Development of combination therapies with BTK inhibitors and dasatinib to treat CNS-infiltrating E2A-PBX1+/preBCR+ ALL.

ABSTRACT: The t(1;19) translocation, encoding the oncogenic fusion protein E2A (TCF3)-PBX1, is involved in acute lymphoblastic leukemia (ALL) and associated with a pre-B-cell receptor (preBCR+) phenotype. Relapse in patients with E2A-PBX1+ ALL frequently occurs in the central nervous system (CNS). Therefore, there is a medical need for the identification of CNS active regimens for the treatment of E2A-PBX1+/preBCR+ ALL. Using unbiased short hairpin RNA (shRNA) library screening approaches, we identified Bruton tyrosine kinase (BTK) as a key gene involved in both proliferation and dasatinib sensitivity of E2A-PBX1+/preBCR+ ALL. Depletion of BTK by shRNAs resulted in decreased proliferation of dasatinib-treated E2A-PBX1+/preBCR+ cells compared with control-transduced cells. Moreover, the combination of dasatinib with BTK inhibitors (BTKi; ibrutinib, acalabrutinib, or zanubrutinib) significantly decreased E2A-PBX1+/preBCR+ human and murine cell proliferation, reduced phospholipase C gamma 2 (PLCG2) and BTK phosphorylation and total protein levels and increased disease-free survival of mice in secondary transplantation assays, particularly reducing CNS-leukemic infiltration. Hence, dasatinib with ibrutinib reduced pPLCG2 and pBTK in primary ALL patient samples, including E2A-PBX1+ ALLs. In summary, genetic depletion and pharmacological inhibition of BTK increase dasatinib effects in human and mouse with E2A-PBX1+/preBCR+ ALL across most of performed assays, with the combination of dasatinib and BTKi proving effective in reducing CNS infiltration of E2A-PBX1+/preBCR+ ALL cells in vivo.

Neoadjuvant chemo- or chemo-radiation-therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo-radiation (NCRT) therapy. We employed data-independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment-naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment-naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post-NCT and post-NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment-naïve PDAC. Further analyses on patient survival and protein expression identified treatment-specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment-naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.

AI-Based Detection of Oral Squamous Cell Carcinoma with Raman Histology.

Stimulated Raman Histology (SRH) employs the stimulated Raman scattering (SRS) of photons at biomolecules in tissue samples to generate histological images. Subsequent pathological analysis allows for an intraoperative evaluation without the need for sectioning and staining. The objective of this study was to investigate a deep learning-based classification of oral squamous cell carcinoma (OSCC) and the sub-classification of non-malignant tissue types, as well as to compare the performances of the classifier between SRS and SRH images. Raman shifts were measured at wavenumbers k1 = 2845 cm-1 and k2 = 2930 cm-1. SRS images were transformed into SRH images resembling traditional H&E-stained frozen sections. The annotation of 6 tissue types was performed on images obtained from 80 tissue samples from eight OSCC patients. A VGG19-based convolutional neural network was then trained on 64 SRS images (and corresponding SRH images) and tested on 16. A balanced accuracy of 0.90 (0.87 for SRH images) and F1-scores of 0.91 (0.91 for SRH) for stroma, 0.98 (0.96 for SRH) for adipose tissue, 0.90 (0.87 for SRH) for squamous epithelium, 0.92 (0.76 for SRH) for muscle, 0.87 (0.90 for SRH) for glandular tissue, and 0.88 (0.87 for SRH) for tumor were achieved. The results of this study demonstrate the suitability of deep learning for the intraoperative identification of tissue types directly on SRS and SRH images.

When Should Lymphadenectomy Be Performed in Non-Metastatic Pancreatic Neuroendocrine Tumors? A Population-Based Analysis of the German Clinical Cancer Registry Group.

