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Understanding the cellular processes that underlie early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies 1 . Here we studied 246,102 single epithelial cells from 16 early-stage LUADs and 47 matched normal lung samples. Epithelial cells comprised diverse normal and cancer cell states, and diversity among cancer cells was strongly linked to LUAD-specific oncogenic drivers. KRAS mutant cancer cells showed distinct transcriptional features, reduced differentiation and low levels of aneuploidy. Non-malignant areas surrounding human LUAD samples were enriched with alveolar intermediate cells that displayed elevated KRT8 expression (termed KRT8 + alveolar intermediate cells (KACs) here), reduced differentiation, increased plasticity and driver KRAS mutations. Expression profiles of KACs were enriched in lung precancer cells and in LUAD cells and signified poor survival. In mice exposed to tobacco carcinogen, KACs emerged before lung tumours and persisted for months after cessation of carcinogen exposure. Moreover, they acquired Kras mutations and conveyed sensitivity to targeted KRAS inhibition in KAC-enriched organoids derived from alveolar type 2 (AT2) cells. Last, lineage-labelling of AT2 cells or KRT8 + cells following carcinogen exposure showed that KACs are possible intermediates in AT2-to-tumour cell transformation. This study provides new insights into epithelial cell states at the root of LUAD development, and such states could harbour potential targets for prevention or intervention. Analyses of single epithelial cells from early-stage lung adenocarcinoma and normal lung identifies a population of intermediate cells that may have an increased likelihood of transforming to tumour cells after injury such as tobacco exposure.

The deadly complication of brain metastasis (BM) is largely confined to a relatively narrow cross-section of systemic malignancies, suggesting a fundamental role for biological mechanisms shared across commonly brain metastatic tumor types. To identify and characterize such mechanisms, we performed genomic, transcriptional, and proteomic profiling using whole-exome sequencing, mRNA-seq, and reverse-phase protein array analysis in a cohort of the lung, breast, and renal cell carcinomas consisting of BM and patient-matched primary or extracranial metastatic tissues. While no specific genomic alterations were associated with BM, correlations with impaired cellular immunity, upregulated oxidative phosphorylation (OXPHOS), and canonical oncogenic signaling pathways including phosphoinositide 3-kinase (PI3K) signaling, were apparent across multiple tumor histologies. Multiplexed immunofluorescence analysis confirmed significant T cell depletion in BM, indicative of a fundamentally altered immune microenvironment. Moreover, functional studies using in vitro and in vivo modeling demonstrated heightened oxidative metabolism in BM along with sensitivity to OXPHOS inhibition in murine BM models and brain metastatic derivatives relative to isogenic parentals. These findings demonstrate that pathophysiological rewiring of oncogenic signaling, cellular metabolism, and immune microenvironment broadly characterizes BM. Further clarification of this biology will likely reveal promising targets for therapeutic development against BM arising from a broad variety of systemic cancers.

In the development of a multiplex immunofluorescence (IF) platform and the optimization and validation of new multiplex IF panels using a tyramide signal amplification system, several technical requirements are important for high-quality staining, analysis, and results. The aim of this review is to discuss the basic requirements for performing multiplex IF tyramide signal amplification (TSA) in formalin-fixed, paraffin-embedded cancer tissues to support translational oncology research. Our laboratory has stained approximately 4000 formalin-fixed, paraffin-embedded tumor samples using the multiplex IF TSA system for immune profiling of several labeled biomarkers in a single slide to elucidate cancer biology at a protein level and identify therapeutic targets and biomarkers. By analyzing several proteins in thousands of cells on a single slide, this technique provides a systems-level view of various processes in various tumor tissues. Although this technology shows high flexibility in cancer studies, it presents several challenges when applied to study different histology cancers. Our experience shows that adequate antibody validation, staining optimization, analysis strategies, and data generation are important steps for generating quality results. Tissue management, fixation procedures, storage, and cutting can also affect the results of the assay and must be standardized. Overall, this method is reliable for supporting translational research given a precise, step-by-step approach.

This phase I/II trial aims to evaluate the efficacy of concurrent atezolizumab with radiation therapy and temozolomide (TMZ) followed by adjuvant atezolizumab and TMZ in newly diagnosed glioblastoma (GBM) patients and to identify pre-treatment correlates with outcome ( N  = 60). Trial number: NCT03174197. The primary outcome was overall survival (OS) whereas secondary outcomes were retrospective global–omics analyses to identify pre-treatment immune and genetic tumor features that correlated with survival. Concurrent use of atezolizumab with radiation and TMZ demonstrated OS in line with published trials for newly diagnosed GBM. Tumor genomic (WES and/or targeted NGS panel), transcriptomic (RNAseq) and tissue microenvironment imaging, as well as fecal metagenomic sequencing were conducted. Gene set enrichment analysis of tumors identified multiple immune-based transcriptomic programs to distinguish patients with longer versus shorter survival ( p  ≤ 0.01). GBM immune enrichment was highly associated with the pre-treatment tumor mesenchymal subtype and patient gastrointestinal bacterial taxa profile. Checkpoint inhibitor (CPI) therapy is modestly effective in Glioblastoma patients, with some patients not benefitting at all. Authors here present the outcomes of single arm prospective clinical trial employing combination CPI therapy in newly diagnosed GBM and identify the pre-treatment genetic, microbiome and immunological factors that might contribute to sensitivity.

