Enhancing Prostate Cancer Diagnosis: Artificial Intelligence-Driven Virtual Biopsy for Optimal Magnetic Resonance Imaging-Targeted Biopsy Approach and Gleason Grading Strategy.

An optimal approach to magnetic resonance imaging fusion targeted prostate biopsy (PBx) remains unclear (number of cores, intercore distance, Gleason grading [GG] principle). The aim of this study was to develop a precise pixel-wise segmentation diagnostic artificial intelligence (AI) algorithm for tumor detection and GG as well as an algorithm for virtual prostate biopsy that are used together to systematically investigate and find an optimal approach to targeted PBx. Pixel-wise AI algorithms for tumor detection and GG were developed using a high-quality, manually annotated data set (slides n = 442) after fast-track annotation transfer into segmentation style. To this end, a virtual biopsy algorithm was developed that can perform random biopsies from tumor regions in whole-mount whole-slide images with predefined parameters. A cohort of 115 radical prostatectomy (RP) patient cases with clinically significant, magnetic resonance imaging-visible tumors (n = 121) was used for systematic studies of the optimal biopsy approach. Three expert genitourinary (GU) pathologists (Y.T., A.P., A.Q.) participated in the validation. The tumor detection algorithm (aware version sensitivity/specificity 0.99/0.90, balanced version 0.97/0.97) and GG algorithm (quadratic kappa range vs pathologists 0.77-0.78) perform on par with expert GU pathologists. In total, 65,340 virtual biopsies were performed to study different biopsy approaches with the following results: (1) 4 biopsy cores is the optimal number for a targeted PBx, (2) cumulative GG strategy is superior to using maximal Gleason score for single cores, (3) controlling for minimal intercore distance does not improve the predictive accuracy for the RP Gleason score, (4) using tertiary Gleason pattern principle (for AI tool) in cumulative GG strategy might allow better predictions of final RP Gleason score. The AI algorithm (based on cumulative GG strategy) predicted the RP Gleason score of the tumor better than 2 of the 3 expert GU pathologists. In this study, using an original approach of virtual prostate biopsy on the real cohort of patient cases, we find the optimal approach to the biopsy procedure and the subsequent GG of a targeted PBx. We publicly release 2 large data sets with associated expert pathologists' GG and our virtual biopsy algorithm.

Blocking the angiopoietin-2-dependent integrin ß-1 signaling axis abrogates small cell lung cancer invasion and metastasis.

Small cell lung cancer (SCLC) is the most aggressive lung cancer entity with an extremely limited therapeutic outcome. Most patients are diagnosed at an extensive stage. However, the molecular mechanisms driving SCLC invasion and metastasis remain largely elusive. We used an autochthonous SCLC mouse model and matched samples from patients with primary and metastatic SCLC to investigate the molecular characteristics of tumor metastasis. We demonstrate that tumor cell invasion and liver metastasis in SCLC are triggered by an Angiopoietin-2 (ANG-2)/Integrin ß-1-dependent pathway in tumor cells, mediated by focal adhesion kinase/Src kinase signaling. Strikingly, CRISPR-Cas9 KO of Integrin ß-1 or blocking Integrin ß-1 signaling by an anti-ANG-2 treatment abrogates liver metastasis formation in vivo. Interestingly, analysis of a unique collection of matched samples from patients with primary and metastatic SCLC confirmed a strong increase of Integrin ß-1 in liver metastasis in comparison with the primary tumor. We further show that ANG-2 blockade combined with PD-1-targeted by anti-PD-1 treatment displays synergistic treatment effects in SCLC. Together, our data demonstrate a fundamental role of ANG-2/Integrin ß-1 signaling in SCLC cells for tumor cell invasion and liver metastasis and provide a potentially new effective treatment strategy for patients with SCLC.

Impact of FAPI-46/dual-tracer PET/CT imaging on radiotherapeutic management in esophageal cancer.