BACKGROUND: Patient selection for lymphadenectomy remains a controversial aspect in the treatment of pancreatic neuroendocrine tumors (pNETs), given the growing importance of parenchyma-sparing resections and minimally invasive procedures. METHODS: This population-based analysis was derived from the German Cancer Registry Group during the period from 2000 to 2021. Patients with upfront resected non-functional non-metastatic pNETs were included. RESULTS: Out of 5520 patients with pNET, 1006 patients met the inclusion criteria. Fifty-three percent of the patients were male. The median age was 64 ± 17 years. G1, G2, and G3 pNETs were found in 57%, 37%, and 7% of the patients, respectively. Lymph node metastasis (LNM) was present in 253 (24%) of all patients. LNM was an independent prognostic factor (HR 1.79, CI 95% 1.21-2.64, p = 0.001) for disease-free survival (DFS). The 3-, 5-, and 10-year disease-free survival in nodal negative tumors compared to nodal positive was 82% vs. 53%, 75% vs. 38%, and 48% vs. 16%. LNM was present in 5% of T1 tumors, 25% of T2 tumors, and 49% of T3-T4 tumors. In T1 tumors, G1 was the most predominant tumor grade (80%). However, in T2 tumors, G2 and G3 represented 44% and 5% of all tumors. LNM was associated with tumors located in the pancreatic head (p < 0.001), positive resection margin (p < 0.001), tumors larger than 2 cm (p < 0.001), and higher tumor grade (p < 0.001). The multivariable analysis showed that tumor size, tumor grade, and location were independent prognostic factors associated with LNM that could potentially be used to predict LNM preoperatively. CONCLUSION: LNM is an independent negative prognostic factor for DFS in pNETs. Due to the low incidence of LNM in T1 tumors (5%), parenchyma-sparing surgery seems oncologically adequate in small G1 pNETs, while regional lymphadenectomy should be recommended in T2 or G2/G3 pNETs.

Non-invasive monitoring of neoadjuvant radiation therapy response in soft tissue sarcomas by multiparametric MRI and quantification of circulating tumor DNA-A study protocol.

BACKGROUND: Wide resection remains the cornerstone of localized soft-tissue sarcomas (STS) treatment. Neoadjuvant radiation therapy (NRT) may decrease the risk of local recurrences; however, its effectiveness for different histological STS subtypes has not been systematically investigated. The proposed prospective study evaluates the NRT response in STS using liquid biopsies and the correlation of multiparametric magnetic resonance imaging (mpMRI) with histopathology and immunohistochemistry. METHODS: Patients with localized high-grade STS, who qualify for NRT, are included in this study. LIQUID BIOPSIES: Quantification of circulating tumor DNA (ctDNA) in patient blood samples is performed by targeted next-generation sequencing. Soft-tissue sarcoma subtype-specific panel sequencing in combination with patient-specific exome sequencing allows the detection of individual structural variants and point mutations. Circulating free DNA is isolated from peritherapeutically collected patient plasma samples and ctDNA quantified therein. Identification of breakpoints is carried out using FACTERA. Bioinformatic analysis is performed using samtools, picard, fgbio, and the MIRACUM Pipeline. MPMRI: Combination of conventional MRI sequences with diffusion-weighted imaging, intravoxel-incoherent motion, and dynamic contrast enhancement. Multiparametric MRI is performed before, during, and after NRT. We aim to correlate mpMRI data with the resected specimen's macroscopical, histological, and immunohistochemical findings. RESULTS: Preliminary data support the notion that quantification of ctDNA in combination with tumor mass characterization through co-registration of mpMRI and histopathology can predict NRT response of STS. CLINICAL RELEVANCE: The methods presented in this prospective study are necessary to assess therapy response in heterogeneous tumors and lay the foundation of future patient- and tumor-specific therapy concepts. These methods can be applied to various tumor entities. Thus, the participation and support of a wider group of oncologic surgeons are needed to validate these findings on a larger patient cohort.

Hourglass, a rapid analysis framework for heterogeneous bioimaging data, identifies sex disparity in IL-6/STAT3-associated immune phenotypes in pancreatic cancer.

Integration and mining of bioimaging data remains a challenge and lags behind the rapidly expanding digital pathology field. We introduce Hourglass, an open-access analytical framework that streamlines biology-driven visualization, interrogation, and statistical assessment of multiparametric datasets. Cognizant of tissue and clinical heterogeneity, Hourglass systematically organizes observations across spatial and global levels and within patient subgroups. Applied to an extensive bioimaging dataset, Hourglass promptly consolidated a breadth of known interleukin-6 (IL-6) functions via its downstream effector STAT3 and uncovered a so-far unknown sexual dimorphism in the IL-6/STAT3-linked intratumoral T-cell response in human pancreatic cancer. As an R package and cross-platform application, Hourglass facilitates knowledge extraction from multi-layered bioimaging datasets for users with or without computational proficiency and provides unique and widely accessible analytical means to harness insights hidden within heterogeneous tissues at the sample and patient level. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Circulating Epithelial Cells in Patients with Intraductal Papillary Mucinous Neoplasm of the Pancreas.