Delta-like Ligand 3 (DLL3) targeting therapies are promising in small cell lung cancer (SCLC) treatment. However, DLL3 expression in SCLC and other neuroendocrine neoplasms (NEN) is heterogeneous and not well characterized. We describe the landscape of DLL3 at the mRNA and protein levels across SCLC, large cell neuroendocrine carcinoma (LCNEC), and non-small cell lung cancer. Additionally, we explore its expression in extra-pulmonary NEN (EP-NEN) using a standardized DLL3 IHC assay. DLL3 expression is enriched in SCLC, LCNEC along with combined histology lung cancers. Moreover, we find a wide range of DLL3 expression in high-grade EP-NEN. We describe heterogenous DLL3 expression not only in SCLC but also in different NEN types. This comprehensive characterization of DLL3 can help guide future clinical trial design targeting DLL3 in NEN including LCNEC and EP-NEN that are lacking standard of care treatment options.

Pancreatic ductal adenocarcinoma (PDAC) is considered non-immunogenic, with trials showing its recalcitrance to PD1 and CTLA4 immune checkpoint therapies (ICTs). Here, we sought to systematically characterize the mechanisms underlying de novo ICT resistance and to identify effective therapeutic options for PDAC. We report that agonist 41BB and antagonist LAG3 ICT alone and in combination, increased survival and antitumor immunity, characterized by modulating T cell subsets with antitumor activity, increased T cell clonality and diversification, decreased immunosuppressive myeloid cells and increased antigen presentation/decreased immunosuppressive capability of myeloid cells. Translational analyses confirmed the expression of 41BB and LAG3 in human PDAC. Since single and dual ICTs were not curative, T cell-activating ICTs were combined with a CXCR1/2 inhibitor targeting immunosuppressive myeloid cells. Triple therapy resulted in durable complete responses. Given similar profiles in human PDAC and the availability of these agents for clinical testing, our findings provide a testable hypothesis for this lethal disease.

Lung cancer is a deadly disease with the highest rates of mortality. Over recent decades, a better understanding of the biological mechanisms implicated in its pathogenesis has led to the development of targeted therapies and immunotherapy, resulting in improvements in patient outcomes. To better understand lung cancer tumor biology and advance towards precision oncology, a comprehensive tumor profile is necessary. In recent years, novel in situ spatial multiomics approaches have emerged offering a more detailed view of the spatial location of tumor and tumor microenvironment cells, identifying their unique composition and functional status. In this sense, novel multiomics platforms have been developed to evaluate tumor heterogeneity, gene expression, metabolic reprogramming, signaling pathway activation, cell–cell interactions, and immune cell programs. In lung cancer research, several studies have used these spatial technologies to locate cells and associated them with histological features that are relevant to the pathogenesis of lung adenocarcinoma. These advancements may unveil further molecular and immune mechanisms in tumor biology that will lead to the discovery of biomarkers for treatment prediction and prognosis. In this review, we provide an overview of more widely used and emerging pathology-based approaches for spatial immune profiling in lung cancer and how they enhance our understanding of tumor biology and immune response.

Imaging-based spatial transcriptomics (ST) is evolving as a pivotal technology in studying tumor biology and associated microenvironments. However, the strengths of the commercially available ST platforms in studying spatial biology have not been systematically evaluated using rigorously controlled experiments. We use serial 5 μm sections of formalin-fixed, paraffin-embedded surgically resected lung adenocarcinoma and pleural mesothelioma samples in tissue microarrays to compare the performance of the ST platforms (CosMx, MERFISH, and Xenium (uni/multi-modal)) in reference to bulk RNA sequencing, multiplex immunofluorescence, GeoMx, and hematoxylin and eosin staining data. In addition to an objective assessment of automatic cell segmentation and phenotyping, we perform a manual phenotyping evaluation to assess pathologically meaningful comparisons between ST platforms. Here, we show the intricate differences between the ST platforms, reveal the importance of parameters such as probe design in determining the data quality, and suggest reliable workflows for accurate spatial profiling and molecular discovery. Spatial cell distribution within a tissue microenvironment is a rapidly advancing field. Here, authors assess three commercially available single-cell resolution spatial transcriptomics approaches (CosMx, MERFISH, and Xenium) to inform which technology outperforms for immune profiling of solid tumors using patient samples.

Low-grade serous carcinoma of the ovary (LGSOC) is relatively resistant to chemotherapy. Given its biological parallels to hormone receptor-positive breast cancer, including responsiveness to anti-estrogen therapies, we conducted a pilot phase II study to assess clinical benefit of neoadjuvant fulvestrant and abemaciclib in women with advanced, unresectable LGSOC (NCT03531645). Imaging assessments were performed every 8 weeks until resectable. The primary endpoint was clinical benefit rate (CBR). Exploratory objectives included evaluation of safety profile, accessing biomarkers related to clinical benefit, and description of tumor phenotypic changes. Fifteen patients were enrolled and evaluable for efficacy. CBR was 100%, with 1/15 patients (7%) achieving complete response (CR), 8/15 patients (53%) achieving partial response (PR), and 6/15 (40%) exhibiting stable disease (SD). Interval cytoreductive surgery (ICS) was performed in 9 patients (60%), with 7 (78%) achieving complete or optimal resection. Fourteen tumor samples underwent transcriptomic and proteomic profiling. Tumors from long-term survivors showed significantly higher baseline expression of cell-cycle-related programs and estrogen signaling-related genes, both suppressed upon treatment. Neoadjuvant fulvestrant and abemaciclib was well tolerated, achieved high response rates, and enabled optimal surgical resection in most patients. Tumor proliferative activity and estrogen signaling dependency may predict therapy response.