End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology

Current approaches for classification of whole slide images (WSI) in digital pathology predominantly utilize a two-stage learning pipeline. The first stage identifies areas of interest (e.g. tumor tissue), while the second stage processes cropped tiles from these areas in a supervised fashion. During inference, a large number of tiles are combined into a unified prediction for the entire slide. A major drawback of such approaches is the requirement for task-specific auxiliary labels which are not acquired in clinical routine. We propose a novel learning pipeline for WSI classification that is trainable end-to-end and does not require any auxiliary annotations. We apply our approach to predict molecular alterations for a number of different use-cases, including detection of microsatellite instability in colorectal tumors and prediction of specific mutations for colon, lung, and breast cancer cases from The Cancer Genome Atlas. Results reach AUC scores of up to 94% and are shown to be competitive with state of the art two-stage pipelines. We believe our approach can facilitate future research in digital pathology and contribute to solve a large range of problems around the prediction of cancer phenotypes, hopefully enabling personalized therapies for more patients in future.Comment: MICCAI 2022; 8.5 Pages, 4 Figure

Glucocorticoids delivered by inorganic‐organic hybrid nanoparticles mitigate acute graft‐versus‐host disease and sustain graft‐versus‐leukemia activity

Glucocorticoids (GCs) are widely used to treat acute graft‐versus‐host disease (aGvHD) due to their immunosuppressive activity, but they also reduce the beneficial graft‐versus‐leukemia (GvL) effect of the allogeneic T cells contained in the graft. Here, we tested whether aGvHD therapy could be improved by delivering GCs with the help of inorganic–organic hybrid nanoparticles (IOH‐NPs) that preferentially target myeloid cells. IOH‐NPs containing the GC betamethasone (BMP‐NPs) efficiently reduced morbidity, mortality, and tissue damage in a totally MHC mismatched mouse model of aGvHD. Therapeutic activity was lost in mice lacking the GC receptor (GR) in myeloid cells, confirming the cell type specificity of our approach. BMP‐NPs had no relevant systemic activity but suppressed cytokine and chemokine gene expression locally in the small intestine, which presumably explains their mode of action. Most importantly, BMP‐NPs delayed the development of an adoptively transferred B cell lymphoma better than the free drug, although the overall incidence was unaffected. Our findings thus suggest that employing IOH‐NPs could diminish the risk of relapse associated with GC therapy of aGvHD patients while still allowing to efficiently ameliorate the disease

Molecular Classification of Neuroendocrine Tumors of the Thymus

INTRODUCTION: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. METHODS: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. RESULTS: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). CONCLUSIONS: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication. peerReviewe

HAPLN1 potentiates peritoneal metastasis in pancreatic cancer

The presence of peritoneal metastasis in pancreatic cancers is associated with poor prognosis. Here the authors show that hyaluronan and proteoglycan link protein-1 (HAPLN1) promotes tumour cell plasticity and pro-tumoral immune microenvironment to facilitate peritoneal dissemination in pancreatic cancers. Pancreatic ductal adenocarcinoma (PDAC) frequently metastasizes into the peritoneum, which contributes to poor prognosis. Metastatic spreading is promoted by cancer cell plasticity, yet its regulation by the microenvironment is incompletely understood. Here, we show that the presence of hyaluronan and proteoglycan link protein-1 (HAPLN1) in the extracellular matrix enhances tumor cell plasticity and PDAC metastasis. Bioinformatic analysis showed that HAPLN1 expression is enriched in the basal PDAC subtype and associated with worse overall patient survival. In a mouse model for peritoneal carcinomatosis, HAPLN1-induced immunomodulation favors a more permissive microenvironment, which accelerates the peritoneal spread of tumor cells. Mechanistically, HAPLN1, via upregulation of tumor necrosis factor receptor 2 (TNFR2), promotes TNF-mediated upregulation of Hyaluronan (HA) production, facilitating EMT, stemness, invasion and immunomodulation. Extracellular HAPLN1 modifies cancer cells and fibroblasts, rendering them more immunomodulatory. As such, we identify HAPLN1 as a prognostic marker and as a driver for peritoneal metastasis in PDAC

Selective inactivation of hypomethylating agents by SAMHD1 provides a rationale for therapeutic stratification in AML.