BACKGROUND: Fibroblast activation protein (FAP) is expressed in the tumor microenvironment (TME) of various cancers. In our analysis, we describe the impact of dual-tracer imaging with Gallium-68-radiolabeled inhibitors of FAP (FAPI-46-PET/CT) and fluorodeoxy-D-glucose (FDG-PET/CT) on the radiotherapeutic management of primary esophageal cancer (EC). METHODS: 32 patients with EC, who are scheduled for chemoradiation, received FDG and FAPI-46 PET/CT on the same day (dual-tracer protocol, 71%) or on two separate days (29%) We compared functional tumor volumes (FTVs), gross tumor volumes (GTVs) and tumor stages before and after PET-imaging. Changes in treatment were categorized as "minor" (adaption of radiation field) or "major" (change of treatment regimen). Immunohistochemistry (IHC) staining for FAP was performed in all patients with available tissue. RESULTS: Primary tumor was detected in all FAPI-46/dual-tracer scans and in 30/32 (93%) of FDG scans. Compared to the initial staging CT scan, 12/32 patients (38%) were upstaged in nodal status after the combination of FDG and FAPI-46 PET scans. Two lymph node metastases were only visible in FAPI-46/dual-tracer. New distant metastasis was observed in 2/32 (6%) patients following FAPI-4 -PET/CT. Our findings led to larger RT fields ("minor change") in 5/32 patients (16%) and changed treatment regimen ("major change") in 3/32 patients after FAPI-46/dual-tracer PET/CT. GTVs were larger in FAPI-46/dual-tracer scans compared to FDG-PET/CT (mean 99.0 vs. 80.3 ml, respectively (p < 0.001)) with similar results for nuclear medical FTVs. IHC revealed heterogenous FAP-expression in all specimens (mean H-score: 36.3 (SD 24.6)) without correlation between FAP expression in IHC and FAPI tracer uptake in PET/CT. CONCLUSION: We report first data on the use of PET with FAPI-46 for patients with EC, who are scheduled to receive RT. Tumor uptake was high and not depending on FAP expression in TME. Further, FAPI-46/dual-tracer PET had relevant impact on management in this setting. Our data calls for prospective evaluation of FAPI-46/dual-tracer PET to improve clinical outcomes of EC.

TERT RNAscope analysis of sub-centimetric papillary thyroid carcinomas and synchronous lymph node metastases.

BACKGROUND: Sub-centrimetric papillary thyroid carcinomas usually have a good prognosis with a cancer specific survival of > 99%, however in up to 65% of patients, lymph node metastases can be observed. Molecular alterations in BRAF, TERT and TP53 are associated with worse clinicopathological outcome in patients with papillary thyroid carcinoma. MATERIAL AND METHODS: Twenty-two cases of papillary thyroid carcinomas measuring ≤ 1 cm with synchronous lymph node metastases were examined regarding morphological patterns and immunohistochemical status of p53, Ki-67, and BRAF V600E status. TERT RNA expression in lymph node metastases were evaluated by RNAScope®. RESULTS: Morphological patterns were heterogeneous in both primary tumors and lymph node metastases. Proliferation indices measured by Ki-67 were low. Both primary and lymph node metastases were wild type for p53 by immunohistochemical analysis. No lymph node metastasis showed TERT expression by RNAScope®. CONCLUSIONS: Our data indicate that TERT expression is not involved in the development early lymph node metastasis in patients with sub-centimetric PTC.

HoLy-Net: Segmentation of histological images of diffuse large B-cell lymphoma.

