Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides.

Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.

Interferon-sensitized hematopoietic progenitors dynamically alter organismal immunity.

Inflammation has enduring impacts on organismal immunity. However, the precise mechanisms by which tissue-restricted inflammation conditions systemic responses are poorly understood. Here, we leveraged a highly compartmentalized model of skin inflammation and identified a surprising type I interferon (IFN)- mediated activation of hematopoietic stem/progenitor cells (HSPCs) that results in profound changes to systemic host responses. Post-inflamed mice were protected from atherosclerosis and had worse outcomes following influenza virus infection. This IFN-mediated HSPC modulation was dependent on IFNAR signaling and could be recapitulated with the administration of recombinant IFNα. Importantly, the transfer of post-inflamed HSPCs was sufficient to transmit the immune suppression phenotype. IFN modulation of HSPCs was rooted both in long-term changes in chromatin accessibility and the emergence of an IFN- responsive functional state from multiple progenitor populations. Collectively, our data reveal the profound and enduring effect of transient inflammation and more specifically type I IFN signaling and set the stage for a more nuanced understanding of HSPC functional modulation by peripheral immune signals.

Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues.

Emerging imaging spatial transcriptomics (iST) platforms and coupled analytical methods can recover cell-to-cell interactions, groups of spatially covarying genes, and gene signatures associated with pathological features, and are thus particularly well-suited for applications in formalin fixed paraffin embedded (FFPE) tissues. Here, we benchmarked the performance of three commercial iST platforms on serial sections from tissue microarrays (TMAs) containing 23 tumor and normal tissue types for both relative technical and biological performance. On matched genes, we found that 10x Xenium shows higher transcript counts per gene without sacrificing specificity, but that all three platforms concord to orthogonal RNA-seq datasets and can perform spatially resolved cell typing, albeit with different false discovery rates, cell segmentation error frequencies, and with varying degrees of sub-clustering for downstream biological analyses. Taken together, our analyses provide a comprehensive benchmark to guide the choice of iST method as researchers design studies with precious samples in this rapidly evolving field.

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

KEAP1 mutation in lung adenocarcinoma promotes immune evasion and immunotherapy resistance.

Lung cancer treatment has benefited greatly through advancements in immunotherapies. However, immunotherapy often fails in patients with specific mutations like KEAP1, which are frequently found in lung adenocarcinoma. We established an antigenic lung cancer model and used it to explore how Keap1 mutations remodel the tumor immune microenvironment. Using single-cell technology and depletion studies, we demonstrate that Keap1-mutant tumors diminish dendritic cell and T cell responses driving immunotherapy resistance. This observation was corroborated in patient samples. CRISPR-Cas9-mediated gene targeting revealed that hyperactivation of the NRF2 antioxidant pathway is responsible for diminished immune responses in Keap1-mutant tumors. Importantly, we demonstrate that combining glutaminase inhibition with immune checkpoint blockade can reverse immunosuppression, making Keap1-mutant tumors susceptible to immunotherapy. Our study provides new insight into the role of KEAP1 mutations in immune evasion, paving the way for novel immune-based therapeutic strategies for KEAP1-mutant cancers.

Tumor-intrinsic LKB1-LIF signaling axis establishes a myeloid niche to promote immune evasion and tumor growth.

Tumor mutations can influence the surrounding microenvironment leading to suppression of anti-tumor immune responses and thereby contributing to tumor progression and failure of cancer therapies. Here we use genetically engineered lung cancer mouse models and patient samples to dissect how LKB1 mutations accelerate tumor growth by reshaping the immune microenvironment. Comprehensive immune profiling of LKB1 -mutant vs wildtype tumors revealed dramatic changes in myeloid cells, specifically enrichment of Arg1 + interstitial macrophages and SiglecF Hi neutrophils. We discovered a novel mechanism whereby autocrine LIF signaling in Lkb1 -mutant tumors drives tumorigenesis by reprogramming myeloid cells in the immune microenvironment. Inhibiting LIF signaling in Lkb1 -mutant tumors, via gene targeting or with a neutralizing antibody, resulted in a striking reduction in Arg1 + interstitial macrophages and SiglecF Hi neutrophils, expansion of antigen specific T cells, and inhibition of tumor progression. Thus, targeting LIF signaling provides a new therapeutic approach to reverse the immunosuppressive microenvironment of LKB1 -mutant tumors.

