Explore the vast range of titles available.

Tumor-associated macrophages are composed of distinct populations arising from monocytes or tissue macrophages, with a poorly understood link to disease pathogenesis. Here, we demonstrate that mouse monocyte migration was supported by glutaminyl-peptide cyclotransferase-like (QPCTL), an intracellular enzyme that mediates N-terminal modification of several substrates, including the monocyte chemoattractants CCL2 and CCL7, protecting them from proteolytic inactivation. Knockout of Qpctl disrupted monocyte homeostasis, attenuated tumor growth and reshaped myeloid cell infiltration, with loss of monocyte-derived populations with immunosuppressive and pro-angiogenic profiles. Antibody targeting of the receptor CSF1R, which more broadly eliminates tumor-associated macrophages, reversed tumor growth inhibition in Qpctl−/− mice and prevented lymphocyte infiltration. Modulation of QPCTL synergized with anti-PD-L1 to expand CD8+ T cells and limit tumor growth. QPCTL inhibition constitutes an effective approach for myeloid cell-targeted cancer immunotherapy.Tumor-associated macrophages can restrict antitumor responses. Barreira da Silva and colleagues demonstrate that the intracellular enzyme QPCTL supports recruitment of immunomodulatory macrophages to the tumor microenvironment and its targeting can enhance tumor control.

Endoplasmic-reticulum resident inositol-requiring enzyme 1α (IRE1) supports protein homeostasis via its cytoplasmic kinase-RNase module. Known cancer dependency on IRE1 entails its enzymatic activation of the transcription factor XBP1s and of regulated RNA decay. We discovered surprisingly that some cancer cell lines require IRE1 but not its enzymatic activity. IRE1 knockdown but not enzymatic IRE1 inhibition or XBP1 disruption attenuated cell cycle progression and tumor growth. IRE1 silencing led to activation of TP53 and CDKN1A/p21 in conjunction with increased DNA damage and chromosome instability, while decreasing heterochromatin as well as DNA and histone H3K9me3 methylation. Immunoelectron microscopy detected some endogenous IRE1 protein at the nuclear envelope. Thus, cancer cells co-opt IRE1 either enzymatically or nonenzymatically, which has significant implications for IRE1’s biological role and therapeutic targeting.

BackgroundIndividualized neoantigen-specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. It is assumed that clonal neoantigens are preferred targets for immunotherapy, but the distributions of clonal neoantigens are not well characterized across cancer types.MethodsWe combined multiregion sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients in order to characterize their globally clonal neoantigen content and factors that would impact neoantigen targeting.ResultsBranching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. In colorectal, renal, and bladder cancer, most tumors had few globally clonal neoantigens. Prioritizing mutations with higher purity-adjusted and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases.ConclusionsWe show that tumor type, multilesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection, and may also be important factors to consider in the development of biomarker strategies.

The immune phenotype of a tumour is a key predictor of its response to immunotherapy 1 – 4 . Patients who respond to checkpoint blockade generally present with immune-inflamed 5 – 7 tumours that are highly infiltrated by T cells. However, not all inflamed tumours respond to therapy, and even lower response rates occur among tumours that lack T cells (immune desert) or that spatially exclude T cells to the periphery of the tumour lesion (immune excluded) 8 . Despite the importance of these tumour immune phenotypes in patients, little is known about their development, heterogeneity or dynamics owing to the technical difficulty of tracking these features in situ. Here we introduce skin tumour array by microporation (STAMP)—a preclinical approach that combines high-throughput time-lapse imaging with next-generation sequencing of tumour arrays. Using STAMP, we followed the development of thousands of arrayed tumours in vivo to show that tumour immune phenotypes and outcomes vary between adjacent tumours and are controlled by local factors within the tumour microenvironment. Particularly, the recruitment of T cells by fibroblasts and monocytes into the tumour core was supportive of T cell cytotoxic activity and tumour rejection. Tumour immune phenotypes were dynamic over time and an early conversion to an immune-inflamed phenotype was predictive of spontaneous or therapy-induced tumour rejection. Thus, STAMP captures the dynamic relationships of the spatial, cellular and molecular components of tumour rejection and has the potential to translate therapeutic concepts into successful clinical strategies. Skin tumour array by microporation (STAMP) captures the dynamic relationships of spatial, cellular and molecular components of tumour rejection and has the potential to translate therapeutic concepts into successful clinical strategies.

In biology, stochastic branching processes with a two-stage, hierarchical structure arise in the study of population dynamics, gene expression, and phylogenetic inference. These models have been commonly analyzed using generating functions, the method of characteristics and various perturbative approximations. Here we describe a general method for analyzing hierarchic first-order reaction networks using Lie theory. Crucially, we identify the fact that the Lie group associated to hierarchic reaction networks decomposes as a wreath product of the groups associated to the subnetworks of the independent and dependent types. After explaining the general method, we illustrate it on a model of population dynamics and the so-called two-state or telegraph model of single-gene transcription. Solutions to such processes provide essential input to downstream methods designed to attempt to infer parameters of these and related models.

