NECTIN4 Amplification Is Frequent in Solid Tumors and Predicts Enfortumab Vedotin Response in Metastatic Urothelial Cancer.

PURPOSE: The anti-NECTIN4 antibody-drug conjugate enfortumab vedotin (EV) is approved for patients with metastatic urothelial cancer (mUC). However, durable benefit is only achieved in a small, yet uncharacterized patient subset. NECTIN4 is located on chromosome 1q23.3, and 1q23.3 gains represent frequent copy number variations (CNVs) in urothelial cancer. Here, we aimed to evaluate NECTIN4 amplifications as a genomic biomarker to predict EV response in patients with mUC. MATERIALS AND METHODS: We established a NECTIN4-specific fluorescence in situ hybridization (FISH) assay to assess the predictive value of NECTIN4 CNVs in a multicenter EV-treated mUC patient cohort (mUC-EV, n = 108). CNVs were correlated with membranous NECTIN4 protein expression, EV treatment responses, and outcomes. We also assessed the prognostic value of NECTIN4 CNVs measured in metastatic biopsies of non-EV-treated mUC (mUC-non-EV, n = 103). Furthermore, we queried The Cancer Genome Atlas (TCGA) data sets (10,712 patients across 32 cancer types) for NECTIN4 CNVs. RESULTS: NECTIN4 amplifications are frequent genomic events in muscle-invasive bladder cancer (TCGA bladder cancer data set: approximately 17%) and mUC (approximately 26% in our mUC cohorts). In mUC-EV, NECTIN4 amplification represents a stable genomic alteration during metastatic progression and associates with enhanced membranous NECTIN4 protein expression. Ninety-six percent (27 of 28) of patients with NECTIN4 amplifications demonstrated objective responses to EV compared with 32% (24 of 74) in the nonamplified subgroup (P < .001). In multivariable Cox analysis adjusted for age, sex, and Bellmunt risk factors, NECTIN4 amplifications led to a 92% risk reduction for death (hazard ratio, 0.08 [95% CI, 0.02 to 0.34]; P < .001). In the mUC-non-EV, NECTIN4 amplifications were not associated with outcomes. TCGA Pan-Cancer analysis demonstrated that NECTIN4 amplifications occur frequently in other cancers, for example, in 5%-10% of breast and lung cancers. CONCLUSION: NECTIN4 amplifications are genomic predictors of EV responses and long-term survival in patients with mUC.

Biomarkers of Response to Anti-NECTIN4 Antibody-Drug Conjugate Enfortumab Vedotin in Urothelial Cancer.

Initial studies indicated that NECTIN4 expression is widespread in metastatic urothelial cancer (mUC), which led to approval of the anti-NECTIN4 antibody-drug conjugate (ADC) enfortumab vedotin (EV) for unselected patients with mUC. However, the recent literature suggests that there has been overestimation of membranous NECTIN4 expression in UC, which is a prerequisite for EV binding. It is well established from the development of Her2-targeting ADCs that treatment response is strongly dependent on membranous expression level of the relevant target antigen. In this context, it has been demonstrated that membranous NECTIN4 expression correlates with EV responses and outcomes. Another promising biomarker could be NECTIN4 copy number alteration, a genomic alteration that occurs in approximately 25% of mUC cases, which is associated with strong membranous NECTIN4 expression. Patients with NECTIN4 amplification exhibit an objective response rate of >90% to EV monotherapy and long-term survival. Given the heterogeneous expression of NECTIN4 in UC, future biomarker research is essential for the development of biomarker-driven mUC treatment strategies to further improve outcomes for patients with mUC. PATIENT SUMMARY: We reviewed current evidence on biomarkers for predicting response to enfortumab vedotin (EV) treatment for metastatic urinary tract cancer (mUC). Studies to date have shown that patients with high levels of the protein NECTIN4 on their cancer cells respond well to EV. This information has the potential to guide future treatment strategies for mUC.

Roflumilast inhibits tumor growth and migration in STK11/LKB1 deficient pancreatic cancer.