Over the last years, there has been large progress in automated segmentation and classification methods in histological whole slide images (WSIs) stained with hematoxylin and eosin (H&E). Current state-of-the-art (SOTA) techniques are based on diverse datasets of H&E-stained WSIs of different types of predominantly solid cancer. However, there is a scarcity of methods and datasets enabling segmentation of tumors of the lymphatic system (lymphomas). Here, we propose a solution for segmentation of diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin's lymphoma. Our method applies to both H&E-stained slides and to a broad range of markers stained with immunohistochemistry (IHC). While IHC staining is an important tool in cancer diagnosis and treatment decisions, there are few automated segmentation and classification methods for IHC-stained WSIs. To address the challenges of nuclei segmentation in H&E- and IHC-stained DLBCL images, we propose HoLy-Net - a HoVer-Net-based deep learning model for lymphoma segmentation. We train two different models, one for segmenting H&E- and one for IHC-stained images and compare the test results with the SOTA methods as well as with the original version of HoVer-Net. Subsequently, we segment patient WSIs and perform single cell-level analysis of different cell types to identify patient-specific tumor characteristics such as high level of immune infiltration. Our method outperforms general-purpose segmentation methods for H&E staining in lymphoma WSIs (with an F1 score of 0.899) and is also a unique automated method for IHC slide segmentation (with an F1 score of 0.913). With our solution, we provide a new dataset we denote LyNSeC (lymphoma nuclear segmentation and classification) containing 73,931 annotated cell nuclei from H&E and 87,316 from IHC slides. Our method and dataset open up new avenues for quantitative, large-scale studies of morphology and microenvironment of lymphomas overlooked by the current automated segmentation methods.

Cystic Pelvic Masses in Men: A Presentation of Uncommon Cases and a Literature Review.

Unclear cystic masses in the pelvis in male patients are a rare situation and could be of benign or malignant origin. The underlying diseases demand for specific diagnostic and therapeutic approaches. We present a case series of 3 male patients with different clinical symptoms (perineal pain, urinary retention and a large scrotal cyst) related to cystic lesions in the pelvic region. On all patients initial histopathological workup was unclear. All patients underwent surgery with complete resection of the tumor which revealed a broad spectrum of histopathological findings: unusual form of cystic adenocarcinoma of the prostate, malignant transformation of a dysontogenetic cyst, and finally a very rare diagnosis of a malignant tumor of the Cowper gland. This case series and literature review provide clues for a possible diagnostic and therapeutic approach in the case of unclear pelvic cystic masses and could support urologists during the therapy selection in the future.

Frequency and functional characterization of fusion genes in squamous cell carcinoma of the lung.

INTRODUCTION: In contrast to lung adenocarcinoma (LUAD), targetable genetic alterations are less frequently detected in squamous cell carcinoma of the lung (LUSC). Over the last years, gene fusions have become promising targets in many solid cancers. Here, we analysed a cohort of LUSC, identified recurrent fusion genes and functionally characterised these tumour genomes. METHODS: A subset of 1608 squamous cell carcinomas of the lung was analysed by means of the FusionPlex® Lung Panel to identify potentially targetable gene fusions using targeted next-generation sequencing. Cases harbouring recurrent gene fusions were further analysed using FISH, Cytoscan HD arrays and cell culture experiments. RESULTS: We found both, known and novel gene fusions in about 3 % of the cases. Known fusions occurring in lung cancer included ALK::EML4, EGFRvIII, EZR::ROS1 and FGFR3::TACC. We further identified recurrent gene fusions of currently unknown biological function, involving EGFR::VSTM2A and NSD3::FGFR1 and showed that the occurrence of the EGFR::VSTM2A fusion is accompanied by high-level amplification of EGFR. Our analyses further revealed that the genomes of these LUSC patients are chromosomally unstable, which leads us to believe that such non-actionable genomic rearrangements may be a result of "chromosomal chaos" most probably not representing exclusive cancer-driving genes in this cancer entity. CONCLUSIONS: We emphasise that caution should be taken when novel fusions are found and that the appearance of new gene fusions should always be interpreted in the molecular context of the respective disease.

Artificial Intelligence-Based Tool for Tumor Detection and Quantitative Tissue Analysis in Colorectal Specimens.

