8%) samples. Cross-check with droplet digital PCR showed good agreement in Bland-Altman analysis (p = 0.217, nonsignificance indicating good agreement). In patients with liver metastases, ctDNA was more frequently detected (24/37, p < 0.001). Tumor volume (3D reconstructions from imaging) and ctDNA variant allele frequency (VAF) were correlated (Spearman's ρ = 0.544, p < 0.001). Median overall survival (OS) was 3.2 (95% confidence interval [CI] 1.6-4.9) versus 8.4 (95% CI 1.6-15.1) months in patients with detectable versus undetectable ctDNA (p = 0.005). Both ctDNA VAF and tumor volume independently predicted OS after adjustment for carbohydrate antigen 19.9 and treatment regimen (hazard ratio [HR] 1.05, 95% CI 1.01-1.09, p = 0.005; HR 1.00, 95% CI 1.01-1.05, p = 0.003). In conclusion, our study showed that ctDNA detection rates are higher in patients with larger tumor volume and liver metastases. Nevertheless, measurements may diverge and, thus, can provide complementary information. Both ctDNA VAF and tumor volume were strong predictors of OS.

Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer.

BACKGROUND: Breast cancer (BC) immune infiltrates play a critical role in tumor progression and response to treatment. Besides stromal tumor infiltrating lymphocytes (sTILs) which have recently reached level 1B evidence as a prognostic marker in triple negative BC, a plethora of methods to assess immune infiltration exists, and it is unclear how these compare to each other and if they can be used interchangeably. METHODS: Two experienced pathologists scored sTIL, intra-tumoral TIL (itTIL), and 6 immune cell types (CD3+, CD4+, CD8+, CD20+, CD68+, FOXP3+) in the International Cancer Genomics Consortium breast cancer cohort using hematoxylin and eosin-stained (n = 243) and immunohistochemistry-stained tissue microarrays (n = 254) and whole slides (n = 82). The same traits were evaluated using transcriptomic- and methylomic-based deconvolution methods or signatures. RESULTS: The concordance correlation coefficient (CCC) between pathologists for sTIL was very good (0.84) and for cell-specific immune infiltrates slightly lower (0.63-0.66). Comparison between tissue microarray and whole slide pathology scores revealed systematically higher values in whole slides (ratio 2.60-5.98). The Spearman correlations between microscopic sTIL and transcriptomic- or methylomic-based assessment of immune infiltrates were highly variable (r = 0.01-0.56). Similar observations were made for cell type-specific quantifications (r = 0.001-0.54). We observed a strong inter-method variability between the omics-derived estimations, which is further cell type dependent. Finally, we demonstrated that most methods more accurately identify highly infiltrated (sTIL ≥ 60%; area under the curve, AUC, 0.64-0.99) as compared to lowly infiltrated tumors (sTIL ≤ 10%; AUC 0.52-0.82). CONCLUSIONS: There is a lower inter-pathologist concordance for cell-specific quantification as compared to overall infiltration quantification. Microscopic assessments are underestimated when considering small cores (tissue microarray) instead of whole slides. Results further highlight considerable differences between the microscopic-, transcriptomic-, and methylomic-based methods in the assessment of overall and cell-specific immune infiltration in BC. We therefore call for extreme caution when assessing immune infiltrates using current methods and emphasize the need for standardized immune characterization beyond TIL.

Lost in translation: confusion on resection and dissection planes hampers the interpretation of pathology reports for perihilar cholangiocarcinoma.

In perihilar cholangiocarcinoma (PHC), interpretation of the resection specimen is challenging for pathologists and clinicians alike. Thorough and correct reporting is necessary for reliable interpretation of residual disease status. The aim of this study is to assess completeness of PHC pathology reports in a single center and assess what hampers interpretation of pathology reports by clinicians. Pathology reports of patients resected for PHC at a single expert tertiary center drafted between 2000 and 2018 were assessed. Reports were assessed regarding completeness, according to the guideline of the International Collaboration on Cancer Reporting (ICCR). A total of 146 reports were assessed. Prognostic tumor characteristics such as vasoinvasive growth and perineural growth were missing in 30/146 (34%) and 22/146 (15%), respectively. One or more planes were missing in 94/146 (64%) of the reports, with the periductal dissection plane missing in 51/145 (35%). Residual disease could be re-classified from R0 to R1 in 22 patients (15%). Reasons for R1 in these patients were the presence of a positive periductal dissection plane (n = 2), < 1-mm margin at the periductal dissection plane (n = 11), or liver parenchyma (n = 9). Completeness of reports improved significantly when drafted by an expert HPB pathologist. This study demonstrates that pathology reporting of PHC is challenging. Reports are frequently incomplete and often do not incorporate assessment of all resection planes and the dissection plane. The periductal dissection plane is frequently overlooked, but is a major cause of residual disease.

Prospective validation of craniocaudal tumour size on MR imaging compared to histoPAthology in patients with uterine cervical cancer: The MPAC study.

PURPOSE: To determine the accuracy of MRI in detecting craniocaudal tumour extension, compared to histopathology, of the hysterectomy specimen in patients with early-stage uterine cervical cancer. Three complementary methods were investigated. MATERIALS AND METHODS: Thirty-four patients with early-stage cervical cancer had pre-operative MRI, followed by radical hysterectomy or trachelectomy. 1) craniocaudal tumour extension was measured on MRI by two radiologists and compared to microscopy by a pathologist, 2) to compensate for changes in uterine shape between pre-operative MRI and the surgical specimen, craniocaudal tumour extensions were directly compared and appreciated as being a part of a 3-dimensional tumour by a radiation oncologist and resident, and 3) tumour size on MRI was compared macroscopically after digital non-rigid registration of the uterus, uterine cavity and tumour of both modalities. RESULTS: The craniocaudal tumour extension measured on histopathology minus MRI gives: 1) on average +3 mm difference when measured by a radiologist compared to the microscopic extension (range -13 to +15 mm), 2) -0.2 mm (range -11 to +6.0 mm) when evaluated on MRI by a radiation oncologist compared to the macroscopic tumour; 3) after non-rigid organ registration, a margin of 10 mm around the tumour on MRI would be needed to cover 95% of the tumour in 90% of the patients. CONCLUSIONS: Results indicate that microscopic tumour extension towards the uterine fundus is within a margin of 10 mm around the visible tumour on MRI. The major source of measurement uncertainty is post-surgical change of organ shape and form.