Pancreatic cancer is a malignant tumor of the digestive system. It is highly aggressive, easily metastasizes, and extremely difficult to treat. This study aimed to analyze the genes that might regulate pancreatic cancer migration to provide an essential basis for the prognostic assessment of pancreatic cancer and individualized treatment. A CRISPR knockout library directed against 915 murine genes was transfected into TB 32047 cell line to screen which gene loss promoted cell migration. Next-generation sequencing and PinAPL.py- analysis was performed to identify candidate genes. We then assessed the effect of serine/threonine kinase 11 (STK11) knockout on pancreatic cancer by wound-healing assay, chick agnosia (CAM) assay, and orthotopic mouse pancreatic cancer model. We performed RNA sequence and Western blotting for mechanistic studies to identify and verify the pathways. After accelerated Transwell migration screening, STK11 was identified as one of the top candidate genes. Further experiments showed that targeted knockout of STK11 promoted the cell migration and increased liver metastasis in mice. Mechanistic analyses revealed that STK11 knockout influences blood vessel morphogenesis and is closely associated with the enhanced expression of phosphodiesterases (PDEs), especially PDE4D, PDE4B, and PDE10A. PDE4 inhibitor Roflumilast inhibited STK11-KO cell migration and tumor size, further demonstrating that PDEs are essential for STK11-deficient cell migration. Our findings support the adoption of therapeutic strategies, including Roflumilast, for patients with STK11-mutated pancreatic cancer in order to improve treatment efficacy and ultimately prolong survival.

Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge.

Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with deterioration of algorithmic performance under shifts in image representations. Considerable covariate shifts occur when assessment is performed on different tumor types, images are acquired using different digitization devices, or specimens are produced in different laboratories. This observation motivated the inception of the 2022 challenge on MItosis Domain Generalization (MIDOG 2022). The challenge provided annotated histologic tumor images from six different domains and evaluated the algorithmic approaches for mitotic figure detection provided by nine challenge participants on ten independent domains. Ground truth for mitotic figure detection was established in two ways: a three-expert majority vote and an independent, immunohistochemistry-assisted set of labels. This work represents an overview of the challenge tasks, the algorithmic strategies employed by the participants, and potential factors contributing to their success. With an F1 score of 0.764 for the top-performing team, we summarize that domain generalization across various tumor domains is possible with today's deep learning-based recognition pipelines. However, we also found that domain characteristics not present in the training set (feline as new species, spindle cell shape as new morphology and a new scanner) led to small but significant decreases in performance. When assessed against the immunohistochemistry-assisted reference standard, all methods resulted in reduced recall scores, with only minor changes in the order of participants in the ranking.

A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67-0.99), 0.8 (95% CI: 0.62-0.99), and 0.81 (95% CI: 0.65-0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

Integration of on-treatment modified Glasgow prognostic score (mGPS) to improve imaging-based prediction of outcomes in patients with non-small cell lung cancer on immune checkpoint inhibition.

INTRODUCTION: A large number of patients with non-small cell lung cancer (NSCLC) on immune checkpoint inhibition (ICI) achieve stable disease (SD) as the best overall response, which is associated with heterogeneous outcomes. In this context, complementary biomarkers that improve outcome prediction are needed. We have recently demonstrated that measuring the on-treatment modified Glasgow prognostic score (mGPS), which is based on the two serum markers C-reactive protein (CRP) and albumin, can improve outcome prediction complementary to radiological staging in metastatic renal cell carcinoma. However, this concept has not been assessed for patients with NSCLC on ICI. METHODS: We assessed the prognostic and predictive value of on-treatment mGPS at week six in patients with NSCLC treated with atezolizumab or docetaxel in the phase 3 OAK trial (NCT02008227) comprising n = 750 patients and validated the findings in the phase 2 BIRCH (NCT02031458, n = 560). RESULTS: On-treatment mGPS assessed at week six demonstrated valuable prognostic information (Hazard Ratio (HR) for mGPS low-risk vs intermediate risk 2.34 (95 % CI 1.76-3.11, p < 0.001) and vs high risk 3.56, (95 % CI 2.57-4.91, p < 0.001) in the atezolizumab-treated subgroup. On-treatment mGPS predicted overall survival more accurately than imaging using RECIST criteria (concordance index: on-treatment mGPS 0.646 (95 % CI 0.615-0.677) vs RECIST 0.606 (95 % CI 0.575-0.637)). On-treatment mGPS provides additional prognostic information to imaging-assessed treatment response at first staging, especially for the patient subgroup with SD. These findings were validated in the BIRCH trial. CONCLUSIONS: We highlight the novel concept of integrating on-treatment mGPS for improved outcome prediction in conjunction with radiological imaging for patients with NSCLC on ICI.

