Enhancement of colorectal cancer therapy through interruption of the HSF1-HSP90 axis by p53 activation or cell cycle inhibition.

The stress-associated molecular chaperone system is an actionable target in cancer therapies. It is ubiquitously upregulated in cancer tissues and enables tumorigenicity by stabilizing hundreds of oncoproteins and disturbing the stoichiometry of protein complexes. Most inhibitors target the key component heat-shock protein 90 (HSP90). However, although classical HSP90 inhibitors are highly tumor-selective, they fail in phase 3 clinical oncology trials. These failures are at least partly due to an interference with a negative feedback loop by HSP90 inhibition, known as heat-shock response (HSR): in response to HSP90 inhibition there is compensatory synthesis of stress-inducible chaperones, mediated by the transcription factor heat-shock factor 1 (HSF1). We recently identified that wildtype p53 (p53) actively reduces the HSR by repressing HSF1 via a p21-CDK4/6-MAPK-HSF1 axis. Here we test the hypothesis that in HSP90-based therapies simultaneous p53 activation or direct cell cycle inhibition interrupts the deleterious HSF1-HSR axis and improves the efficiency of HSP90 inhibitors. Indeed, we find that the clinically relevant p53 activator Idasanutlin suppresses the HSF1-HSR activity in HSP90 inhibitor-based therapies. This combination synergistically reduces cell viability and accelerates cell death in p53-proficient colorectal cancer (CRC) cells, murine tumor-derived organoids and patient-derived organoids (PDOs). Mechanistically, upon combination therapy human CRC cells strongly upregulate p53-associated pathways, apoptosis, and inflammatory immune pathways. Likewise, in the chemical AOM/DSS CRC model in mice, dual HSF1-HSP90 inhibition strongly represses tumor growth and remodels immune cell composition, yet displays only minor toxicities in mice and normal mucosa-derived organoids. Importantly, inhibition of the cyclin dependent kinases 4 and 6 (CDK4/6) under HSP90 inhibition phenocopies synergistic repression of the HSR in p53-proficient CRC cells. Even more important, in p53-deficient (mutp53-harboring) CRC cells, an HSP90 inhibition in combination with CDK4/6 inhibitors similarly suppresses the HSF1-HSR system and reduces cancer growth. Likewise, p53-mutated PDOs strongly respond to dual HSF1-HSP90 pathway inhibition and thus, providing a strategy to target CRC independent of the p53 status. In sum, activating p53 (in p53-proficient cancer cells) or inhibiting CDK4/6 (independent of the p53 status) provide new options to improve the clinical outcome of HSP90-based therapies and to enhance colorectal cancer therapy.

Integrating AI-Powered Digital Pathology and Imaging Mass Cytometry Identifies Key Classifiers of Tumor Cells, Stroma, and Immune Cells in Non-Small Cell Lung Cancer.

Artificial intelligence (AI)-powered approaches are becoming increasingly used as histopathologic tools to extract subvisual features and improve diagnostic workflows. On the other hand, hi-plex approaches are widely adopted to analyze the immune ecosystem in tumor specimens. Here, we aimed at combining AI-aided histopathology and imaging mass cytometry (IMC) to analyze the ecosystem of non-small cell lung cancer (NSCLC). An AI-based approach was used on hematoxylin and eosin (H&E) sections from 158 NSCLC specimens to accurately identify tumor cells, both adenocarcinoma and squamous carcinoma cells, and to generate a classifier of tumor cell spatial clustering. Consecutive tissue sections were stained with metal-labeled antibodies and processed through the IMC workflow, allowing quantitative detection of 24 markers related to tumor cells, tissue architecture, CD45+ myeloid and lymphoid cells, and immune activation. IMC identified 11 macrophage clusters that mainly localized in the stroma, except for S100A8+ cells, which infiltrated tumor nests. T cells were preferentially localized in peritumor areas or in tumor nests, the latter being associated with better prognosis, and they were more abundant in highly clustered tumors. Integrated tumor and immune classifiers were validated as prognostic on whole slides. In conclusion, integration of AI-powered H&E and multiparametric IMC allows investigation of spatial patterns and reveals tissue relevant features with clinical relevance. SIGNIFICANCE: Leveraging artificial intelligence-powered H&E analysis integrated with hi-plex imaging mass cytometry provides insights into the tumor ecosystem and can translate tumor features into classifiers to predict prognosis, genotype, and therapy response.

