Choroidal Manifestation of Smoldering Myeloma: Case Report.

This case illustrates clinical, histopathological, immunohistochemical, and molecular pathological diagnostic testing of smoldering myeloma with atypical ophthalmic manifestations. In our case, the choroidal lesion presented as a solitary manifestation of a systemic disease. Choroidal lesions of monoclonal plasma cells are extremely rare and should be included in the differential diagnosis of amelanotic choroidal lesions, even if the histopathological examination of the primary lesion is not informative. Clinical course, immunohistochemistry, and molecular pathology are essential components of the diagnostic pathway.

Preoperative Detection of Local Tumor Extent in Patients with Advanced Retinoblastoma: Predictive Value of MRI and Clinical Findings. / Präoperativer Nachweis der lokalen Tumorausdehnung bei Patienten mit fortgeschrittenem Retinoblastom: prädiktiver Wert MR-tomografischer und klinischer Befunde.

OBJECTIVE: Before planned enucleation, local tumor extension in advanced retinoblastoma is routinely assessed preoperatively using high-resolution magnetic resonance imaging (MRI). The aim of our study was to analyse the predictive value of MRI and clinical characteristics for predicting tumor extent, as confirmed by histopathology postoperatively. PATIENTS AND METHODS: All consecutive patients were included who underwent primary enucleation for advanced retinoblastoma after high-resolution MRI examination in our hospital between January 2011 and December 2021. The primary study endpoint was the evaluation of the predictability of histopathological risk factors on preoperative MRI examination. The sensitivity and specificity of the MRI examination with respect to clinically relevant optic nerve infiltration and choroidal infiltration were determined. RESULTS: The mean age of the 209 included patients was 1.6 years (range 1 month to 4.7 years). MRI indicated optic nerve infiltration in 46 (22%) patients, extensive choroidal infiltration in 78 (40.2%) patients, and scleral infiltration in one patient (2.6%). Histopathological examination demonstrated postlaminar optic infiltration in 25 (12%) patients and extensive choroidal infiltration in 17 (8.1%) cases. Scleral infiltration was evident in 8 (3.8%) patients. In the final multivariate analysis, MRI findings of tumor infiltration and a preoperative intraocular pressure ≥ 20 mmHg were independently associated with histopathological evidence of clinically relevant optic nerve (p = 0.033/p = 0.011) and choroidal infiltration (p = 0.005/p = 0.029). The diagnostic accuracy of the prediction models based on the multivariate analysis for the identification of the clinically relevant optic nerve (AUC = 0.755) and choroidal infiltration (AUC = 0.798) was greater than that of purely MRI-based prediction (respectively 0.659 and 0.742). The sensitivity and specificity of MRI examination for determining histopathological risk factors in our cohort were 64% and 65% for clinically relevant optic infiltration and 87% and 64% for clinically relevant choroidal infiltration. CONCLUSION: The local tumor extent of retinoblastoma with infiltration of the optic nerve and choroid can be well estimated based on radiological and clinical characteristics before treatment initiation. The combination of clinical and radiological risk factors supports the possibility of early treatment stratification in retinoblastoma patients.

A quantitative polymerase chain reaction based method for molecular subtype classification of urinary bladder cancer-Stromal gene expressions show higher prognostic values than intrinsic tumor genes.