Digital pathology adoption allows for applying computational algorithms to routine pathology tasks. Our study aimed to develop a clinical-grade artificial intelligence (AI) tool for precise multiclass tissue segmentation in colorectal specimens (resections and biopsies) and clinically validate the tool for tumor detection in biopsy specimens. The training data set included 241 precisely manually annotated whole-slide images (WSIs) from multiple institutions. The algorithm was trained for semantic segmentation of 11 tissue classes with an additional module for biopsy WSI classification. Six case cohorts from 5 pathology departments (4 countries) were used for formal and clinical validation, digitized by 4 different scanning systems. The developed algorithm showed high precision of segmentation of different tissue classes in colorectal specimens with composite multiclass Dice score of up to 0.895 and pixel-wise tumor detection specificity and sensitivity of up to 0.958 and 0.987, respectively. In the clinical validation study on multiple external cohorts, the AI tool reached sensitivity of 1.0 and specificity of up to 0.969 for tumor detection in biopsy WSI. The AI tool analyzes most biopsy cases in less than 1 minute, allowing effective integration into clinical routine. We developed and extensively validated a highly accurate, clinical-grade tool for assistive diagnostic processing of colorectal specimens. This tool allows for quantitative deciphering of colorectal cancer tissue for development of prognostic and predictive biomarkers and personalization of oncologic care. This study is a foundation for a SemiCOL computational challenge. We open-source multiple manually annotated and weakly labeled test data sets, representing a significant contribution to the colorectal cancer computational pathology field.

An international multi-institutional validation study of the algorithm for prostate cancer detection and Gleason grading.

Pathologic examination of prostate biopsies is time consuming due to the large number of slides per case. In this retrospective study, we validate a deep learning-based classifier for prostate cancer (PCA) detection and Gleason grading (AI tool) in biopsy samples. Five external cohorts of patients with multifocal prostate biopsy were analyzed from high-volume pathology institutes. A total of 5922 H&E sections representing 7473 biopsy cores from 423 patient cases (digitized using three scanners) were assessed concerning tumor detection. Two tumor-bearing datasets (core n = 227 and 159) were graded by an international group of pathologists including expert urologic pathologists (n = 11) to validate the Gleason grading classifier. The sensitivity, specificity, and NPV for the detection of tumor-bearing biopsies was in a range of 0.971-1.000, 0.875-0.976, and 0.988-1.000, respectively, across the different test cohorts. In several biopsy slides tumor tissue was correctly detected by the AI tool that was initially missed by pathologists. Most false positive misclassifications represented lesions suspicious for carcinoma or cancer mimickers. The quadratically weighted kappa levels for Gleason grading agreement for single pathologists was 0.62-0.80 (0.77 for AI tool) and 0.64-0.76 (0.72 for AI tool) for the two grading datasets, respectively. In cases where consensus for grading was reached among pathologists, kappa levels for AI tool were 0.903 and 0.855. The PCA detection classifier showed high accuracy for PCA detection in biopsy cases during external validation, independent of the institute and scanner used. High levels of agreement for Gleason grading were indistinguishable between experienced genitourinary pathologists and the AI tool.

Digital droplet PCR-based quantification of ccfHPV-DNA as liquid biopsy in HPV-driven cervical and vulvar cancer.

PURPOSE: More than 99% of cervical cancers and up to 40% of vulvar cancers are human papillomavirus (HPV) related. HPV 16 and 18 are the most relevant subtypes. Novel technologies allow the detection of minimal amounts of circulating cell-free HPV DNA (ccfHPV-DNA). The aim of this study was to evaluate ccfHPV-DNA assessed by droplet digital PCR (ddPCR) as a biomarker for molecular therapy monitoring in early, advanced, relapsed and metastatic HPV-driven cervical and vulvar cancer. METHODS: Inclusion criteria of the study were histologically proven HPV 16/18-driven cervical and vulvar cancer with first diagnosed disease, newly diagnosed recurrence, or progression of disease. Blood samples were taken pre- and post-therapeutically. Circulating cell-free HPV DNA was quantified using ddPCR and the results were correlated with clinical data. RESULTS: The mean copy number of ccfHPV-DNA was 838.6 (± 3089.1) in pretreatment and 2.3 (± 6.4) in post-treatment samples (p < 0.05). The copy number of ccfHPV-DNA increased with higher FIGO stages (p < 0.05), which are commonly used for clinical staging/assessment. Furthermore, we compared the distribution of copy numbers between T-stage 1 versus T-stage 2/3. We could show higher copy number level of ccfHPV-DNA in T-stage 2/3 (p < 0.05). CONCLUSIONS: Therapy monitoring with determination of ccfHPV-DNA by ddPCR with a small amount of plasma reflects response to therapy and appears feasible for patients in advanced cancer stages of cervical and vulvar cancer. This promising tool should be examined as marker of therapy monitoring in particular in novel HPV-directed therapies.