Hypermethylated SHOX2 in circulating cell-free DNA post renal cell carcinoma surgery as TNM-independent biomarker for recurrence risk.

INTRODUCTION: Adjuvant immune checkpoint inhibitor trials in renal cell carcinoma (RCC) call for improved recurrence risk stratification. Due to limitations of circulating tumor DNA (ctDNA) use in RCC, the use of hypermethylated SHOX2 gene (mSHOX2) in circulating cell-free DNA is explored as a surrogate marker for identifying high-risk patients after RCC surgery. METHODS: Liquid biopsies were collected post-surgery from 45 RCC patients (mean duration 4.3 days). Real-time polymerase chain reaction was used to analyze SHOX2 methylation in circulating cell-free DNA. Patients were categorized as mSHOX2 positive or negative by cut-off. Metastasis-free survival (MFS), cancer-specific survival (CSS), and overall survival (OS) were assessed using Cox regression and Log-rank analyses (median follow-up time: 60 months). RESULTS: 17 patients were mSHOX2 positive, showing unfavorable OS/CSS (Log-rank P = 0.004 and 0.02) and nearly 6-fold higher recurrence risk (hazard ratio 5.89, 95% CI 1.46-23.8). Multivariable Cox analysis confirmed mSHOX2 as an independent recurrence risk factor, disregarding TNM-based stratification. CONCLUSIONS: mSHOX2 effectively identifies high-risk RCC patients post-surgery, indicating minimal residual disease. This easy to implement biomarker has potential for guiding of adjuvant therapy decisions.

PITX2 as a Sensitive and Specific Marker of Midgut Neuroendocrine Tumors: Results from a Cohort of 1157 Primary Neuroendocrine Neoplasms.

As neuroendocrine tumors (NETs) often present as metastatic lesions, immunohistochemical assignment to a site of origin is one of the most important tasks in their pathologic assessment. Because a fraction of NETs eludes the typical expression profiles of their primary localization, additional sensitive and specific markers are required to improve diagnostic certainty. We investigated the expression of the transcription factor Pituitary Homeobox 2 (PITX2) in a large-scale cohort of 909 NET and 248 neuroendocrine carcinomas (NEC) according to the immunoreactive score (IRS) and correlated PITX2 expression groups with general tumor groups and primary localization. PITX2 expression (all expression groups) was highly sensitive (98.1%) for midgut-derived NET, but not perfectly specific, as non-midgut NET (especially pulmonary/duodenal) were quite frequently weak or moderately positive. The specificity rose to 99.5% for a midgut origin of NET if only a strong PITX2 expression was considered, which was found in only 0.5% (one pancreatic/one pulmonary) of non-midgut NET. In metastases of midgut-derived NET, PITX2 was expressed in all cases (87.5% strong, 12.5% moderate), whereas CDX2 was negative or only weakly expressed in 31.3% of the metastases. In NEC, a fraction of cases (14%) showed a weak or moderate PITX2 expression, which was not associated with a specific tumor localization. Our study independently validates PITX2 as a very sensitive and specific immunohistochemical marker of midgut-derived NET in a very large collective of neuroendocrine neoplasms. Therefore, our data argue toward implementation into diagnostic panels applied for NET as a firstline midgut marker.

Hybrid ultrasound and single wavelength optoacoustic imaging reveals muscle degeneration in peripheral artery disease.

Peripheral arterial disease (PAD) leads to chronic vascular occlusion and results in end organ damage in critically perfused limbs. There are currently no clinical methods available to determine the muscular damage induced by chronic mal-perfusion. This monocentric prospective cross-sectional study investigated n = 193 adults, healthy to severe PAD, in order to quantify the degree of calf muscle degeneration caused by PAD using a non-invasive hybrid ultrasound and single wavelength optoacoustic imaging (US/SWL-OAI) approach. While US provides morphologic information, SWL-OAI visualizes the absorption of pulsed laser light and the resulting sound waves from molecules undergoing thermoelastic expansion. US/SWL-OAI was compared to multispectral data, clinical disease severity, angiographic findings, phantom experiments, and histological examinations from calf muscle biopsies. We were able to show that synergistic use of US/SWL-OAI is most likely to map clinical degeneration of the muscle and progressive PAD.