Transcriptome-based molecular subtypes of muscle-invasive bladder cancer (MIBC) have been shown to be both prognostic and predictive, but are not used in routine clinical practice. We aimed to develop a feasible, reverse transcription quantitative polymerase chain reaction (RT-qPCR)-based method for molecular subtyping. First, we defined a 68-gene set covering tumor intrinsic (luminal, basal, squamous, neuronal, epithelial-to-mesenchymal, in situ carcinoma) and stromal (immune, extracellular matrix, p53-like) signatures. Then, classifier methods with this 68-gene panel were developed in silico and validated on public data sets with available subtype class information (MD Anderson [MDA], The Cancer Genome Atlas [TCGA], Lund, Consensus). Finally, expression of the selected 68 genes was determined in 104 frozen tissue samples of our MIBC cohort by RT-qPCR using the TaqMan Array Card platform and samples were classified by our newly developed classifiers. The prognostic value of each subtype classification system and molecular signature scores were assessed. We found that the reduced marker set combined with the developed classifiers were able to reproduce the TCGA II, MDA, Lund and Consensus subtype classification systems with an overlap of 79%, 76%, 69% and 64%, respectively. Importantly, we could successfully classify 96% (100/104) of our MIBC samples by using RT-qPCR. Neuronal and luminal subtypes and low stromal gene expressions were associated with poor survival. In conclusion, we developed a robust and feasible method for the molecular subtyping according to the TCGA II, MDA, Lund and Consensus classifications. Our results suggest that stromal signatures have a superior prognostic value compared to tumor intrinsic signatures and therefore underline the importance of tumor-stroma interaction during the progression of MIBC.

Anterior chamber enhancement predicts optic nerve infiltration in retinoblastoma.

OBJECTIVES: As described recently, intravenously injected gadolinium-based contrast agent (GBCA) penetrates into the anterior eye chamber (AC) and is drained from the retina to the distal optic nerve (ON) along perivascular spaces, which serves retinal homeostasis and was termed the orbital glymphatic system (GS). Independently, AC enhancement predicted ON infiltration, a major risk factor for advanced retinoblastoma (RB), in a small RB patient cohort. We aimed to review the supposed imaging biomarker for ON infiltration in a large RB cohort and with respect to the recently described orbital GS. METHODS: This IRB-approved retrospective single-center study encompassed 539 orbital MRIs performed with an orbital coil and with the children under general anesthesia. Differences of signal intensity ratios (∆SIRs) of the AC to the lens were determined between non-contrast and GBCA-enhanced T1-weighted images and were correlated with histopathologic presence of ON infiltration. RESULTS: ∆SIR of the RB eye was an independent, significant predictor for ON invasion in multivariate analysis with adjustment for tumor size (p < 0.05) and increased with infiltration level. CONCLUSIONS: GBCA enhancement of the AC predicts ON infiltration. This might be caused by impairment of the orbital glymphatic system, which is supposed to clear toxic metabolites from the retina to the postlaminar ON. In RB with ON infiltration, this efflux path is likely to be inhibited, which is supposed to result in disturbed retinal homeostasis, release of vascular endothelial growth factor, and iris neovascularization, which increases penetration of GBCA into the AC. KEY POINTS: • Infiltration of the optic nerve can be predicted by anterior chamber enhancement after intravenous MRI contrast agent administration. • Increased anterior chamber enhancement in retinoblastoma with optic nerve infiltration might result from dysfunction of the orbital glymphatic system with disturbance of retinal homeostasis and consecutive iris neovascularization.

[Diagnostic principles of thyroid tumors in pathology : Relevant changes due to the current WHO classification]. / Diagnostische Grundlagen von Schilddrüsentumoren in der Pathologie : Relevante Änderungen durch die aktuelle WHO-Klassifikation.

The current edition of the WHO classification of thyroid tumors (2017) contains a number of very relevant changes with considerable consequences for the diagnostic assessment of thyroid specimens. This applies to both the histomorphological examination of surgical specimens and the preoperative fine needle biopsy (FNB). In addition, molecular pathological examinations are becoming increasingly important in the diagnosis of thyroid tumors. Changes affect practically all areas of thyroid tumor diagnostics. Some of these changes have far-reaching consequences that justify a comprehensive commentary and query of the knowledge acquired in the form of this CME article.

Intraarterial Chemotherapy for Retinoblastoma - Initial Experiences of a German Reference Centre. / Intraarterielle Chemotherapie beim Retinoblastom ­ erste Erfahrungen eines deutschen Referenzzentrums.