Radiomics for the non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to non-small cell lung cancer.

BACKGROUND: The expression level of the programmed cell death ligand 1 (PD-L1) appears to be a predictor for response to immunotherapy using checkpoint inhibitors in patients with non-small cell lung cancer (NSCLC). As differences in terms of PD-L1 expression levels in the extracranial primary tumor and the brain metastases may occur, a reliable method for the non-invasive assessment of the intracranial PD-L1 expression is, therefore of clinical value. Here, we evaluated the potential of radiomics for a non-invasive prediction of PD-L1 expression in patients with brain metastases secondary to NSCLC. PATIENTS AND METHODS: Fifty-three NSCLC patients with brain metastases from two academic neuro-oncological centers (group 1, n = 36 patients; group 2, n = 17 patients) underwent tumor resection with a subsequent immunohistochemical evaluation of the PD-L1 expression. Brain metastases were manually segmented on preoperative T1-weighted contrast-enhanced MRI. Group 1 was used for model training and validation, group 2 for model testing. After image pre-processing and radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. The radiomics model was trained and validated using random stratified cross-validation. Finally, the best-performing radiomics model was applied to the test data. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analyses. RESULTS: An intracranial PD-L1 expression (i.e., staining of at least 1% or more of tumor cells) was present in 18 of 36 patients (50%) in group 1, and 7 of 17 patients (41%) in group 2. Univariate analysis identified the contrast-enhancing tumor volume as a significant predictor for PD-L1 expression (area under the ROC curve (AUC), 0.77). A random forest classifier using a four-parameter radiomics signature, including tumor volume, yielded an AUC of 0.83 ± 0.18 in the training data (group 1), and an AUC of 0.84 in the external test data (group 2). CONCLUSION: The developed radiomics classifiers allows for a non-invasive assessment of the intracranial PD-L1 expression in patients with brain metastases secondary to NSCLC with high accuracy.

Artificial intelligence for tumour tissue detection and histological regression grading in oesophageal adenocarcinomas: a retrospective algorithm development and validation study.

BACKGROUND: Oesophageal adenocarcinoma and adenocarcinoma of the oesophagogastric junction are among the most common malignant epithelial tumours. Most patients receive neoadjuvant therapy before complete tumour resection. Histological assessment after resection includes identification of residual tumour tissue and areas of regressive tumour, data which are used to calculate a clinically relevant regression score. We developed an artificial intelligence (AI) algorithm for tumour tissue detection and tumour regression grading in surgical specimens from patients with oesophageal adenocarcinoma or adenocarcinoma of the oesophagogastric junction. METHODS: We used one training cohort and four independent test cohorts to develop, train, and validate a deep learning tool. The material consisted of histological slides from surgically resected specimens from patients with oesophageal adenocarcinoma and adenocarcinoma of the oesophagogastric junction from three pathology institutes (two in Germany, one in Austria) and oesophageal cancer cohort of The Cancer Genome Atlas (TCGA). All slides were from neoadjuvantly treated patients except for those from the TCGA cohort, who were neoadjuvant-therapy naive. Data from training cohort and test cohort cases were extensively manually annotated for 11 tissue classes. A convolutional neural network was trained on the data using a supervised principle. First, the tool was formally validated using manually annotated test datasets. Next, tumour regression grading was assessed in a retrospective cohort of post-neoadjuvant therapy surgical specimens. The grading of the algorithm was compared with that of a group of 12 board-certified pathologists from one department. To further validate the tool, three pathologists processed whole resection cases with and without AI assistance. FINDINGS: Of the four test cohorts, one included 22 manually annotated histological slides (n=20 patients), one included 62 sides (n=15), one included 214 slides (n=69), and the final one included 22 manually annotated histological slides (n=22). In the independent test cohorts the AI tool had high patch-level accuracy for identifying both tumour and regression tissue. When we validated the concordance of the AI tool against analyses by a group of pathologists (n=12), agreement was 63·6% (quadratic kappa 0·749; p<0·0001) at case level. The AI-based regression grading triggered true reclassification of resected tumour slides in seven cases (including six cases who had small tumour regions that were initially missed by pathologists). Use of the AI tool by three pathologists increased interobserver agreement and substantially reduced diagnostic time per case compared with working without AI assistance. INTERPRETATION: Use of our AI tool in the diagnostics of oesophageal adenocarcinoma resection specimens by pathologists increased diagnostic accuracy, interobserver concordance, and significantly reduced assessment time. Prospective validation of the tool is required. FUNDING: North Rhine-Westphalia state, Federal Ministry of Education and Research of Germany, and the Wilhelm Sander Foundation.