Intraductal papillary mucinous neoplasm (IPMN) is the most common pancreatic cyst and a precursor of pancreatic cancer (PDAC). Since PDAC has a devastatingly high mortality rate, the early diagnosis and treatment of any precursor lesion are rational. The safety of the existing guidelines on the clinical management of IPMN has been criticized due to unsatisfactory sensitivity and specificity, showing the need for further markers. Blood obtained from patients with IPMN was therefore subjected to size-based isolation of circulating epithelial cells (CECs). We isolated CECs and evaluated their cytological characteristics. Additionally, we compared Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in CECs and the primary IPMN tissue, since KRAS mutations are very typical for PDAC. Samples from 27 IPMN patients were analyzed. In 10 (37%) patients, CECs were isolated and showed a hybrid pattern of surface markers involving both epithelial and mesenchymal markers, suggesting a possible EMT process of the cells. Especially, patients with high-grade dysplasia in the main specimen were all CEC-positive. KRAS mutations were also present in CECs but less common than in IPMN tissue. The existence of CEC in IPMN patients offers additional blood-based research possibilities for IMPN biology.

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

PURPOSE: With the increased use of focal radiation dose escalation for primary prostate cancer (PCa), accurate delineation of gross tumor volume (GTV) in prostate-specific membrane antigen PET (PSMA-PET) becomes crucial. Manual approaches are time-consuming and observer dependent. The purpose of this study was to create a deep learning model for the accurate delineation of the intraprostatic GTV in PSMA-PET. METHODS: A 3D U-Net was trained on 128 different 18F-PSMA-1007 PET images from three different institutions. Testing was done on 52 patients including one independent internal cohort (Freiburg: n = 19) and three independent external cohorts (Dresden: n = 14 18F-PSMA-1007, Boston: Massachusetts General Hospital (MGH): n = 9 18F-DCFPyL-PSMA and Dana-Farber Cancer Institute (DFCI): n = 10 68Ga-PSMA-11). Expert contours were generated in consensus using a validated technique. CNN predictions were compared to expert contours using Dice similarity coefficient (DSC). Co-registered whole-mount histology was used for the internal testing cohort to assess sensitivity/specificity. RESULTS: Median DSCs were Freiburg: 0.82 (IQR: 0.73-0.88), Dresden: 0.71 (IQR: 0.53-0.75), MGH: 0.80 (IQR: 0.64-0.83) and DFCI: 0.80 (IQR: 0.67-0.84), respectively. Median sensitivity for CNN and expert contours were 0.88 (IQR: 0.68-0.97) and 0.85 (IQR: 0.75-0.88) (p = 0.40), respectively. GTV volumes did not differ significantly (p > 0.1 for all comparisons). Median specificity of 0.83 (IQR: 0.57-0.97) and 0.88 (IQR: 0.69-0.98) were observed for CNN and expert contours (p = 0.014), respectively. CNN prediction took 3.81 seconds on average per patient. CONCLUSION: The CNN was trained and tested on internal and external datasets as well as histopathology reference, achieving a fast GTV segmentation for three PSMA-PET tracers with high diagnostic accuracy comparable to manual experts.

Morphologic and molecular analysis of liver injury after SARS-CoV-2 vaccination reveals distinct characteristics.