BACKGROUND: Adequate management of retinoblastoma requires a multidisciplinary and individual approach to treatment. Intraarterial chemotherapy (IAC) is one of the most commonly used treatment modalities, and enables supraselective application of chemotherapy via the ophthalmic artery and is now established in almost all treatment centres. However, published treatment success rates are heterogeneous. There are some unanswered issues regarding sight-threatening ocular complications and the long-term occurrence of secondary malignancies and metastatic disease. The objective of the present study is to analyse the results of a German national reference centre. METHODS: Retrospective analysis of all children with an indication for at least one IAC from April 2010 to April 2020. IAC was used either as primary or recurrence therapy. Obligatory follow-up was at least 6 months. RESULTS: 137 eyes of 127 children with an indication for IAC could be included. 12 eyes with a follow-up of less than 6 months and 37 eyes in which IAC was technically not feasible were excluded. In summary, 88 eyes of 79 children were finally analysed. Mean follow-up was 38 months, ranging from 7 to 117 months. In total, 195 procedures were completed. In 30 eyes (34.1%) IAC was conducted as primary and in 58 (65.9%) as secondary therapy. There was an initial IAC treatment response in 75 eyes (85.2%) with a recurrence-free rate of 61.3%. Eye salvage rate was 68.1% with 28 enucleated eyes in total. Ocular complications were observed in 36 eyes (40.9%), with 19 eyes (21.6%) showing severe sight-threatening and 11 eyes (12.5%) presenting minor non-sight-threatening toxic reactions. During follow-up, 1 child developed a secondary malignancy, 1 child developed metastasis and 1 child died as a consequence of trilateral retinoblastoma. CONCLUSION: In summary, IAC is a potent modality for retinoblastoma treatment and has been very successful, even in advanced disease and heavily pretreated eyes. However, ocular complications should be taken in consideration, especially when the only seeing eye is treated. Long term incidences of secondary malignancies and metastatic diseases should be further investigated in prospective studies.

SOX4, SOX11 and PAX6 mRNA expression was identified as a (prognostic) marker for the aggressiveness of neuroendocrine tumors of the lung by using next-generation expression analysis (NanoString).

BACKGROUND: Neuroendocrine tumors of the lung (NELC) account for 25% of all lung cancer cases and transcription factors may drive dedifferentiation of these tumors. This study was conducted to identify supportive diagnostic and prognostic biomarkers. MATERIALS & METHODS: A total of 16 TC, 13 AC, 16 large cell neuroendocrine carcinomas and 15 small cell lung cancer were investigated for the mRNA expression of 11 transcription factors and related genes (MYB, MYBBP1A, OCT4, PAX6, PCDHB, RBP1, SDCBP, SOX2, SOX4, SOX11, TEAD2). RESULTS: SOX4 (p = 0.0002), SOX11 (p < 0.0001) and PAX6 (p = 0.0002) were significant for tumor type. Elevated PAX6 and SOX11 expression correlated with poor outcome in large cell neuroendocrine carcinomas and small cell lung cancer (p < 0.0001 and p = 0.0232, respectively) based on survival data of 34 patients (57%). CONCLUSION: Aggressiveness of NELC correlated with increasing expression of transcription factors. SOX11 seems to be a highly valuable diagnostic and prognostic marker for aggressive NELC.

Different micro-RNA expression profiles distinguish subtypes of neuroendocrine tumors of the lung: results of a profiling study.