Task design for crowdsourced glioma cell annotation in microscopy images.

Crowdsourcing has been used in computational pathology to generate cell and cell nuclei annotations for machine learning. Herein, we broaden its scope to the previously unsolved challenging task of glioma cell detection. This requires multiplexed immunofluorescence microscopy due to diffuse invasiveness and exceptional similarity between glioma cells and reactive astrocytes. In four pilot experiments, we iteratively developed a task design enabling high-quality annotations by crowdworkers on Amazon Mechanical Turk. We applied majority or weighted vote and validated them against ground truth in the final setting. On the base of a YOLO convolutional neural network architecture, we used these consensus labels for training with different image representations regarding colors, intensities, and immmunohistochemical marker combinations. A crowd of 712 workers defined aggregated point annotations in 235 images with an average [Formula: see text] score of 0.627 for majority vote. The networks resulted in acceptable [Formula: see text] scores up to 0.69 for YOLOv8 on average and indicated first evidence for transferability to images lacking tumor markers, especially in IDH-wildtype glioblastoma. Our work confirms feasibility of crowdsourcing to generate labels suitable for training of machine learning tools in the challenging and clinically relevant use case of glioma microenvironment.

Rare germline variants in POLE and POLD1 encoding the catalytic subunits of DNA polymerases ε and δ in glioma families.

Pathogenic germline variants in the DNA polymerase genes POLE and POLD1 cause polymerase proofreading-associated polyposis, a dominantly inherited disorder with increased risk of colorectal carcinomas and other tumors. POLE/POLD1 variants may result in high somatic mutation and neoantigen loads that confer susceptibility to immune checkpoint inhibitors (ICIs). To explore the role of POLE/POLD1 germline variants in glioma predisposition, whole-exome sequencing was applied to leukocyte DNA of glioma patients from 61 tumor families with at least one glioma case each. Rare heterozygous POLE/POLD1 missense variants predicted to be deleterious were identified in glioma patients from 10 (16%) families, co-segregating with the tumor phenotype in families with available DNA from several tumor patients. Glioblastoma patients carrying rare POLE variants had a mean overall survival of 21 months. Additionally, germline variants in POLD1, located at 19q13.33, were detected in 2/34 (6%) patients with 1p/19q-codeleted oligodendrogliomas, while POLE variants were identified in 2/4 (50%) glioblastoma patients with a spinal metastasis. In 13/15 (87%) gliomas from patients carrying POLE/POLD1 variants, features of defective polymerase proofreading, e.g. hypermutation, POLE/POLD1-associated mutational signatures, multinucleated cells, and increased intratumoral T cell response, were observed. In a CRISPR/Cas9-derived POLE-deficient LN-229 glioblastoma cell clone, a mutator phenotype and delayed S phase progression were detected compared to wildtype POLE cells. Our data provide evidence that rare POLE/POLD1 germline variants predispose to gliomas that may be susceptible to ICIs. Data compiled here suggest that glioma patients carrying POLE/POLD1 variants may be recognized by cutaneous manifestations, e.g. café-au-lait macules, and benefit from surveillance colonoscopy.

Anti-GABA-A Receptor Antibody-Mediated Epilepsia Partialis Continua After Treatment With Alemtuzumab: A Case Report.

BACKGROUND AND OBJECTIVES: Patients with anti-GABA-A receptor encephalitis characteristically experience therapy-refractory epileptic seizures. General anesthesia is often required to terminate refractory status epilepticus. The immunologic mechanisms leading to antibody formation remain to be elucidated. Described triggers of anti-GABA-A autoimmunity are tumors, mainly thymomas, and herpes simplex encephalitis. METHODS: We present a young woman with prediagnosis of relapse remitting multiple sclerosis (MS), treated with interferons, natalizumab, and alemtuzumab. Six months after one and only cycle of alemtuzumab, speech arrest and behavioral changes with aggressive and anxious traits appeared. She showed increasing motor convulsions resulting in focal status epilepticus. RESULTS: Anti-GABA-A receptor antibodies in CSF and serum were confirmed in different external laboratories, in a more extensive analysis after antibodies against NMDAR, CASPR2, LGI1, GABABR, and AMPAR were ruled out during in-house examination. Clinical condition improved temporarily with cortisone therapy, plasmapheresis, and IVIG but deteriorated rapidly after steroid discontinuation, resulting in brain biopsy. On histopathologic confirmation consistent with anti-GABA-A receptor antibody-associated CNS inflammation, completing the first rituximab cycle, continuing oral corticosteroids and supplementing immunosuppression with cyclosporine A led to quick recovery. DISCUSSION: Our case describes a severe autoantibody-induced encephalitis in a young patient with MS, with alemtuzumab as a potential trigger for anti-GABA-A receptor encephalitis.