Spatial expression of claudin 18.2 in matched primaries and metastases of tubo-ovarian carcinoma of all subtypes.

Physiologically, claudin 18 splice variant 2 (CLDN18.2) expression is restricted to the gastric epithelium, but its expression has been detected in solid cancers. Zolbetuximab, a chimeric IgG1 antibody targeting CLDN18.2, has demonstrated promising effects in patients suffering from CLDN18.2-positive, HER2-negative locally advanced gastric cancer and is currently being studied further. To date, little is known about CLDN18.2 expression in other histological subtypes of tubo-ovarian carcinoma (TOC) and their matching metastases.Using a cohort of all histological TOC subtypes, we investigated the immunohistochemical (IHC) CLDN18.2 expression in both TOCs (n = 536), their matching metastatic tissue (n = 385) and in 93 metastases without primary. Tissue microarrays comprised both the tumor center and periphery. IHC positivity was defined as biomarker expression of ≥ 75% in tumor cells with moderate-to-strong membranous staining.Overall CLDN18.2 positivity was 4.1% (21/515) in the TOC centers and 3.6% (18/498) in their peripheries. In primaries of mucinous tubo-ovarian carcinoma (MTOC), CLDN18.2 positivity rates were 45% (18/40) and 36.6% (15/41), respectively. Positivity rates for the corresponding metastases were 33% (4/12, center) and 27% (3/11, periphery). The expression was relatively homogenous throughout all tumor sites. With no expression in 99.5% of nonmucinous tumors, CLDN18.2 positivity was almost exclusively seen in the mucinous subtype.In tubo-ovarian carcinoma, CLDN18.2 expression was, with rare exceptions, restricted to the mucinous subtype. Among them, 33% of metastasized MTOCs presented with CLDN18.2 positivity. Hence, CLDN18.2 might display a promising target for personalized therapy in patients with advanced MTOC.

Diagnosis of malignancy in oropharyngeal confocal laser endomicroscopy using GPT 4.0 with vision.

PURPOSE: Confocal Laser Endomicroscopy (CLE) is an imaging tool, that has demonstrated potential for intraoperative, real-time, non-invasive, microscopical assessment of surgical margins of oropharyngeal squamous cell carcinoma (OPSCC). However, interpreting CLE images remains challenging. This study investigates the application of OpenAI's Generative Pretrained Transformer (GPT) 4.0 with Vision capabilities for automated classification of CLE images in OPSCC. METHODS: CLE Images of histological confirmed SCC or healthy mucosa from a database of 12 809 CLE images from 5 patients with OPSCC were retrieved and anonymized. Using a training data set of 16 images, a validation set of 139 images, comprising SCC (83 images, 59.7%) and healthy normal mucosa (56 images, 40.3%) was classified using the application programming interface (API) of GPT4.0. The same set of images was also classified by CLE experts (two surgeons and one pathologist), who were blinded to the histology. Diagnostic metrics, the reliability of GPT and inter-rater reliability were assessed. RESULTS: Overall accuracy of the GPT model was 71.2%, the intra-rater agreement was κ = 0.837, indicating an almost perfect agreement across the three runs of GPT-generated results. Human experts achieved an accuracy of 88.5% with a substantial level of agreement (κ = 0.773). CONCLUSIONS: Though limited to a specific clinical framework, patient and image set, this study sheds light on some previously unexplored diagnostic capabilities of large language models using few-shot prompting. It suggests the model`s ability to extrapolate information and classify CLE images with minimal example data. Whether future versions of the model can achieve clinically relevant diagnostic accuracy, especially in uncurated data sets, remains to be investigated.

A novel grading approach predicts worse outcomes in stage pT1 non-muscle-invasive bladder cancer.