MicroRNAs (miRNAs) are a class of small (∼22 nucleotides), non-coding, highly conserved single-stranded RNAs with posttranscriptional regulatory features, including the regulation of cell proliferation, differentiation, survival, and apoptosis. They are deregulated in a broad variety of tumors showing characteristic expression patterns and can, thus, be used as a diagnostic tool. In contrast to non-small cell carcinoma of the lung neuroendocrine lung tumors, encompassing typical and atypical carcinoids, small cell lung cancer and large cell neuroendocrine lung cancer, no data about deregulation of tumor entity-specific miRNAs are available to date. miRNA expression differences might give useful information about the biological characteristics of these tumors, as well as serve as helpful markers.In 12 pulmonary neuroendocrine tumors classified as either typical carcinoid, atypical, large cell neuroendocrine or small cell lung cancer, screening for 763 miRNAs known to be involved in pulmonary cancerogenesis was conducted by performing 384-well TaqMan low-density array real-time qPCR. In the entire cohort, 44 miRNAs were identified, which showed a significantly different miRNA expression. For 12 miRNAs, the difference was highly significant (P<0.01). Eight miRNAs showed a negative (miR-22, miR-29a, miR-29b, miR-29c, miR-367*; miR-504, miR-513C, miR-1200) and four miRNAs a positive (miR-18a, miR-15b*, miR-335*, miR-1201) correlation to the grade of tumor biology. The miRNAs let-7d; miR-19; miR-576-5p; miR-340*; miR-1286 are significantly associated with survival. Members of the miR-29 family seem to be extremely important in this group of tumors. We found a number of miRNAs, which showed a highly significant deregulation in pulmonary neuroendocrine tumors. Moreover, some of these deregulated miRNAs seem to allow discrimination of the various subtypes of pulmonary neuroendocrine tumors. Thus, the analysis of specific sets of miRNAs can be proposed as diagnostic and/or predictive markers in this group of neoplasias.

Mdm2 protein expression is strongly associated with survival in malignant pleural mesothelioma.

AIMS: TP53 mutations are extremely rare in malignant pleural mesothelioma (MPM). In TP53 wild-type tumors, the functional p53 protein can be inactivated by MDM2. MATERIALS & METHODS: A total of 61 patient samples were tested for their Mdm2 and p53 protein expression levels via immunohistochemistry. RESULTS: This study demonstrates nuclear Mdm2 expression in three out of four mesothelioma cell lines and 21.3% of the MPM specimens investigated. After silencing of the MDM2 gene by siRNA in MPM cell lines, Mdm2 immunoexpression is lost and cells show changes indicative of severe damage. Mdm2 protein expression in MPM is detected in epithelioid and biphasic subtypes only and is significantly associated with poor survival compared with Mdm2-negative tumors. This may be explained by increased Mdm2 levels possibly leading to an increased ubiquitilation and proteasomal degradation of functional p53 protein. CONCLUSION: Expression of Mdm2 is a strong prognostic factor associated with shortened overall survival in MPM.

AI-based digital histopathology for perihilar cholangiocarcinoma: A step, not a jump.

Introduction: Perihilar cholangiocarcinoma (PHCC) is a rare malignancy with limited survival prediction accuracy. Artificial intelligence (AI) and digital pathology advancements have shown promise in predicting outcomes in cancer. We aimed to improve prognosis prediction for PHCC by combining AI-based histopathological slide analysis with clinical factors. Methods: We retrospectively analyzed 317 surgically treated PHCC patients (January 2009-December 2018) at the University Hospital of Essen. Clinical data, surgical details, pathology, and outcomes were collected. Convolutional neural networks (CNN) analyzed whole-slide images. Survival models incorporated clinical and histological features. Results: Among 142 eligible patients, independent survival predictors were tumor grade (G), tumor size (T), and intraoperative transfusion requirement. The CNN-based model combining clinical and histopathological features demonstrates proof of concept in prognosis prediction, limited by histopathological complexity and feature extraction challenges. However, the CNN-based model generated heatmaps assisting pathologists in identifying areas of interest. Conclusion: AI-based digital pathology showed potential in PHCC prognosis prediction, though refinement is necessary for clinical relevance. Future research should focus on enhancing AI models and exploring novel approaches to improve PHCC patient prognosis prediction.

Preemptive tumor profiling for biomarker-stratified early clinical drug development in metastatic breast cancer patients.