ARID1A-deficient bladder cancer is dependent on PI3K signaling and sensitive to EZH2 and PI3K inhibitors.

Metastatic urothelial carcinoma is generally incurable with current systemic therapies. Chromatin modifiers are frequently mutated in bladder cancer, with ARID1A-inactivating mutations present in about 20% of tumors. EZH2, a histone methyltransferase, acts as an oncogene that functionally opposes ARID1A. In addition, PI3K signaling is activated in more than 20% of bladder cancers. Using a combination of in vitro and in vivo data, including patient-derived xenografts, we show that ARID1A-mutant tumors were more sensitive to EZH2 inhibition than ARID1A WT tumors. Mechanistic studies revealed that (a) ARID1A deficiency results in a dependency on PI3K/AKT/mTOR signaling via upregulation of a noncanonical PI3K regulatory subunit, PIK3R3, and downregulation of MAPK signaling and (b) EZH2 inhibitor sensitivity is due to upregulation of PIK3IP1, a protein inhibitor of PI3K signaling. We show that PIK3IP1 inhibited PI3K signaling by inducing proteasomal degradation of PIK3R3. Furthermore, ARID1A-deficient bladder cancer was sensitive to combination therapies with EZH2 and PI3K inhibitors in a synergistic manner. Thus, our studies suggest that bladder cancers with ARID1A mutations can be treated with inhibitors of EZH2 and/or PI3K and revealed mechanistic insights into the role of noncanonical PI3K constituents in bladder cancer biology.

Lymphatic Vessel Invasion in Routine Pathology Reports of Papillary Thyroid Cancer.

Purpose: It is not mandatory to report lymphatic vessel invasion in pathology reports of papillary thyroid cancer (PTC) according to the current Union for International Cancer Control (UICC) TNM (tumor, nodes, and metastases) classification. However, there is some evidence for its correlation with lymph node metastasis (LNM) and prognosis. The aim of this study was to explore the clinical implication of lymphatic vessel invasion documentation of PTC because pathology reports play a pivotal role in postsurgical clinical decision-making in endocrine tumor boards. Methods: Patients undergoing postoperative radioiodine treatment for PTC at the University Hospital of Cologne, Germany between December 2015 and March 2020 were identified. Pathology reports were screened for documentation of lymphatic vessel invasion. Demographics and clinicopathologic data of patients documented, including lymphatic vessel invasion and lymph nodal involvement were analyzed. Results: A total of 578 patients were identified and included. Lymphatic vessel invasion was reported in pathology reports of 366 (63.3%) and omitted in 112 (36.7%) patients. Positive lymphatic vessel invasion (L1) was diagnosed in 67 (18.3%) of 366 patients and was documented as absent (L0) in 299 (81.7%) patients. Lymph nodal (N) status was positive (N+) in 126 (45.6%) and negative (N0) in 150 (54.3%) of these patients. In 54 (80.6%) L1 cases N+ status and in 137 (65.6%) L0 cases N0 status was diagnosed. In 13 (19.4%) cases with L1 status, there were no LNMs (L1 N0). In total, 72 (34.4%) patients had LNM despite L0 status (L0 N+). The sensitivity and specificity of LVI reporting for LNM were 0.42 and 0.91, respectively. Conclusion: In routine pathology reports of PTC used for indication to postoperative radioiodine treatment by a German endocrine tumor board, lymphatic vessel invasion was found to be reported inconsistently and mostly as L0. L1 diagnoses, however, reliably correlated with reported LNM and might, thus, be relevant for clinical decision-making. For this reason, we advocate for standardized pathologic reassessment of lymphatic vessel invasion, in particular for cases where lymph nodes are not included in the pathologic specimen and if L0 is documented.