Proinflammatory Macrophage Activation by the Polysialic Acid-Siglec-16 Axis Is Linked to Increased Survival of Patients with Glioblastoma.

PURPOSE: Interactions with tumor-associated microglia and macrophages (TAM) are critical for glioblastoma progression. Polysialic acid (polySia) is a tumor-associated glycan, but its frequency of occurrence and its prognostic value in glioblastoma are disputed. Through interactions with the opposing immune receptors Siglec-11 and Siglec-16, polySia is implicated in the regulation of microglia and macrophage activity. However, due to a nonfunctional SIGLEC16P allele, SIGLEC16 penetrance is less than 40%. Here, we explored possible consequences of SIGLEC16 status and tumor cell-associated polySia on glioblastoma outcome. EXPERIMENTAL DESIGN: Formalin-fixed paraffin-embedded specimens of two independent cohorts with 70 and 100 patients with newly diagnosed glioblastoma were retrospectively analyzed for SIGLEC16 and polySia status in relation to overall survival. Inflammatory TAM activation was assessed in tumors, in heterotypic tumor spheroids consisting of polySia-positive glioblastoma cells and Siglec-16-positive or Siglec-16-negative macrophages, and by exposing Siglec-16-positive or Siglec-16-negative macrophages to glioblastoma cell-derived membrane fractions. RESULTS: Overall survival of SIGLEC16 carriers with polySia-positive tumors was increased. Consistent with proinflammatory Siglec-16 signaling, levels of TAM positive for the M2 marker CD163 were reduced, whereas the M1 marker CD74 and TNF expression were increased, and CD8+ T cells enhanced in SIGLEC16/polySia double-positive tumors. Correspondingly, TNF production was elevated in heterotypic spheroid cultures with Siglec-16-expressing macrophages. Furthermore, a higher, mainly M1-like cytokine release and activating immune signaling was observed in SIGLEC16-positive as compared with SIGLEC16-negative macrophages confronted with glioblastoma cell-derived membranes. CONCLUSIONS: Collectively, these results strongly suggest that proinflammatory TAM activation causes the better outcome in patients with glioblastoma with a functional polySia-Siglec-16 axis.

Moderately Hypofractionated Radio(chemo)therapy With Simultaneous Integrated Boost for Recurrent, Previously Irradiated, High-grade Glioma.

BACKGROUND/AIM: The therapy of recurrent, previously irradiated, high-grade gliomas is still a major interdisciplinary challenge, and the overall prognosis remains poor. Reirradiation has been established as a major component of the management of relapse, in addition to further debulking surgery and systemic options. Herein, we present a moderately hypofractionated reirradiation concept with simultaneous integrated boost for such recurrent, previously irradiated tumors. PATIENTS AND METHODS: From October 2019 to January 2021, 12 patients with recurrent malignant gliomas were re-irradiated. All patients had previously undergone surgery and irradiation with mostly normal fractions at the time of primary therapy. Radiotherapy of relapse was performed in all patients with 33 Gy, with 2.2 Gy single dose with a simultaneously integrated boost of 40.05 Gy with a single dose of 2.67 Gy in 15 fractions. Nine out of the 12 patients underwent debulking surgery before reirradiation, and seven patients received concurrent chemotherapy with temozolomide. The mean follow-up was 15.5 months. RESULTS: The median overall survival after recurrence was 9.3 months. The survival rate after 1 year was 33%. Toxicity during radiotherapy was low. In two patients, small areas of radionecrosis were observed at follow-up magnetic resonance imaging in the target volume; these patients were clinically asymptomatic. CONCLUSION: Moderate hypofractionation shortens the duration of radiotherapy and thereby improves accessibility for patients with limited mobility and prognosis, and achieves a respectable overall survival rate. Furthermore, the extent of late toxicity is also acceptable in these preirradiated patients.

Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy.