Biomarker-stratified cancer pharmacotherapy was pioneered in the care of breast cancer patients. The utility of agents modulating hormone receptors, synthesis of steroid hormones, or HER2-targeting agents has been greatly enhanced by the detection of predictive biomarkers in diagnostic tumor samples. Based on deeper understanding of breast cancer biology multiple drug candidates have been developed to modulate additional molecular targets which may associate with specific biomarker profiles. Accordingly, exploratory biomarkers are increasingly incorporated in early clinical trials, thus demanding a new process of patient selection. Here, we describe the implementation of preemptive, multiplexed biomarker profiling linked to standard diagnostic algorithms for metastatic breast cancer patients treated at the West German Cancer Center. Profiling for experimental biomarkers was prospectively offered to patients with metastatic breast cancer who met generic clinical trial inclusion criteria. Formalin-fixed, paraffin-embedded tumor samples were retrieved and studied for potentially "actionable" biomarkers related to active clinical trials by immunohistochemistry, amplicon sequencing, and in situ hybridization. The clinical course of those "profiled" patients was closely monitored to offer trial participation whenever applicable. Here, we report results from the first 131 patients enrolled in this program. PIK3CA mutations (23 %) and amplifications (2 %), loss of PTEN expression (13 %), and FGFR1 amplifications (8 %) were detected next to established biomarkers such as estrogen (67 %) and progesterone receptor expression (52 %), and HER2 overexpression or amplification (23 %). So far 16 "profiled" patients (12 %) have been enrolled in biomarker-stratified early clinical trials. Preemptive profiling of investigational biomarkers can be integrated into the diagnostic algorithm of a large Comprehensive Cancer Center. Extensive administrative efforts are required to successfully enroll "profiled" patients with metastatic breast cancer in early clinical trials stratified by exploratory biomarkers.

The impact of oxygen supply and erythrocytes during normothermic kidney perfusion.

The influence of erythrocytes and oxygen concentration on kidneys during long-term normothermic kidney perfusion is under debate. This study compares acellular and erythrocyte-based NMP with focus on oxygen delivery to the tissue as well as the effects of high oxygenation on tissue integrity. Pig kidneys were connected to NMP for six hours. The first group (n = 6; AC500) was perfused without addition of oxygen carriers, arterial perfusate pO2 was maintained at 500 mmHg. In the second group (n = 6; RBC500) washed erythrocytes were added to the perfusate at pO2 of 500 mmHg. Third group (n = 6; RBC200) was perfused with erythrocyte containing perfusate at more physiological pO2 of 200 mmHg. Addition of RBC did not relevantly increase oxygen consumption of the kidneys during perfusion. Likewise, there were no differences in kidney functional and injury parameters between AC500 and RBC500 group. Expression of erythropoietin as indicator of tissue hypoxia was comparable in all three groups. Cell free NMP at supraphysiological oxygen partial pressure seems to be a safe alternative to erythrocyte based perfusion without adverse effect on kidney integrity and provides a less cumbersome application of NMP in clinical practice.

PDGF, NGF, and EGF as main contributors to tumorigenesis in high-risk retinoblastoma.