Radiomics for the noninvasive prediction of the BRAF mutation status in patients with melanoma brain metastases.

BACKGROUND: The BRAF V600E mutation is present in approximately 50% of patients with melanoma brain metastases and an important prerequisite for response to targeted therapies, particularly BRAF inhibitors. As heterogeneity in terms of BRAF mutation status may occur in melanoma patients, a wild-type extracranial primary tumor does not necessarily rule out a targetable mutation in brain metastases using BRAF inhibitors. We evaluated the potential of MRI radiomics for a noninvasive prediction of the intracranial BRAF mutation status. METHODS: Fifty-nine patients with melanoma brain metastases from two university brain tumor centers (group 1, 45 patients; group 2, 14 patients) underwent tumor resection with subsequent genetic analysis of the intracranial BRAF mutation status. Preoperative contrast-enhanced MRI was manually segmented and analyzed. Group 1 was used for model training and validation, group 2 for model testing. After radiomics feature extraction, a test-retest analysis was performed to identify robust features prior to feature selection. Finally, the best performing radiomics model was applied to the test data. Diagnostic performances were evaluated using receiver operating characteristic (ROC) analyses. RESULTS: Twenty-two of 45 patients (49%) in group 1, and 8 of 14 patients (57%) in group 2 had an intracranial BRAF V600E mutation. A linear support vector machine classifier using a six-parameter radiomics signature yielded an area under the ROC curve of 0.92 (sensitivity, 83%; specificity, 88%) in the test data. CONCLUSIONS: The developed radiomics classifier allows a noninvasive prediction of the intracranial BRAF V600E mutation status in patients with melanoma brain metastases with high diagnostic performance.

BCG invokes superior STING-mediated innate immune response over radiotherapy in a carcinogen murine model of urothelial cancer.

Radiation and bacillus Calmette-Guérin (BCG) instillations are used clinically for treatment of urothelial carcinoma, but the precise mechanisms by which they activate an immune response remain elusive. The role of the cGAS-STING pathway has been implicated in both BCG and radiation-induced immune response; however, comparison of STING pathway molecules and the immune landscape following treatment in urothelial carcinoma has not been performed. We therefore comprehensively analyzed the local immune response in the bladder tumor microenvironment following radiotherapy and BCG instillations in a well-established spontaneous murine model of urothelial carcinoma to provide insight into activation of STING-mediated immune response. Mice were exposed to the oral carcinogen, BBN, for 12 weeks prior to treatment with a single 15 Gy dose of radiation or three intravesical instillations of BCG (1 × 108 CFU). At sacrifice, tumors were staged by a urologic pathologist and effects of therapy on the immune microenvironment were measured using the NanoString Myeloid Innate Immunity Panel and immunohistochemistry. Clinical relevance was established by measuring immune biomarker expression of cGAS and STING on a human tissue microarray consisting of BCG-treated non-muscle-invasive urothelial carcinomas. BCG instillations in the murine model elevated STING and downstream STING-induced interferon and pro-inflammatory molecules, intratumoral M1 macrophage and T-cell accumulation, and complete tumor eradication. In contrast, radiotherapy caused no changes in STING pathway or innate immune gene expression; rather, it induced M2 macrophage accumulation and elevated FoxP3 expression characteristic of immunosuppression. In human non-muscle-invasive bladder cancer, STING protein expression was elevated at baseline in patients who responded to BCG therapy and increased further after BCG therapy. Overall, these results show that STING pathway activation plays a key role in effective BCG-induced immune response and strongly indicate that the effects of BCG on the bladder cancer immune microenvironment are more beneficial than those induced by radiation. © 2021 The Pathological Society of Great Britain and Ireland.