BACKGROUND & AIMS: Liver injury after COVID-19 vaccination is very rare and shows clinical and histomorphological similarities with autoimmune hepatitis (AIH). Little is known about the pathophysiology of COVID-19 vaccine-induced liver injury (VILI) and its relationship to AIH. Therefore, we compared VILI with AIH. METHODS: Formalin-fixed and paraffin-embedded liver biopsy samples from patients with VILI (n = 6) and from patients with an initial diagnosis of AIH (n = 9) were included. Both cohorts were compared by histomorphological evaluation, whole-transcriptome and spatial transcriptome sequencing, multiplex immunofluorescence, and immune repertoire sequencing. RESULTS: Histomorphology was similar in both cohorts but showed more pronounced centrilobular necrosis in VILI. Gene expression profiling showed that mitochondrial metabolism and oxidative stress-related pathways were more and interferon response pathways were less enriched in VILI. Multiplex analysis revealed that inflammation in VILI was dominated by CD8+ effector T cells, similar to drug-induced autoimmune-like hepatitis. In contrast, AIH showed a dominance of CD4+ effector T cells and CD79a+ B and plasma cells. T-cell receptor (TCR) and B-cell receptor sequencing showed that T and B cell clones were more dominant in VILI than in AIH. In addition, many T cell clones detected in the liver were also found in the blood. Interestingly, analysis of TCR beta chain and Ig heavy chain variable-joining gene usage further showed that TRBV6-1, TRBV5-1, TRBV7-6, and IgHV1-24 genes are used differently in VILI than in AIH. CONCLUSIONS: Our analyses support that SARS-CoV-2 VILI is related to AIH but also shows distinct differences from AIH in histomorphology, pathway activation, cellular immune infiltrates, and TCR usage. Therefore, VILI may be a separate entity, which is distinct from AIH and more closely related to drug-induced autoimmune-like hepatitis. IMPACT AND IMPLICATIONS: Little is known about the pathophysiology of COVID-19 vaccine-induced liver injury (VILI). Our analysis shows that COVID-19 VILI shares some similarities with autoimmune hepatitis, but also has distinct differences such as increased activation of metabolic pathways, a more prominent CD8+ T cell infiltrate, and an oligoclonal T and B cell response. Our findings suggest that VILI is a distinct disease entity. Therefore, there is a good chance that many patients with COVID-19 VILI will recover completely and will not develop long-term autoimmune hepatitis.

Stimulated Raman histology for histological evaluation of oral squamous cell carcinoma.

OBJECTIVES: To investigate whether in patients undergoing surgery for oral squamous cell carcinoma, stimulated Raman histology (SRH), in comparison with H&E-stained frozen sections, can provide accurate diagnoses regarding neoplastic tissue and sub-classification of non-neoplastic tissues. MATERIALS AND METHODS: SRH, a technology based on Raman scattering, was applied to generate digital histopathologic images of 80 tissue samples obtained from 8 oral squamous cell carcinoma (OSCC) patients. Conventional H&E-stained frozen sections were then obtained from all 80 samples. All images/sections (SRH and H&E) were analyzed for squamous cell carcinoma, normal mucosa, connective tissue, muscle tissue, adipose tissue, salivary gland tissue, lymphatic tissue, and inflammatory cells. Agreement between SRH and H&E was evaluated by calculating Cohen's kappa. Accuracy of SRH compared to H&E was quantified by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) as well as area under the receiver operating characteristic curve (AUC). RESULTS: Thirty-six of 80 samples were classified as OSCC by H&E-based diagnosis. Regarding the differentiation between neoplastic and non-neoplastic tissue, high agreement between H&E and SRH (kappa: 0.880) and high accuracy of SRH (sensitivity: 100%; specificity: 90.91%; PPV: 90.00%, NPV: 100%; AUC: 0.954) were demonstrated. For sub-classification of non-neoplastic tissues, SRH performance was dependent on the type of tissue, with high agreement and accuracy for normal mucosa, muscle tissue, and salivary glands. CONCLUSION: SRH provides high accuracy in discriminating neoplastic and non-neoplastic tissues. Regarding sub-classification of non-neoplastic tissues in OSCC patients, accuracy varies depending on the type of tissue examined. CLINICAL RELEVANCE: This study demonstrates the potential of SRH for intraoperative imaging of fresh, unprocessed tissue specimens from OSCC patients without the need for sectioning or staining.

Preoperative CA125 Significantly Improves Risk Stratification in High-Grade Endometrial Cancer.

Patients with high-grade endometrial carcinoma (EC) have an increased risk of tumor spread and lymph node metastasis (LNM). Preoperative imaging and CA125 can be used in work-up. As data on cancer antigen 125 (CA125) in high-grade EC are limited, we aimed to study primarily the predictive value of CA125, and secondarily the contributive value of computed tomography (CT) for advanced stage and LNM. Patients with high-grade EC (n = 333) and available preoperative CA125 were included retrospectively. The association of CA125 and CT findings with LNM was analyzed by logistic regression. Elevated CA125 ((>35 U/mL), (35.2% (68/193)) was significantly associated with stage III-IV disease (60.3% (41/68)) compared with normal CA125 (20.8% (26/125), [p < 0.001]), and with reduced disease-specific-(DSS) (p < 0.001) and overall survival (OS) (p < 0.001). The overall accuracy of predicting LNM by CT resulted in an area under the curve (AUC) of 0.623 (p < 0.001) independent of CA125. Stratification by CA125 resulted in an AUC of 0.484 (normal), and 0.660 (elevated). In multivariate analysis elevated CA125, non-endometrioid histology, pathological deep myometrial invasion ≥50%, and cervical involvement were significant predictors of LNM, whereas suspected LNM on CT was not. This shows that elevated CA125 is a relevant independent predictor of advanced stage and outcome specifically in high-grade EC.