Retinoblastoma (RB) is the most common form of eye cancer experienced in childhood. Its aggressive malignancy is associated with excellent survival rates in high-income countries; however, the prognosis in third-world countries is less favorable. Early diagnosis can maximize the patient's visual outcomes and their survival rate. Therapy should be conducted in highly specialized treatment centers. Intravenous chemotherapy (IVC) in bilaterally affected children currently forms the majority of therapy. Local destructive procedures and local chemotherapies such as intra-arterial chemotherapy (IAC) or intravitreal chemotherapy can be taken into consideration depending on the extent and size of the tumor. Nonetheless, children and parents remain under constant stress, revisiting doctors for medical treatment and fearing vision loss and even enucleation of the eye. Adequate molecular patient stratification to improve targeted therapy is still lacking. This retrospective study analyzed formalin-fixed paraffin-embedded specimens from a cohort of 21 RB samples. A total of 11 of those samples showed undifferentiated retinoblastoma (URB) histopathological risk features, and the other 10 showed differentiated retinoblastoma (DRB) histopathological grading. RNA from all samples was isolated and analyzed via digital gene expression patterns. Conductors of cell survival and DNA repair were dominant in the DRB samples. In contrast, the agents responsible for cell-cycle progression and apoptosis were overexpressed in URB samples. Our work reveals the importance of molecular mechanisms within the immune system subjected to histologic subtypes of RB, providing more detailed background on their genetic behavior. This is of great interest for therapeutic strategies, such as targeted immune- and gene-based therapies, for retinoblastoma.

18F-PSMA Cerenkov Luminescence and Flexible Autoradiography Imaging in a Prostate Cancer Mouse Model and First Results of a Radical Prostatectomy Feasibility Study in Men.

Intraoperative identification of positive resection margins (PRMs) in high-risk prostate cancer (PC) needs improvement. Cerenkov luminescence imaging (CLI) with 68Ga-PSMA-11 is promising, although limited by low residual activity and artificial signals. Here, we aimed to assess the value of CLI and flexible autoradiography (FAR) with 18F-PSMA-1007. Methods: Mice bearing subcutaneous PSMA-avid RM1-PGLS tumors were administered 18F-PSMA-1007, and PET/CT was performed. After the animals had been killed, organs were excised and measured signals in CLI and FAR CLI were correlated with tracer activity concentrations (ACs) obtained from PET/CT. For clinical assessment, 7 high-risk PC patients underwent radical prostatectomy immediately after preoperative 18F-PSMA PET/CT. Contrast-to-noise ratios (CNRs) were calculated for both imaging modalities in intact specimens and after incision above the index lesion. Results: In the heterotopic in vivo mouse model (n = 5), CLI did not detect any lesion. FAR CLI detected a distinct signal in all mice, with a lowest AC of 7.25 kBq/mL (CNR, 5.48). After incision above the index lesion of the prostate specimen, no increased signal was observed at the cancer area in CLI. In contrast, using FAR CLI, a signal was detectable in 6 of 7 patients. The AC in the missed index lesion was 1.85 kBq/mL, resulting in a detection limit of at least 2.06 kBq/mL. Histopathology demonstrated 2 PRMs, neither of which was predicted by CLI or FAR CLI. Conclusion: 18F-PSMA FAR CLI was superior to CLI in tracer-related signal detectability. PC was could be visualized in radical prostatectomy down to 2.06 kBq/mL. However, the detection of PRMs was limited. Direct anatomic correlation of FAR CLI is challenging because of the scintillator overlay.

Histology-Based Prediction of Therapy Response to Neoadjuvant Chemotherapy for Esophageal and Esophagogastric Junction Adenocarcinomas Using Deep Learning.