OBJECTIVE: To develop a prognostically relevant scoring system for stage pT1 non-muscle-invasive bladder cancer (NMIBC) incorporating tumour budding, growth pattern and invasion pattern because the World Health Organisation grading system shows limited prognostic value in such patients. PATIENTS AND METHODS: The tissue specimens and clinical data of 113 patients with stage pT1 NMIBC who underwent transurethral resection of bladder tumour were retrospectively investigated. Tumour budding, and growth and invasion patterns were evaluated and categorised into two grade groups (GGs). GGs and other clinical and histopathological variables were investigated regarding recurrence-free survival (RFS), progression-free survival (PFS), cancer-specific survival (CSS) and overall survival (OS) using univariable and multivariable Cox regression analyses. RESULTS: The integration of two tumour budding groups, two growth patterns, and two invasion patterns yielded an unfavourable GG (n = 28; 24.7%) that had a high impact on oncological outcomes. The unfavourable GG was identified as an independent RFS and OS predictor (P = 0.004 and P = 0.046, respectively) and linked to worse PFS (P = 0.001) and CSS (P = 0.001), irrespective of the European Association of Urology risk group. The unfavourable GG was associated with higher rates of BCG-unresponsive tumours (P = 0.006). Study limitations include the retrospective, single-centre design, diverse therapies and small cohort. CONCLUSIONS: We present a morphology-based grading system for stage pT1 NMIBC that correlates with disease aggressiveness and oncological patient outcomes. It therefore identifies a highest risk group of stage pT1 NMIBC patients, who should be followed up more intensively or receive immediate radical cystectomy. The grading incorporates objective variables assessable on haematoxylin and eosin slides and immunohistochemistry, enabling an easy-to-use low-cost approach that is applicable in daily routine. Further studies are needed to validate and confirm these results.

Associations of TACSTD2/TROP2 and NECTIN-4/NECTIN-4 with molecular subtypes, PD-L1 expression, and FGFR3 mutational status in two advanced urothelial bladder cancer cohorts.

AIMS: Treatment options for advanced urothelial carcinoma (aUC) rapidly evolved: besides immunomodulative therapeutic options and inhibitors targeting Fibroblast growth factor receptor (FGFR) alterations, two new antibody-drug conjugates (ADC), sacituzumab govitecan (SG) and enfortumab vedotin (EV), have been approved. However, little is known about the associations of specific aUC properties and the surface target expression of TROP2 and NECTIN-4. Our aim was to characterize associations of TACSTD2/TROP2 and NECTIN-4/NECTIN-4 protein and gene expression with morphomolecular and clinicopathological characteristics of aUC in two large independent cohorts. METHODS AND RESULTS: The TCGA BLCA (n = 405) and the CCC-EMN (n = 247) cohorts were retrospectively analysed. TROP2/TACSTD2 and NECTIN-4/NECTIN-4 are highly expressed at the protein and transcript level in aUC, and their expression status did not correlate with patient survival in both cohorts. NECTIN-4/NECTIN-4 expression was higher in luminal tumours and reduced in squamous aUCs. NECTIN-4 was negative in 10.6% of samples, and 18.4% of samples had low expression (H-score <15). The TROP2 negativity rate amounted to 6.5%. TACSTD2 and NECTIN-4 expression was reduced in neuroendocrine-like and/or protein-based double-negative tumours. TROP2- and NECTIN-4-negative tumours included one sarcomatoid and four neuroendocrine aUC. FGFR3 alterations and PD-L1 expression on tumour and immune cells did not associate with TROP2 or NECTIN-4 expression. CONCLUSIONS: TACSTD2/TROP2 and NECTIN-4/NECTIN-4 are widely expressed in aUC, independent of FGFR3 alterations or PD-L1 expression, thus representing a suitable target for ADC treatment in the majority of aUC. The expression loss was associated with aggressive morphomolecular aUC subtypes, i.e. neuroendocrine(-like) and sarcomatoid aUC.

Adipocyte Precursor-Derived NRG1 Promotes Resistance to FGFR Inhibition in Urothelial Carcinoma.