Raman Spectroscopic Imaging of Human Bladder Resectates towards Intraoperative Cancer Assessment.

Raman spectroscopy offers label-free assessment of bladder tissue for in vivo and ex vivo intraoperative applications. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates. Raman microspectroscopic images were collected from whole tissue samples in a closed chamber at 785 nm laser excitation using a 20× objective lens and 250 µm step size. Without further preprocessing, Raman images were decomposed by the hyperspectral unmixing algorithm vertex component analysis into endmember spectra and their abundancies. Hierarchical cluster analysis distinguished endmember Raman spectra that were assigned to normal bladder, bladder cancer, necrosis, epithelium and lipid inclusions. Interestingly, Raman spectra of microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. In conclusion, our Raman workflow and data processing protocol with minimal user interference offers advantages for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices.

Dermatofibrosarcoma protuberans of the scalp: Surgical management in a multicentric series of 11 cases and systematic review of the literature.

BACKGROUND: Dermatofibrosarcoma protuberans is a rare, slow-growing soft-tissue malignancy originating in the dermis that is characterized by an infiltrating growth pattern with a marked tendency of local recurrence. Complete surgical resection with pathological margin clearance must be achieved to reduce the risk of tumor recurrence. Resulting defects often require extensive reconstructive procedures. Dermatofibrosarcoma protuberans of the scalp poses particular challenges owing to the proximity to the face and brain. This study aims to evaluate treatment options and proposes an algorithm for management of scalp dermatofibrosarcoma protuberans based on a multicentric case series and systematic review of the literature. METHODS: A retrospective multicentric chart analysis of 11 patients with scalp dermatofibrosarcoma protuberans who presented within the last 20 years was performed regarding demographic data, pathological tumor characteristics, and surgical management (resection and reconstruction). Additionally, a further 42 patients (44 cases) were identified through a systematic Preferred Reporting Systems for Systematic Reviews and Meta-Analysis-based review of the literature searching the Medline and Embase databases. RESULTS: In total, 30 cases were classified as primary and 20 cases as recurring scalp dermatofibrosarcoma protuberans (data from 5 cases were missing). The median tumor size was 24 cm2 (interquartile range 7.8-64), and the median defect size was 55.8 cm2 (interquartile range 48-112). Recurring scalp dermatofibrosarcoma protuberans was more often associated with invasion of deeper layers and required more extensive tumor resection to achieve negative margins. Within the subgroup that was managed with peripheral and deep en face margin assessment, no recurrence was observed. Most patients required local (41. 8%) or free flap (27.8%) reconstruction after dermatofibrosarcoma protuberans resection. CONCLUSION: Whenever possible, peripheral and deep en face margin assessment-based techniques should be preferred for resection of scalp dermatofibrosarcoma protuberans because they provide superior oncological safety while preserving uninvolved tissue. Patients with locally advanced and recurring scalp dermatofibrosarcoma protuberans often require multidisciplinary treatment including neurosurgery, radiotherapy, and microvascular reconstructive surgery and should be referred to a specialized center.

Proteome alterations in human autopsy tissues in relation to time after death.

Protein expression is a primary area of interest for routine histological diagnostics and tissue-based research projects, but the limitations of its post-mortem applicability remain largely unclear. On the other hand, tissue specimens obtained during autopsies can provide unique insight into advanced disease states, especially in cancer research. Therefore, we aimed to identify the maximum post-mortem interval (PMI) which is still suitable for characterizing protein expression patterns, to explore organ-specific differences in protein degradation, and to investigate whether certain proteins follow specific degradation kinetics. Therefore, the proteome of human tissue samples obtained during routine autopsies of deceased patients with accurate PMI (6, 12, 18, 24, 48, 72, 96 h) and without specific diseases that significantly affect tissue preservation, from lungs, kidneys and livers, was analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). For the kidney and liver, significant protein degradation became apparent at 48 h. For the lung, the proteome composition was rather static for up to 48 h and substantial protein degradation was detected only at 72 h suggesting that degradation kinetics appear to be organ specific. More detailed analyses suggested that proteins with similar post-mortem kinetics are not primarily shared in their biological functions. The overrepresentation of protein families with analogous structural motifs in the kidney indicates that structural features may be a common factor in determining similar postmortem stability. Our study demonstrates that a longer post-mortem period may have a significant impact on proteome composition, but sampling within 24 h may be appropriate, as degradation is within acceptable limits even in organs with faster autolysis.