PURPOSE: Quantifying treatment response to gastroesophageal junction (GEJ) adenocarcinomas is crucial to provide an optimal therapeutic strategy. Routinely taken tissue samples provide an opportunity to enhance existing positron emission tomography-computed tomography (PET/CT)-based therapy response evaluation. Our objective was to investigate if deep learning (DL) algorithms are capable of predicting the therapy response of patients with GEJ adenocarcinoma to neoadjuvant chemotherapy on the basis of histologic tissue samples. METHODS: This diagnostic study recruited 67 patients with I-III GEJ adenocarcinoma from the multicentric nonrandomized MEMORI trial including three German university hospitals TUM (University Hospital Rechts der Isar, Munich), LMU (Hospital of the Ludwig-Maximilians-University, Munich), and UME (University Hospital Essen, Essen). All patients underwent baseline PET/CT scans and esophageal biopsy before and 14-21 days after treatment initiation. Treatment response was defined as a ≥35% decrease in SUVmax from baseline. Several DL algorithms were developed to predict PET/CT-based responders and nonresponders to neoadjuvant chemotherapy using digitized histopathologic whole slide images (WSIs). RESULTS: The resulting models were trained on TUM (n = 25 pretherapy, n = 47 on-therapy) patients and evaluated on our internal validation cohort from LMU and UME (n = 17 pretherapy, n = 15 on-therapy). Compared with multiple architectures, the best pretherapy network achieves an area under the receiver operating characteristic curve (AUROC) of 0.81 (95% CI, 0.61 to 1.00), an area under the precision-recall curve (AUPRC) of 0.82 (95% CI, 0.61 to 1.00), a balanced accuracy of 0.78 (95% CI, 0.60 to 0.94), and a Matthews correlation coefficient (MCC) of 0.55 (95% CI, 0.18 to 0.88). The best on-therapy network achieves an AUROC of 0.84 (95% CI, 0.64 to 1.00), an AUPRC of 0.82 (95% CI, 0.56 to 1.00), a balanced accuracy of 0.80 (95% CI, 0.65 to 1.00), and a MCC of 0.71 (95% CI, 0.38 to 1.00). CONCLUSION: Our results show that DL algorithms can predict treatment response to neoadjuvant chemotherapy using WSI with high accuracy even before therapy initiation, suggesting the presence of predictive morphologic tissue biomarkers.

A Phase II Study of Nab-Paclitaxel and Gemcitabine as First-Line Therapy in Patients with Cholangiocarcinoma Ineligible for Cisplatin-Based Chemotherapy (NACHO).

INTRODUCTION: Gemcitabine and cisplatin is the standard first-line systemic treatment in patients with advanced cholangiocarcinoma (CCA). However, a substantial number of patients do not qualify for cisplatin due to comorbidities or poor performance status. The phase II pilot study NACHO evaluated the efficacy of nab-paclitaxel (125 mg/m2) and gemcitabine (1000 mg/m2) given on days 1, 8, and 15 every 4 weeks as first-line therapy in patients with advanced CCA ineligible for cisplatin-based chemotherapy. METHODS: Patients with any comorbidity precluding cisplatin therapy, such as renal impairment, impaired hearing, increased risk or history for thromboembolic events, intolerance of extensive hydration, or significant cardiovascular disease were eligible. Primary endpoint was overall response rate (ORR) per RECIST 1.1. Secondary endpoints were progression-free survival (PFS), overall survival (OS), safety, and patient reported outcome. RESULTS: From December 2016 to July 2017, 10 patients were prospectively enrolled and treated. The ORR with nab-paclitaxel/gemcitabine was 50%, the disease control rate (DCR) was 90%. Median PFS was 5.7 months (95% CI: 5.3-6.1), and median OS was 7.8 months (95% CI: 5.4-10.2). In total, 13 SAEs were documented without any new safety signals. There were 14 grade 3-4 treatment-related adverse events (TRAEs) in 10 patients of the ITT population. Exploratory subgroup analyses including known prognostic markers were performed. CONCLUSIONS: The NACHO trial supports safety and efficacy of nab-paclitaxel and gemcitabine in patients with advanced CCA ineligible for cisplatin-based therapy and should be further evaluated in a larger prospective trial.