Background: Deep learning tasks, which require large numbers of images, are widely applied in digital pathology. This poses challenges especially for supervised tasks since manual image annotation is an expensive and laborious process. This situation deteriorates even more in the case of a large variability of images. Coping with this problem requires methods such as image augmentation and synthetic image generation. In this regard, unsupervised stain translation via GANs has gained much attention recently, but a separate network must be trained for each pair of source and target domains. This work enables unsupervised many-to-many translation of histopathological stains with a single network while seeking to maintain the shape and structure of the tissues. Methods: StarGAN-v2 is adapted for unsupervised many-to-many stain translation of histopathology images of breast tissues. An edge detector is incorporated to motivate the network to maintain the shape and structure of the tissues and to have an edge-preserving translation. Additionally, a subjective test is conducted on medical and technical experts in the field of digital pathology to evaluate the quality of generated images and to verify that they are indistinguishable from real images. As a proof of concept, breast cancer classifiers are trained with and without the generated images to quantify the effect of image augmentation using the synthetized images on classification accuracy. Results: The results show that adding an edge detector helps to improve the quality of translated images and to preserve the general structure of tissues. Quality control and subjective tests on our medical and technical experts show that the real and artificial images cannot be distinguished, thereby confirming that the synthetic images are technically plausible. Moreover, this research shows that, by augmenting the training dataset with the outputs of the proposed stain translation method, the accuracy of breast cancer classifier with ResNet-50 and VGG-16 improves by 8.0% and 9.3%, respectively. Conclusions: This research indicates that a translation from an arbitrary source stain to other stains can be performed effectively within the proposed framework. The generated images are realistic and could be employed to train deep neural networks to improve their performance and cope with the problem of insufficient numbers of annotated images.

Impact of RNA Signatures on pCR and Survival after 12-Week Neoadjuvant Pertuzumab plus Trastuzumab with or without Paclitaxel in the WSG-ADAPT HER2+/HR- Trial.

PURPOSE: To identify associations of biological signatures and stromal tumor-infiltrating lymphocytes (sTIL) with pathological complete response (pCR; ypT0 ypN0) and survival in the Phase II WSG-ADAPT HER2+/HR- trial (NCT01817452). EXPERIMENTAL DESIGN: Patients with cT1-cT4c, cN0-3 HER2+/HR- early breast cancer (EBC) were randomized to pertuzumab+trastuzumab (P+T, n = 92) or P+T+paclitaxel (n = 42). Gene expression signatures were analyzed in baseline biopsies using NanoString Breast Cancer 360 panel (n = 117); baseline and on-treatment (week 3) sTIL levels were available in 119 and 76 patients, respectively. Impacts of standardized gene expression signatures on pCR and invasive disease-free survival (iDFS) were estimated by logistic and Cox regression. RESULTS: In all patients, ERBB2 [OR, 1.70; 95% confidence interval (CI), 1.08-2.67] and estrogen receptor (ER) signaling (OR, 1.72; 95% CI, 1.13-2.61) were favorable, whereas PTEN (OR, 0.57; 95% CI, 0.38-0.87) was unfavorable for pCR. After 60 months median follow-up, 13 invasive events occurred (P+T: n = 11, P+T+paclitaxel: n = 2), none following pCR. Gene signatures related to immune response (IR) and ER signaling were favorable for iDFS, all with similar HR about 0.43-0.55. These patterns were even more prominent in the neoadjuvant chemotherapy-free group, where additionally BRCAness signature was unfavorable (HR, 2.00; 95% CI, 1.04-3.84). IR signatures were strongly intercorrelated. sTILs (baseline/week 3/change) were not associated with pCR or iDFS, though baseline sTILs correlated positively with IR signatures. CONCLUSIONS: Distinct gene signatures were associated with pCR versus iDFS in HER2+/HR- EBC. The potential role of IR in preventing recurrence suggests that patients with upregulated IR signatures could be candidates for de-escalation concepts in HER2+ EBC.

CycleGAN for virtual stain transfer: Is seeing really believing?

Digital Pathology is an area prone to high variation due to multiple factors which can strongly affect diagnostic quality and visual appearance of the Whole-Slide-Images (WSIs). The state-of-the art methods to deal with such variation tend to address this through style-transfer inspired approaches. Usually, these solutions directly apply successful approaches from the literature, potentially with some task-related modifications. The majority of the obtained results are visually convincing, however, this paper shows that this is not a guarantee that such images can be directly used for either medical diagnosis or reducing domain shift.This article shows that slight modification in a stain transfer architecture, such as a choice of normalisation layer, while resulting in a variety of visually appealing results, surprisingly greatly effects the ability of a stain transfer model to reduce domain shift. By extensive qualitative and quantitative evaluations, we confirm that translations resulting from different stain transfer architectures are distinct from each other and from the real samples. Therefore conclusions made by visual inspection or pretrained model evaluation might be misleading.