Multiparametric magnetic resonance imaging for radiation therapy response monitoring in soft tissue sarcomas: a histology and MRI co-registration algorithm.

Rationale: To establish a spatially exact co-registration procedure between in vivo multiparametric magnetic resonance imaging (mpMRI) and (immuno)histopathology of soft tissue sarcomas (STS) to identify imaging parameters that reflect radiation therapy response of STS. Methods: The mpMRI-Protocol included diffusion-weighted (DWI), intravoxel-incoherent motion (IVIM), and dynamic contrast-enhancing (DCE) imaging. The resection specimen was embedded in 6.5% agarose after initial fixation in formalin. To ensure identical alignment of histopathological sectioning and in vivo imaging, an ex vivo MRI scan of the specimen was rigidly co-registered with the in vivo mpMRI. The deviating angulation of the specimen to the in vivo location of the tumor was determined. The agarose block was trimmed accordingly. A second ex vivo MRI in a dedicated localizer with a 4 mm grid was performed, which was matched to a custom-built sectioning machine. Microtomy sections were stained with hematoxylin and eosin. Immunohistochemical staining was performed with anti-ALDH1A1 antibodies as a radioresistance and anti-MIB1 antibodies as a proliferation marker. Fusion of the digitized microtomy sections with the in vivo mpMRI was accomplished through nonrigid co-registration to the in vivo mpMRI. Co-registration accuracy was qualitatively assessed by visual assessment and quantitatively evaluated by computing target registration errors (TRE). Results: The study sample comprised nine tumor sections from three STS patients. Visual assessment after nonrigid co-registration showed a strong morphological correlation of the histopathological specimens with ex vivo MRI and in vivo mpMRI after neoadjuvant radiation therapy. Quantitative assessment of the co-registration procedure using TRE analysis of different pairs of pathology and MRI sections revealed highly accurate structural alignment, with a total median TRE of 2.25 mm (histology - ex vivo MRI), 2.22 mm (histology - in vivo mpMRI), and 2.02 mm (ex vivo MRI - in vivo mpMRI). There was no significant difference between TREs of the different pairs of sections or caudal, middle, and cranial tumor parts, respectively. Conclusion: Our initial results show a promising approach to obtaining accurate co-registration between histopathology and in vivo MRI for STS. In a larger cohort of patients, the method established here will enable the prospective identification and validation of in vivo imaging biomarkers for radiation therapy response prediction and monitoring in STS patients via precise molecular and cellular correlation.

Targeted and explorative profiling of kallikrein proteases and global proteome biology of pancreatic ductal adenocarcinoma, chronic pancreatitis, and normal pancreas highlights disease-specific proteome remodelling.

Pancreatic ductal adenocarcinoma (PDAC) represents one of the most aggressive and lethal malignancies worldwide with an urgent need for new diagnostic and therapeutic strategies. One major risk factor for PDAC is the pre-indication of chronic pancreatitis (CP), which represents highly inflammatory pancreatic tissue. Kallikreins (KLKs) are secreted serine proteases that play an important role in various cancers as components of the tumor microenvironment. Previous studies of KLKs in solid tumors largely relied on either transcriptomics or immunodetection. We present one of the first targeted mass spectrometry profiling of kallikrein proteases in PDAC, CP, and normal pancreas. We show that KLK6 and KLK10 are significantly upregulated in PDAC (n=14) but not in CP (n=7) when compared to normal pancreas (n=16), highlighting their specific intertwining with malignancy. Additional explorative proteome profiling identified 5936 proteins in our pancreatic cohort and observed disease-specific proteome rearrangements in PDAC and CP. As such, PDAC features an enriched proteome motif for extracellular matrix (ECM) and cell adhesion while there is depletion of mitochondrial energy metabolism proteins, reminiscent of the Warburg effect. Although often regarded as a PDAC hallmark, the ECM fingerprint was also observed in CP, alongside with a prototypical inflammatory proteome motif as well as with an increased wound healing process and proteolytic activity, thereby possibly illustrating tissue autolysis. Proteogenomic analysis based on publicly accessible data sources identified 112 PDAC-specific and 32 CP-specific single amino acid variants, which among others affect KRAS and ANKHD1. Our study emphasizes the diagnostic potential of kallikreins and provides novel insights into proteomic characteristics of PDAC and CP.