Aberrations of the fibroblast growth factor receptor (FGFR) family members are frequently observed in metastatic urothelial cancer (mUC), and blocking the FGF/FGFR signaling axis is used as a targeted therapeutic strategy for treating patients. Erdafitinib is a pan-FGFR inhibitor, which has recently been approved by the FDA for mUC with FGFR2/3 alterations. Although mUC patients show initial response to erdafitinib, acquired resistance rapidly develops. Here, we found that adipocyte precursors promoted resistance to erdafitinib in FGFR-dependent bladder and lung cancer in a paracrine manner. Moreover, neuregulin 1 (NRG1) secreted from adipocyte precursors was a mediator of erdafitinib resistance by activating human epidermal growth factor receptor 3 (ERBB3; also known as HER3) signaling, and knockdown of NRG1 in adipocyte precursors abrogated the conferred paracrine resistance. NRG1 expression was significantly downregulated in terminally differentiated adipocytes compared with their progenitors. Pharmacologic inhibition of the NRG1/HER3 axis using pertuzumab reversed erdafitinib resistance in tumor cells in vitro and prolonged survival of mice bearing bladder cancer xenografts in vivo. Remarkably, data from single-cell RNA sequencing revealed that NRG1 was enriched in platelet-derived growth factor receptor-A (PDGFRA) expressing inflammatory cancer-associated fibroblasts, which is also expressed on adipocyte precursors. Together, this work reveals a paracrine mechanism of anti-FGFR resistance in bladder cancer, and potentially other cancers, that is amenable to inhibition using available targeted therapies. SIGNIFICANCE: Acquired resistance to FGFR inhibition can be rapidly promoted by paracrine activation of the NRG1/HER3 axis mediated by adipocyte precursors and can be overcome by the combination of pertuzumab and erdafitinib treatment. See related commentary by Kolonin and Anastassiou, p. 648.

An empirical survey on the adaption of neoadjuvant chemotherapy in bladder cancer.

OBJECTIVE: To determine the adaption of neoadjuvant chemotherapy (NAC) in patients with muscle-invasive bladder cancer (MIBC) in Germany, Austria and Switzerland and especially underlying reasons for potential low adherence to guidelines. METHODS: We conducted a non-validated survey amongst 336 urologic departments in Germany, Austria and Switzerland. RedCap questionnaires were electronically distributed and included 23 items concerning the general NAC administration standards and guideline compliance in patient counselling regarding actual treatment. RESULTS: Return rate of the questionnaire was 19.1% (63/336). Although 45 departments (71.4%) claim to perform NAC as standard-of-care, only 49% of eligible patients actually receive NAC. An advanced disease stage (≥cT3) and a high tumor-volume were mentioned to support application of NAC, whereas 35% of responders worry a deterioration of patients' preoperative status due to NAC. Furthermore, 26.7% of respondents are concerned about the low extent of survival benefit. CONCLUSION: Application of NAC in eligible MIBC-patients in Germany, Austria and Switzerland remains low. Although the majority of urologic departments discusses NAC and acknowledges the need for intensified treatment in advanced disease stages, not all eligible patients will actually receive NAC before radical cystectomy.

[Histomolecular classification of urothelial carcinoma of the urinary bladder : From histological phenotype to genotype and back]. / Histomolekulare Klassifikation des Urothelkarzinoms der Harnblase : Vom histologischen Phänotyp zum Genotyp und zurück.

BACKGROUND: Of all urothelial carcinomas (UCs), 25% are muscle invasive and associated with a 5-year overall survival rate of 50%. Findings regarding the molecular classification of muscle-invasive urothelial carcinomas (MIUCs) have not yet found their way into clinical practice. OBJECTIVES: Prediction of molecular consensus subtypes in MIUCs with artificial intelligence (AI) based on histologic hematoxylin-eosin (HE) sections. METHODS: Pathologic review and annotation of The Cancer Genome Atlas (TCGA) Bladder Cancer (BLCA) Cohort (N = 412) and the Dr. Senckenberg Institute of Pathology (SIP) BLCA Cohort (N = 181). An AI model for the prediction of molecular subtypes based on annotated histomorphology was trained. RESULTS: For a five-fold cross-validation with TCGA cases (N = 274), an internal TCGA test set (N = 18) and an external SIP test set (N = 27), we reached mean area under the receiver operating characteristic curve (AUROC) scores of 0.73, 0.8 and 0.75 for the classification of the used molecular subtypes "luminal", "basal/squamous" and "stroma-rich". By training on correlations to individual molecular subtypes, rather than training on one subtype assignment per case, the AI prediction of subtypes could be significantly improved. DISCUSSION: Follow-up studies with RNA extraction from various areas of AI-predicted molecular heterogeneity may improve molecular classifications and thereby AI algorithms trained on these classifications.