Understanding fibrosis pathogenesis via modeling macrophage-fibroblast interplay in immune-metabolic context.

Fibrosis is a progressive biological condition, leading to organ dysfunction in various clinical settings. Although fibroblasts and macrophages are known as key cellular players for fibrosis development, a comprehensive functional model that considers their interaction in the metabolic/immunologic context of fibrotic tissue has not been set up. Here we show, by transcriptome-based mathematical modeling in an in vitro system that represents macrophage-fibroblast interplay and reflects the functional effects of inflammation, hypoxia and the adaptive immune context, that irreversible fibrosis development is associated with specific combinations of metabolic and inflammatory cues. The in vitro signatures are in good alignment with transcriptomic profiles generated on laser captured glomeruli and cortical tubule-interstitial area, isolated from human transplanted kidneys with advanced stages of glomerulosclerosis and interstitial fibrosis/tubular atrophy, two clinically relevant conditions associated with organ failure in renal allografts. The model we describe here is validated on tissue based quantitative immune-phenotyping of biopsies from transplanted kidneys, demonstrating its feasibility. We conclude that the combination of in vitro and in silico modeling represents a powerful systems medicine approach to dissect fibrosis pathogenesis, applicable to specific pathological conditions, and develop coordinated targeted approaches.

Impact of stromal tumor-infiltrating lymphocytes (sTILs) on response to neoadjuvant chemotherapy in triple-negative early breast cancer in the WSG-ADAPT TN trial.

BACKGROUND: Higher density of stromal tumor-infiltrating lymphocytes (sTILs) at baseline has been associated with increased rates of pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). While evidence supports favorable association of pCR with survival in TNBC, an independent impact of sTILs (after adjustment for pCR) on survival is not yet established. Moreover, the impact of sTIL dynamics during NACT on pCR and survival in TNBC is unknown. METHODS: The randomized WSG-ADAPT TN phase II trial compared efficacy of 12-week nab-paclitaxel with gemcitabine versus carboplatin. This preplanned translational analysis assessed impacts of sTIL measurements at baseline (sTIL-0) and after 3 weeks of chemotherapy (sTIL-3) on pCR and invasive disease-free survival (iDFS). Predictive performance of sTIL-0 and sTIL-3 for pCR was quantified by ROC analysis and logistic regression; Kaplan-Meier estimation and Cox regression (with mediation analysis) were used to determine their impact on iDFS. RESULTS: For prediction of pCR, the AUC statistics for sTIL-0 and sTIL-3 were 0.60 and 0.63, respectively, in all patients; AUC for sTIL-3 was higher in NP/G. The positive predictive value (PPV) of "lymphocyte-predominant" status (sTIL-0 ≥ 60%) at baseline was 59.3%, though only 13.0% of patients had this status. To predict non-pCR, the cut point sTIL-0 ≤ 10% yielded PPV = 69.5% while addressing 33.8% of patients. Higher sTIL levels (particularly at 3 weeks) were independently and favorably associated with better iDFS, even after adjusting for pCR. For example, the adjusted hazard ratio for 3-week sTILs ≥ 60% (vs. < 60%) was 0.48 [0.23-0.99]. Low cellularity in 3-week biopsies was the strongest individual predictor for pCR (in both therapy arms), but not for iDFS. CONCLUSION: The independent impact of sTILs on iDFS suggests that favorable immune response can influence key tumor biological processes for long-term survival. The results suggest that the reliability of pCR following neoadjuvant therapy as a surrogate for survival could vary among subgroups in TNBC defined by immune response or other factors. Dynamic measurements of sTILs under NACT could support immune response-guided patient selection for individualized therapy approaches for both very low levels (more effective therapies) and very high levels (de-escalation concepts). TRIAL REGISTRATION: Clinical trials No: NCT01815242, retrospectively registered January 25, 2013.

Immune cell infiltration pattern in non-small cell lung cancer PDX models is a model immanent feature and correlates with a distinct molecular and phenotypic make-up.