Genomic Classifiers in Personalized Prostate Cancer Radiation Therapy Approaches: A Systematic Review and Future Perspectives Based on International Consensus.

Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk stratification after surgery, but less data exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) a survey of experts using the Delphi method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research. We performed a systematic review and screened ongoing clinical trials on ClinicalTrials.gov. Based on these results, a multidisciplinary international team of experts received an adapted Delphi method survey. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa.

Overexpression of integrin alpha 2 (ITGA2) correlates with poor survival in patients with pancreatic ductal adenocarcinoma.

AIMS: Due to the known malignant potential and the poor overall prognosis of pancreatic ductal adenocarcinoma (PDAC), the identification of new biomarkers is of utmost importance. It has been reported that integrin alpha 2 (ITGA2), plakophilin 3 (PKP3) and adenylate kinase 4 (AK4) are associated with poor survival and more aggressive malignant behaviour in multiple cancers; however, their role in PDAC is still unknown. Therefore, the aim of this study was to investigate the correlation of ITGA2, PKP3 and AK4 expression with PDAC tumour characteristics and patient survival. METHODS: Of 105 patients undergoing oncological pancreatic resection between 2012 and 2018, tissue microarrays were prepared from formalin-fixed, paraffin-embedded PDAC tissues and immunohistochemically stained with PKP3, AK4 and ITGA2. Clinical and pathological patient data were retrieved from the electronic patient charts and correlated with biomarker staining scores. RESULTS: ITGA2 expression was high in 43% of patients with PDAC, whereas AK4 and PKP3 expressions were high in 28% and 57%, respectively. Overall survival was negatively associated with high ITGA2 expression in comparison with low expression (13 months (95% CI 10 to 18 months) vs 25 months (95% CI 20 to 30 months), p<0.001). Expression of AK4 and PKP3 did not correlate with overall survival. Multivariate Cox regression identified ITGA2 as an independent predictor of shorter overall survival in PDAC of different lymph node status and high tumour grade (G3/G4). CONCLUSIONS: ITGA2 is an independent prognostic parameter for survival in patients with resected PDAC. PKP3 and AK4 do not appear to have prognostic value for survival in PDAC.

Protocol of the HISTOTHERM study: assessing the response to hyperthermia and hypofractionated radiotherapy in recurrent breast cancer.

Introduction: Breast cancer is globally the leading cancer in women, and despite the high 5-year survival rate the most frequent cause of cancer related deaths. Surgery, systemic therapy and radiotherapy are the three pillars of curative breast cancer treatment. However, locoregional recurrences frequently occur after initial treatment and are often challenging to treat, amongst others due to high doses of previous radiotherapy treatments. Radiotherapy can be combined with local hyperthermia to sensitize tumor cells to radiation and thereby significantly reduce the required radiation dose. Therefore, the combination treatment of mild local hyperthermia, i.e. locally heating of the tissue to 39-43°C, and re-irradiation with a reduced total dose is a relevant treatment option for previously irradiated patients. The mechanisms of this effect in the course of the therapy are to date not well understood and will be investigated in the HISTOTHERM study. Methods and analyses: Patients with local or (loco)regional recurrent breast cancer with macroscopic tumors are included in the study. Local tumor control is evaluated clinically and histologically during the course of a combination treatment of 60 minutes mild superficial hyperthermia (39 - 43°C) using water-filtered infrared A (wIRA) irradiation, immediately followed by hypofractionated re-irradiation with a total dose of 20-24 Gy, administered in weekly doses of 4 Gy. Tumor and tumor stroma biopsies as well as blood samples will be collected prior to treatment, during therapy (at a dose of 12 Gy) and in the follow-up to monitor therapy response. The treatment represents the standard operating procedure for hyperthermia plus re-irradiation. Various tissue and blood-based markers are analyzed. We aim at pinpointing key mechanisms and markers for therapy response which may help guiding treatment decisions in future. In addition, quality of life in the course of treatment will be assessed and survival data will be evaluated. Registration: The study is registered at the German Clinical Trials Register, Deutsches Register Klinischer Studien (DRKS00029221).