Hypomethylating agents decitabine and azacytidine are regarded as interchangeable in the treatment of acute myeloid leukemia (AML). However, their mechanisms of action remain incompletely understood, and predictive biomarkers for HMA efficacy are lacking. Here, we show that the bioactive metabolite decitabine triphosphate, but not azacytidine triphosphate, functions as activator and substrate of the triphosphohydrolase SAMHD1 and is subject to SAMHD1-mediated inactivation. Retrospective immunohistochemical analysis of bone marrow specimens from AML patients at diagnosis revealed that SAMHD1 expression in leukemic cells inversely correlates with clinical response to decitabine, but not to azacytidine. SAMHD1 ablation increases the antileukemic activity of decitabine in AML cell lines, primary leukemic blasts, and xenograft models. AML cells acquire resistance to decitabine partly by SAMHD1 up-regulation. Together, our data suggest that SAMHD1 is a biomarker for the stratified use of hypomethylating agents in AML patients and a potential target for the treatment of decitabine-resistant leukemia

Pulmonary cancers across different histotypes share hybrid tuft cell/ionocyte-like molecular features and potentially druggable vulnerabilities

Tuft cells are chemosensory epithelial cells in the respiratory tract and several other organs. Recent studies revealed tuft cell-like gene expression signatures in some pulmonary adenocarcinomas, squamous cell carcinomas (SQCC), small cell carcinomas (SCLC), and large cell neuroendocrine carcinomas (LCNEC). Identification of their similarities could inform shared druggable vulnerabilities. Clinicopathological features of tuft cell-like (tcl) subsets in various lung cancer histotypes were studied in two independent tumor cohorts using immunohistochemistry (n = 674 and 70). Findings were confirmed, and additional characteristics were explored using public datasets (RNA seq and immunohistochemical data) (n = 555). Drug susceptibilities of tuft cell-like SCLC cell lines were also investigated. By immunohistochemistry, 10–20% of SCLC and LCNEC, and approximately 2% of SQCC expressed POU2F3, the master regulator of tuft cells. These tuft cell-like tumors exhibited “lineage ambiguity” as they co-expressed NCAM1, a marker for neuroendocrine differentiation, and KRT5, a marker for squamous differentiation. In addition, tuft cell-like tumors co-expressed BCL2 and KIT, and tuft cell-like SCLC and LCNEC, but not SQCC, also highly expressed MYC. Data from public datasets confirmed these features and revealed that tuft cell-like SCLC and LCNEC co-clustered on hierarchical clustering. Furthermore, only tuft cell-like subsets among pulmonary cancers significantly expressed FOXI1, the master regulator of ionocytes, suggesting their bidirectional but immature differentiation status. Clinically, tuft cell-like SCLC and LCNEC had a similar prognosis. Experimentally, tuft cell-like SCLC cell lines were susceptible to PARP and BCL2 co-inhibition, indicating synergistic effects. Taken together, pulmonary tuft cell-like cancers maintain histotype-related clinicopathologic characteristics despite overlapping unique molecular features. From a therapeutic perspective, identification of tuft cell-like LCNECs might be crucial given their close kinship with tuft cell-like SCLC

The B-cell antigen receptor signals through a preformed transducer module of SLP65 and CIN85

The Slp65 adaptor molecule is important for B-cell receptor signalling. Here, the interactomes of SLP65 in resting and activated B cells are resolved by mass spectrometry. A number of SLP65 interacting partners, including CIN85, continuously associate with SLP65 in a stimulation-independent manner. CIN85 recruits SLP65 to the membrane and it is required for SLP65 phosphorylation

SAMHD1 is a biomarker for cytarabine response and a therapeutic target in acute myeloid leukemia.

The nucleoside analog cytarabine (Ara-C) is an essential component of primary and salvage chemotherapy regimens for acute myeloid leukemia (AML). After cellular uptake, Ara-C is converted into its therapeutically active triphosphate metabolite, Ara-CTP, which exerts antileukemic effects, primarily by inhibiting DNA synthesis in proliferating cells. Currently, a substantial fraction of patients with AML fail to respond effectively to Ara-C therapy, and reliable biomarkers for predicting the therapeutic response to Ara-C are lacking. SAMHD1 is a deoxynucleoside triphosphate (dNTP) triphosphohydrolase that cleaves physiological dNTPs into deoxyribonucleosides and inorganic triphosphate. Although it has been postulated that SAMHD1 sensitizes cancer cells to nucleoside-analog derivatives through the depletion of competing dNTPs, we show here that SAMHD1 reduces Ara-C cytotoxicity in AML cells. Mechanistically, dGTP-activated SAMHD1 hydrolyzes Ara-CTP, which results in a drastic reduction of Ara-CTP in leukemic cells. Loss of SAMHD1 activity-through genetic depletion, mutational inactivation of its triphosphohydrolase activity or proteasomal degradation using specialized, virus-like particles-potentiates the cytotoxicity of Ara-C in AML cells. In mouse models of retroviral AML transplantation, as well as in retrospective analyses of adult patients with AML, the response to Ara-C-containing therapy was inversely correlated with SAMHD1 expression. These results identify SAMHD1 as a potential biomarker for the stratification of patients with AML who might best respond to Ara-C-based therapy and as a target for treating Ara-C-refractory AML

Recent advances and conceptual changes in the classification of neuroendocrine tumors of the thymus

Neuroendocrine tumors of the thymus (TNET) are exceedingly rare neoplasms. Their histomorphology is identical to neuroendocrine tumors elsewhere in the body (in particular the lungs) and bears no similarity with thymomas and thymic carcinomas. Recent molecular findings have profoundly changed our perception of these tumors and may impact future histological classification systems