BACKGROUND: The field of cancer immunology is rapidly moving towards innovative therapeutic strategies, resulting in the need for robust and predictive preclinical platforms reflecting the immunological response to cancer. Well characterized preclinical models are essential for the development of predictive biomarkers in the oncology as well as the immune-oncology space. In the current study, gold standard preclinical models are being refined and combined with novel image analysis tools to meet those requirements. METHODS: A panel of 14 non-small cell lung cancer patient-derived xenograft models (NSCLC PDX) was propagated in humanized NOD/Shi-scid/IL-2Rnull mice. The models were comprehensively characterized for relevant phenotypic and molecular features, including flow cytometry, immunohistochemistry, histology, whole exome sequencing and cytokine secretion. RESULTS: Models reflecting hot (>5% tumor-infiltrating lymphocytes/TILs) as opposed to cold tumors (<5% TILs) significantly differed regarding their cytokine profiles, molecular genetic aberrations, stroma content, and programmed cell death ligand-1 status. Treatment experiments including anti cytotoxic T-lymphocyte-associated protein 4, anti-programmed cell death 1 or the combination thereof across all 14 models in the single mouse trial format showed distinctive tumor growth response and spatial immune cell patterns as monitored by computerized analysis of digitized whole-slide images. Image analysis provided for the first time qualitative evaluation of the extent to which PDX models retain the histological features from their original human donors. CONCLUSIONS: Deep phenotyping of PDX models in a humanized setting by combinations of computational pathology, immunohistochemistry, flow cytometry and proteomics enables the exhaustive analysis of innovative preclinical models and paves the way towards the development of translational biomarkers for immuno-oncology drugs.

Longitudinal monitoring of STAT3 phosphorylation and histologic outcome of tofacitinib therapy in patients with ulcerative colitis.

BACKGROUND: Tofacitinib is the first in class, pan-JAK inhibitor approved for ulcerative colitis (UC). Clinical efficacy has been shown, but long-term real-life endoscopic and histologic data are lacking. AIM: To investigate the effects of tofacitinib in patients with refractory UC focussing on endoscopic, histologic and molecular outcomes, including STAT3 phosphorylation (pSTAT3) detection in the spatial context of mucosal inflammation METHODS: We prospectively monitored 59 highly refractory patients (96.7% anti-TNF exposure, 91.7% vedolizumab exposure) initiating tofacitinib at two IBD referral centres and assessed outcome at the end of induction and after 48 weeks of therapy. Endoscopic improvement was defined as a Mayo endoscopic subscore ≤1, endoscopic and histologic remission as Mayo endoscopic subscore 0 and Nancy histologic score 0. Multiplex immunohistochemistry with multispectral imaging was used to assess pSTAT3. RESULTS: Endoscopic improvement was achieved by 24.4% and 30.5% of patients at weeks 8 and 48, respectively. Endoscopic and histologic remission rates were 11.1%, 23.7 and 16.7%, 21.4%, respectively. Endoscopic improvement at week 8 was significantly associated with treatment continuation in the long-term (72.7% vs 20.6%, p = 0.003). Although we observed a gradual decrease of mucosal pSTAT3 levels in both remitters and non-remitters (p < 0.05), no association with treatment outcome could be demonstrated. However, lamina propria pSTAT3 was significantly associated with the Nancy Histologic index (p = 0.004). CONCLUSION: Tofacitinib can induce and maintain endoscopic and histologic remission in up to one-quarter of highly refractory UC patients. Longitudinal monitoring of nuclear pSTAT3 in mucosal tissue compartments reflects distinctive on-target effects, independently of long-term treatment outcomes.

ALK-positive histiocytosis: a new clinicopathologic spectrum highlighting neurologic involvement and responses to ALK inhibition.