T cells are essential for anti-tumor immunity, but their ability to eliminate tumors depends on coordinated interactions with type 1 conventional dendritic cells (cDC1s). While cDC1s are known for cross-presenting tumor-derived antigens in lymph nodes to prime CD8+ T cells, their role within the tumor itself remains less well understood. Here, we use the Skin Tumor Array by Micro-Poration (STAMP) model to investigate how cDC1-T cell interactions shape immune responses and influence tumor fate. Our data reveal that it is the spatial distribution of both cDC1s and T cells that determines whether a tumor can be rejected. We defined three primary immunotypes based on the spatial distribution of T cells and cDC1s: T cell-inflamed/dendritic cell-inflamed (TC-In/DC-In) tumors, where T cells and cDC1s co-infiltrate the tumor; T cell-inflamed/dendritic cell-excluded (TC-In/DC-Ex) tumors, where T cells infiltrate but cDC1s remain at the periphery; and T cell-excluded/dendritic cell-excluded (TC-Ex/DC-Ex) tumors, which lack both cDC1 and T cell infiltration. Notably, TC-In/DC-In tumors are more likely to undergo rejection, whereas TC-In/DC-Ex tumors persist despite T cell infiltration. Within TC-In/DC-In tumors, cDC1s engage in direct interactions with T cells, upregulate co-stimulatory molecules, and sustain effector T cell responses, while cDC1s in TC-In/DC-Ex tumors express higher migration-associated genes, suggesting a propensity to exit the tumor. We further show that chemokine modulation, particularly through CXCL9, CCL5, and XCL1, can reshape immune infiltration patterns to promote intra-tumoral cDC1-T cell clustering and improve tumor rejection. These findings underscore the unexpectedly important role of cDC1 positioning and function in sustaining effective anti-tumor immunity and highlight spatially organized cDC1-T cell clusters as critical hubs for local T cell activation.

Recent advancements in transcriptomics and proteomics have opened the possibility for spatially resolved molecular characterization of tissue architecture with the promise of enabling a deeper understanding of tissue biology in either homeostasis or disease. The wealth of data generated by these technologies has recently driven the development of a wide range of computational methods. These methods have the requirement of advanced coding fluency to be applied and integrated across the full spatial omics analysis process thus presenting a hurdle for widespread adoption by the biology research community. To address this, we introduce SPEX (Spatial Expression Explorer), a web-based analysis platform that employs modular analysis pipeline design, accessible through a user-friendly interface. SPEX’s infrastructure allows for streamlined access to open source image data management systems,analysis modules, and fully integrated data visualization solutions. Analysis modules include essential steps covering image processing, single-cell and spatial analysis. We demonstrate SPEX’s ability to facilitate the discovery of biological insights in spatially resolved omics datasets from healthy tissue to tumor samples.

Endoplasmic-reticulum resident inositol-requiring enzyme alpha; (IRE1) supports protein homeostasis via a cytoplasmic kinase-RNase module. Known cancer dependency on IRE1 entails its enzymatic activation of the transcription factor XBP1s and of RNA decay. We discovered that some cancer cells require IRE1 but not its enzymatic activity. IRE1 knockdown, but not enzymatic inhibition or XBP1 disruption, increased DNA damage and chromosome instability while engaging the TP53 pathway and cyclin-dependent kinase inhibitors and attenuating cell cycle progression. IRE1 depletion downregulated factors involved in chromosome replication and segregation and in chromatin remodeling. Immunoelectron microscopy indicated that endogenous IRE1 can localize to the nuclear envelope. Thus, cancer cells can require IRE1 either enzymatically or nonenzymatically, with significant implications for IRE1's biological role and therapeutic targeting.Competing Interest StatementThe authors have declared no competing interest.

Purpose: Renal cell carcinoma (RCC) with venous tumor thrombus (VTT) arising from the primary tumor occurs in 4-10% of cases and is associated with advanced disease. RCC with VTT and distant metastasis represents a unique clinical entity, and provides opportunities to examine the origins and relative timing of tumor lesion emergence and to identify molecular correlates with disease state. Experimental Design: We performed genomic and evolutionary analyses on 16 RCC patients with VTT, with eight also having metastases, using multi-region exome and RNA sequencing. Results: No genomic alterations were specifically associated with the VTT or metastasis lesions; each tumor had multiple hallmark driver alterations, consistent with advanced disease state. We found that 21% (3/14) of clear-cell RCC cases could be assigned a previously defined \"evolutionary subtype\". Somatic mutation signatures were largely consistent with previously established RCC signatures, and showed low heterogeneity across regions of each tumor. Mismatch repair and homologous recombination (\"BRCA-ness\") deficiency signatures consistently co-occurred across most tumors, suggesting a pervasive role for intracellular DNA damage in RCC and the potential for related treatment strategies. Phylogenetic timing analysis of metastatic cases suggested that in most tumors, metastases branched from the primary tumor prior to formation of VTT and in some cases before diversification of the primary tumor. Both VTT and the earliest metastases were predicted to emerge many years prior to diagnosis. Transcriptional landscape analysis identified key differences distinguishing each lesion type from primary tumor: VTT upregulated TNF?? signaling and associated inflammatory pathways, whereas metastases upregulated MTOR signaling. Conclusions: Our results provide a map of how RCC tumors can evolve, with metastatic clones typically emerging early in RCC development and taking hold via MTOR signaling, and later formation of VTT via local inflammatory processes. Competing Interest Statement All authors except Dr. Meng and Dr. Porten are paid employees of Genentech and stockholders of Roche.

Abstract Individualized neoantigen specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. To characterize these potential obstacles, we combined multi-region sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients. Branching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. Prioritizing mutations with higher purity- and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases. Our results show that indication type, multi-lesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection. Competing Interest Statement Authors from Genentech, Inc. are employed by and receive stock options from Genentech.