Machine Learning-assisted immunophenotyping of peripheral blood identifies innate immune cells as best predictor of response to induction chemo-immunotherapy in head and neck squamous cell carcinoma - knowledge obtained from the CheckRad-CD8 trial.

PURPOSE: Individual prediction of treatment response is crucial for personalized treatment in multimodal approaches against head-and-neck squamous cell carcinoma (HNSCC). So far, no reliable predictive parameters for treatment schemes containing immunotherapy have been identified. This study aims to predict treatment response to induction chemo-immunotherapy based on the peripheral blood immune status in patients with locally advanced HNSCC. METHODS: The peripheral blood immune phenotype was assessed in whole blood samples in patients treated in the phase II CheckRad-CD8 trial as part of the pre-planned translational research program. Blood samples were analyzed by multicolor flow cytometry before (T1) and after (T2) induction chemo-immunotherapy with cisplatin/docetaxel/durvalumab/tremelimumab. Machine Learning techniques were used to predict pathological complete response (pCR) after induction therapy. RESULTS: The tested classifier methods (LDA, SVM, LR, RF, DT, and XGBoost) allowed a distinct prediction of pCR. Highest accuracy was achieved with a low number of features represented as principal components. Immune parameters obtained from the absolute difference (lT2-T1l) allowed the best prediction of pCR. In general, less than 30 parameters and at most 10 principal components were needed for highly accurate predictions. Across several datasets, cells of the innate immune system such as polymorphonuclear cells, monocytes, and plasmacytoid dendritic cells are most prominent. CONCLUSIONS: Our analyses imply that alterations of the innate immune cell distribution in the peripheral blood following induction chemo-immuno-therapy is highly predictive for pCR in HNSCC.

Proposal for a Novel Histological Scoring System as a Potential Grading Approach for Muscle-invasive Urothelial Bladder Cancer Correlating with Disease Aggressiveness and Patient Outcomes.

BACKGROUND: Grading of muscle-invasive bladder cancer (MIBC) according to the current World Health Organization (WHO) criteria is controversial due to its limited prognostic value. All MIBC cases except a tiny minority are of high grade. OBJECTIVE: To develop a prognostic histological scoring system for MIBC integrating histomorphological phenotype, stromal tumor-infiltrating lymphocytes (sTILs), tumor budding, and growth and spreading patterns. DESIGN, SETTING, AND PARTICIPANTS: Tissue specimens and clinical data of 484 patients receiving cystectomy and lymphadenectomy with curative intent with or without adjuvant chemotherapy. Histomorphological phenotypes, sTILs, tumor budding, and growth and spreading patterns were evaluated and categorized into four grade groups (GGs). GGs were correlated with molecular subtypes, immune infiltration, immune checkpoint expression, extracellular matrix (ECM) remodeling, and epithelial-mesenchymal transition (EMT) activity. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: GGs were associated with overall (OS), disease-specific (DSS), and progression-free (PFS) survival in univariable and multivariable analyses. Association with biological features was analyzed with descriptive statistics. RESULTS AND LIMITATIONS: Integration of two histomorphological tumor groups, three sTILs groups, three tumor budding groups, and four growth/spread patterns yielded four novel GGs that had high significance in the univariable survival analysis (OS, DSS, and PFS). GGs were confirmed as independent prognostic predictors with the greatest effect in the multivariable Cox regression analysis. Correlation with molecular data showed a gradual transition from basal to luminal subtypes from GG1 to GG4; a gradual decrease in survival, immune infiltration, and immune checkpoint activity; and a gradual increase in ECM remodeling and EMT activity. CONCLUSIONS: We propose a novel, prognostically relevant, and biologically based scoring system for MIBC in cystectomies applicable to routine pathological sections. PATIENT SUMMARY: We developed a novel approach to assess the aggressiveness of advanced bladder cancer, which allows improved risk stratification compared with the method currently proposed by the World Health Organization.