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic and predictive markers. A strong correlation of sarcopenia or overall body composition and survival has been described. Here, we explore whether automated assessment of body composition and liver metastases from standard of care CT images can add to clinical parameters in personalized survival risk prognostication. METHODS: We retrospectively analysed clinical imaging data from 85 patients (50.6% female, mean age 58.9 SD 12.2 years) with colorectal cancer and synchronous liver metastases. Pretrained deep learning models were used to assess body composition and liver metastasis geometry from abdominal CT images before the initiation of systemic treatment. Abdominal muscle-to-bone ratio (MBR) was calculated by dividing abdominal muscle volume by abdominal bone volume. MBR was compared with body mass index (BMI), abdominal muscle volume, and abdominal muscle volume divided by height squared. Differences in overall survival based on body composition and liver metastasis parameters were compared using Kaplan-Meier survival curves. Results were correlated with clinical and biomarker data to develop a machine learning model for survival risk prognostication. RESULTS: The MBR, unlike abdominal muscle volume or BMI, was significantly associated with overall survival (HR 0.39, 95% CI: 0.19-0.80, P = 0.009). The MBR (P = 0.022), liver metastasis surface area (P = 0.01) and primary tumour sidedness (P = 0.007) were independently associated with overall survival in multivariate analysis. Body composition parameters did not correlate with KRAS mutational status or primary tumour sidedness. A prediction model based on MBR, liver metastasis surface area and primary tumour sidedness achieved a concordance index of 0.69. CONCLUSIONS: Automated segmentation enables to extract prognostic parameters from routine imaging data for personalized survival modelling in advanced colorectal cancer patients.

Predictive value of molecular subtypes and APOBEC3G for adjuvant chemotherapy in urothelial bladder cancer.

OBJECTIVE: Although targeted approaches have become available in second- and third-line settings, platinum-based chemotherapy remains the standard first-line treatment for advanced muscle-invasive bladder cancer (MIBC). Therefore, the prediction of platinum resistance is of utmost clinical importance. METHODS: In this study, we established a routine compatible method for the molecular classification of MIBC samples according to various classification systems and applied this method to evaluate the impact of subtypes on survival after adjuvant chemotherapy. This retrospective study included 191 patients with advanced MIBC (pT≥3 or pN+) who underwent radical cystectomy, with or without adjuvant chemotherapy. A 48-gene panel and classifier rule set were established to determine molecular subtypes according to TCGA, MDA, LundTax, and Consensus classifications. Additionally, 12 single platinum-predictive candidate genes were assessed. The results were correlated with patients' clinicopathological and follow-up data and were validated using independent data sets. RESULTS: Our final evaluation of 159 patients demonstrated better survival in the luminal groups for those who received chemotherapy compared with those who did not. In contrast, no such differences were observed in basal subtypes. The use of chemotherapy was associated with better survival in patients with high APOBEC3G expression (p < 0.002). This association was confirmed using an independent data set of patients who received neoadjuvant platinum therapy. CONCLUSIONS: The proposed method robustly replicates the most commonly used transcriptome-based subtype classifications from paraffin-embedded tissue samples. The luminal, but not basal, molecular subtypes had the greatest benefit from adjuvant platinum therapy. We identified and validated APOBEC3G as a novel predictive marker for platinum-treated patients.

Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology.

The segmentation of histopathological whole slide images into tumourous and non-tumourous types of tissue is a challenging task that requires the consideration of both local and global spatial contexts to classify tumourous regions precisely. The identification of subtypes of tumour tissue complicates the issue as the sharpness of separation decreases and the pathologist's reasoning is even more guided by spatial context. However, the identification of detailed tissue types is crucial for providing personalized cancer therapies. Due to the high resolution of whole slide images, existing semantic segmentation methods, restricted to isolated image sections, are incapable of processing context information beyond. To take a step towards better context comprehension, we propose a patch neighbour attention mechanism to query the neighbouring tissue context from a patch embedding memory bank and infuse context embeddings into bottleneck hidden feature maps. Our memory attention framework (MAF) mimics a pathologist's annotation procedure - zooming out and considering surrounding tissue context. The framework can be integrated into any encoder-decoder segmentation method. We evaluate the MAF on two public breast cancer and liver cancer data sets and an internal kidney cancer data set using famous segmentation models (U-Net, DeeplabV3) and demonstrate the superiority over other context-integrating algorithms - achieving a substantial improvement of up to 17% on Dice score. The code is publicly available at https://github.com/tio-ikim/valuing-vicinity.