An inflammatory state remodels the immune microenvironment and improves risk stratification in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive census of the bone marrow immune microenvironment in adult and pediatric patients with AML. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B-cell subtype enriched in patients with high-inflammation AML, as well as an increase in CD8+GZMK+ and regulatory T cells, accompanied by a reduction in T-cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in patients with AML. Addition of the iScore refines current risk stratifications for patients with AML and may enable identification of patients in need of more aggressive treatment. This work provides a framework for classifying patients with AML based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings.

The Impact of Inflammation-Induced Tumor Plasticity during Myeloid Transformation.

Clonal hematopoiesis (CH) is an aging-associated condition characterized by the clonal outgrowth of mutated preleukemic cells. Individuals with CH are at an increased risk of developing hematopoietic malignancies. Here, we describe a novel animal model carrying a recurrent TET2 missense mutation frequently found in patients with CH and leukemia. In a fashion similar to CH, animals show signs of disease late in life when they develop a wide range of myeloid neoplasms, including acute myeloid leukemia (AML). Using single-cell transcriptomic profiling of the bone marrow, we show that disease progression in aged animals correlates with an enhanced inflammatory response and the emergence of an aberrant inflammatory monocytic cell population. The gene signature characteristic of this inflammatory population is associated with poor prognosis in patients with AML. Our study illustrates an example of collaboration between a genetic lesion found in CH and inflammation, leading to transformation and the establishment of blood neoplasms. SIGNIFICANCE: Progression from a preleukemic state to transformation, in the presence of TET2 mutations, is coupled with the emergence of inflammation and a novel population of inflammatory monocytes. Genes characteristic of this inflammatory population are associated with the worst prognosis in patients with AML. These studies connect inflammation to progression to leukemia. See related commentary by Pietras and DeGregori, p. 2234 . This article is highlighted in the In This Issue feature, p. 2221.

223Ra Induces Transient Functional Bone Marrow Toxicity.

223Ra is a bone-seeking, α-particle-emitting radionuclide approved for the treatment of patients with metastatic prostate cancer and is currently being tested in a variety of clinical trials for primary and metastatic cancers to bone. Clinical evaluation of 223Ra hematologic safety showed a significantly increased rate of neutropenia and thrombocytopenia in patients, hinting at myelosuppression as a side effect. Methods: In this study, we investigated the consequences of 223Ra treatment on bone marrow biology by combining flow cytometry, single-cell RNA sequencing, three-dimensional multiphoton microscopy and bone marrow transplantation analyses. Results: 223Ra accumulated in bones and induced zonal radiation damage confined to the bone interface, followed by replacement of the impaired areas with adipocyte infiltration, as monitored by 3-dimensional multiphoton microscopy ex vivo. Flow cytometry and single-cell transcriptomic analyses on bone marrow hematopoietic populations revealed transient, nonspecific 223Ra-mediated cytotoxicity on resident populations, including stem, progenitor, and mature leukocytes. This toxicity was paralleled by a significant decrease in white blood cells and platelets in peripheral blood-an effect that was overcome within 40 d after treatment. 223Ra exposure did not impair full hematopoietic reconstitution, suggesting that bone marrow function is not permanently hampered. Conclusion: Our results provide a comprehensive explanation of 223Ra reversible effects on bone marrow cells and exclude long-term myelotoxicity, supporting safety for patients.

Surface antigen-guided CRISPR screens identify regulators of myeloid leukemia differentiation.

Lack of cellular differentiation is a hallmark of many human cancers, including acute myeloid leukemia (AML). Strategies to overcome such a differentiation blockade are an approach for treating AML. To identify targets for differentiation-based therapies, we applied an integrated cell surface-based CRISPR platform to assess genes involved in maintaining the undifferentiated state of leukemia cells. Here we identify the RNA-binding protein ZFP36L2 as a critical regulator of AML maintenance and differentiation. Mechanistically, ZFP36L2 interacts with the 3' untranslated region of key myeloid maturation genes, including the ZFP36 paralogs, to promote their mRNA degradation and suppress terminal myeloid cell differentiation. Genetic inhibition of ZFP36L2 restores the mRNA stability of these targeted transcripts and ultimately triggers myeloid differentiation in leukemia cells. Epigenome profiling of several individuals with primary AML revealed enhancer modules near ZFP36L2 that associated with distinct AML cell states, establishing a coordinated epigenetic and post-transcriptional mechanism that shapes leukemic differentiation.