First description of hematogenously metastasized sclerosing epithelioid fibrosarcoma arising in the uterine cervix.

•First Case of hematogenously metastasized sclerosing epithelioid fibrosarcoma arising primarily in the cervix uteri.•Tumor cells were strongly and diffusely positive for MUC4.•Tumor showed a rare EWSR1-CREB3L2 gene fusion.

NAB2-STAT6 Gene Fusions to Evaluate Primary/Metastasis of Hemangiopericytoma/Solitary Fibrous Tumors.

OBJECTIVES: Hemangiopericytomas (HPCs) and solitary fibrous tumors (SFTs) were considered two distinct entities, but a common gene fusion, NAB2-STAT6, has been identified in both. Although rare, HPCs and SFTs do metastasize, some many years later after resection. Given the extended disease-free interval, it can be difficult to determine with certainty if an HPC or SFT at a new anatomic location represents a second primary or metastatic disease. METHODS: RNA was extracted from formalin-fixed, paraffin-embedded tissue of two patients with multiple SFT/HPC samples. The fusion gene was amplified by reverse transcription polymerase chain reaction (RT-PCR) and a custom-designed Archer FusionPlex panel (94 target genes) and the Illumina NextSeq 550. RESULTS: We identified two patients with multiple resections for HPC/SFT during 26 years at our institution. The first patient had a history of HPC and almost 10 years later she was diagnosed with malignant SFT. The HPC and the SFT shared the same fusion breakpoint. The second patient had multiple lesions in the brain and bone/soft tissue over a 27-year span following a diagnosis of meningeal SFT. Three lesions from this patient shared the same fusion breakpoint. CONCLUSIONS: Our study demonstrated the same fusion breakpoints in primary and metastatic SFTs/HPCs at different time points using both RT-PCR and the Archer fusion panel.

Timing of Development of Symptomatic Brain Metastases from Non-Small Cell Lung Cancer: Impact on Symptoms, Treatment, and Survival in the Era of Molecular Treatments.

OBJECTIVE: We attempted to analyze whether early presentation with brain metastases (BM) represents a poor prognostic factor in patients with non-small cell lung cancer (NSCLC), which should guide the treatment team towards less intensified therapy. PATIENTS AND METHODS: In a retrospective bi-centric analysis, we identified patients receiving surgical treatment for NSCLC BM. We collected demographic-, tumor-, and treatment-related parameters and analyzed their influence on further survival. RESULTS: We included 377 patients. Development of BM was precocious in 99 (26.3%), synchronous in 152 (40.3%), and metachronous in 126 (33.4%) patients. The groups were comparable in terms of age (p = 0.76) and number of metastases (p = 0.11), and histology (p = 0.1); however, mutational status significantly differed (p = 0.002). The precocious group showed the worst clinical status as assessed by Karnofsky performance score (KPS) upon presentation (p < 0.0001). Resection followed by postoperative radiotherapy was the predominant treatment modality for precocious BM, while in syn- and metachronous BM surgical and radio-surgical treatment was balanced. Overall survival (OS) did not differ between the groups (p = 0.76). A good postoperative clinical status (KPS ≥ 70) and the application of any kind of adjuvant systemic therapy were independent predictive factors for OS. CONCLUSION: Early BM presentation was not associated with worse OS in NSCLC BM patients.