ALK-positive histiocytosis is a rare subtype of histiocytic neoplasm first described in 2008 in 3 infants with multisystemic disease involving the liver and hematopoietic system. This entity has subsequently been documented in case reports and series to occupy a wider clinicopathologic spectrum with recurrent KIF5B-ALK fusions. The full clinicopathologic and molecular spectra of ALK-positive histiocytosis remain, however, poorly characterized. Here, we describe the largest study of ALK-positive histiocytosis to date, with detailed clinicopathologic data of 39 cases, including 37 cases with confirmed ALK rearrangements. The clinical spectrum comprised distinct clinical phenotypic groups: infants with multisystemic disease with liver and hematopoietic involvement, as originally described (Group 1A: 6/39), other patients with multisystemic disease (Group 1B: 10/39), and patients with single-system disease (Group 2: 23/39). Nineteen patients of the entire cohort (49%) had neurologic involvement (7 and 12 from Groups 1B and 2, respectively). Histology included classic xanthogranuloma features in almost one-third of cases, whereas the majority displayed a more densely cellular, monomorphic appearance without lipidized histiocytes but sometimes more spindled or epithelioid morphology. Neoplastic histiocytes were positive for macrophage markers and often conferred strong expression of phosphorylated extracellular signal-regulated kinase, confirming MAPK pathway activation. KIF5B-ALK fusions were detected in 27 patients, whereas CLTC-ALK, TPM3-ALK, TFG-ALK, EML4-ALK, and DCTN1-ALK fusions were identified in single cases. Robust and durable responses were observed in 11/11 patients treated with ALK inhibition, 10 with neurologic involvement. This study presents the existing clinicopathologic and molecular landscape of ALK-positive histiocytosis and provides guidance for the clinical management of this emerging histiocytic entity.

An automatic framework for fusing information from differently stained consecutive digital whole slide images: A case study in renal histology.

OBJECTIVE: This article presents an automatic image processing framework to extract quantitative high-level information describing the micro-environment of glomeruli in consecutive whole slide images (WSIs) processed with different staining modalities of patients with chronic kidney rejection after kidney transplantation. METHODS: This four-step framework consists of: 1) approximate rigid registration, 2) cell and anatomical structure segmentation 3) fusion of information from different stainings using a newly developed registration algorithm 4) feature extraction. RESULTS: Each step of the framework is validated independently both quantitatively and qualitatively by pathologists. An illustration of the different types of features that can be extracted is presented. CONCLUSION: The proposed generic framework allows for the analysis of the micro-environment surrounding large structures that can be segmented (either manually or automatically). It is independent of the segmentation approach and is therefore applicable to a variety of biomedical research questions. SIGNIFICANCE: Chronic tissue remodelling processes after kidney transplantation can result in interstitial fibrosis and tubular atrophy (IFTA) and glomerulosclerosis. This pipeline provides tools to quantitatively analyse, in the same spatial context, information from different consecutive WSIs and help researchers understand the complex underlying mechanisms leading to IFTA and glomerulosclerosis.

Immune cell composition and functional marker dynamics from multiplexed immunohistochemistry to predict response to neoadjuvant chemotherapy in the WSG-ADAPT-TN trial.

BACKGROUND: The association of early changes in the immune infiltrate during neoadjuvant chemotherapy (NACT) with pathological complete response (pCR) in triple-negative breast cancer (TNBC) remains unexplored. METHODS: Multiplexed immunohistochemistry was performed in matched tumor biopsies obtained at baseline and after 3 weeks of NACT from 66 patients from the West German Study Group Adjuvant Dynamic Marker-Adjusted Personalized Therapy Trial Optimizing Risk Assessment and Therapy Response Prediction in Early Breast Cancer - Triple Negative Breast Cancer (WSG-ADAPT-TN) trial. Association between CD4, CD8, CD73, T cells, PD1-positive CD4 and CD8 cells, and PDL1 levels in stroma and/or tumor at baseline, week 3 and 3-week change with pCR was evaluated with univariable logistic regression. RESULTS: Compared with no change in immune cell composition and functional markers, transition from 'cold' to 'hot' (below-median and above-median marker level at baseline, respectively) suggested higher pCR rates for PD1-positive CD4 (tumor: OR=1.55, 95% CI 0.45 to 5.42; stroma: OR=2.65, 95% CI 0.65 to 10.71) and PD1-positive CD8 infiltrates (tumor: OR=1.77, 95% CI 0.60 to 5.20; stroma: OR=1.25, 95% CI 0.41 to 3.84; tumor+stroma: OR=1.62, 95% CI 0.51 to 5.12). No pCR was observed after 'hot-to-cold' transition in PD1-positive CD8 cells. pCR rates appeared lower after hot-to-cold transitions in T cells (tumor: OR=0.26, 95% CI 0.03 to 2.34; stroma: OR=0.35, 95% CI 0.04 to 3.25; tumor+stroma: OR=0.00, 95% CI 0.00 to 1.04) and PD1-positive CD4 cells (tumor: OR=0.60, 95% CI 0.11 to 3.35; stroma: OR=0.22, 95% CI 0.03 to 1.92; tumor+stroma: OR=0.32, 95% CI 0.04 to 2.94). Higher pCR rates collated with 'altered' distribution (levels below-median and above-median in tumor and stroma, respectively) of T cell (OR=3.50, 95% CI 0.84 to 14.56) and PD1-positive CD4 cells (OR=4.50, 95% CI 1.01 to 20.14). CONCLUSION: Our exploratory findings indicate that comprehensive analysis of early immune infiltrate dynamics complements currently investigated predictive markers for pCR and may have a potential to improve guidance for individualized de-escalation/escalation strategies in TNBC.

Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning.

Delayed graft function (DGF) is a strong risk factor for development of interstitial fibrosis and tubular atrophy (IFTA) in kidney transplants. Quantitative assessment of inflammatory infiltrates in kidney biopsies of DGF patients can reveal predictive markers for IFTA development. In this study, we combined multiplex tyramide signal amplification (mTSA) and convolutional neural networks (CNNs) to assess the inflammatory microenvironment in kidney biopsies of DGF patients (n = 22) taken at 6 weeks post-transplantation. Patients were stratified for IFTA development (<10% versus ≥10%) from 6 weeks to 6 months post-transplantation, based on histopathological assessment by three kidney pathologists. One mTSA panel was developed for visualization of capillaries, T- and B-lymphocytes and macrophages and a second mTSA panel for T-helper cell and macrophage subsets. The slides were multi spectrally imaged and custom-made python scripts enabled conversion to artificial brightfield whole-slide images (WSI). We used an existing CNN for the detection of lymphocytes with cytoplasmatic staining patterns in immunohistochemistry and developed two new CNNs for the detection of macrophages and nuclear-stained lymphocytes. F1-scores were 0.77 (nuclear-stained lymphocytes), 0.81 (cytoplasmatic-stained lymphocytes), and 0.82 (macrophages) on a test set of artificial brightfield WSI. The CNNs were used to detect inflammatory cells, after which we assessed the peritubular capillary extent, cell density, cell ratios, and cell distance in the two patient groups. In this cohort, distance of macrophages to other immune cells and peritubular capillary extent did not vary significantly at 6 weeks post-transplantation between patient groups. CD163+ cell density was higher in patients with ≥10% IFTA development 6 months post-transplantation (p < 0.05). CD3+CD8-/CD3+CD8+ ratios were higher in patients with <10% IFTA development (p < 0.05). We observed a high correlation between CD163+ and CD4+GATA3+ cell density (R = 0.74, p < 0.001). Our study demonstrates that CNNs can be used to leverage reliable, quantitative results from mTSA-stained, multi spectrally imaged slides of kidney transplant biopsies.

Pitfalls in Genetic Diagnostics: Why Phenotyping is Essential.

New genetic testing technologies have revolutionized medicine within the past years. It is foreseeable that the development will continue with the introduction of new techniques. Nevertheless, despite improved technology, an exact clinical description of the phenotype is still necessary and it is important to critically question findings, both before initiating genetic testing and when interpreting the results. We present four brief case vignettes to point out difficulties associated with correctly interpreting genetic findings.

Histopathological and Immune Prognostic Factors in Colo-Rectal Liver Metastases.

Prognostic studies are increasingly providing new tools to stratify colo-rectal liver metastasis patients into clinical subgroups, with remarkable implications in terms of clinical management and therapeutic choice. Here, the strengths and hurdles of current prognostic tools in colo-rectal liver metastasis are discussed. Alongside more classic histopathological parameters, which capture features related to the tumor component, such as tumor invasion, tumor growth pattern and regression score, we will discuss immune mediators, which are starting to be considered important features. Their objective quantification has shown significant results in prognostication studies, with most of the work focused on adaptive immune cells, namely T cells. As for macrophages, they are only starting to be appreciated and we will present recent advances in evaluation of macrophage morphological features. Deeper knowledge acquired by multiparametric analyses is rapidly uncovering the variety of immune players that should be assessed. The future projection is to implement deep-learning histopathological tools and to integrate histopathological and immune metrics in multiparametric scores, with the ultimate objective to achieve a deeper resolution of the tumor features and their relevance for colo-rectal liver metastasis.