Metabolomics at the tumor microenvironment interface: Decoding cellular conversations.

Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.

Spatial resolution of the head and neck cancer tumor microenvironment to identify tumor and stromal features associated with therapy response.

Head and neck cancer (HNC) is the seventh most common cancer globally, resulting in 440 000 deaths per year. While there have been advancements in chemoradiotherapy and surgery, relapse occurs in more than half of HNCs, and these patients have a median survival of 10 months and a 2-year survival of < 20%. Only a subset of patients displays durable benefits from immunotherapies in metastatic and recurrent HNC, making it critical to understand the tumor microenvironment (TME) underpinning therapy responses in HNC. To recognize biological differences within the TME that may be predictive of immunotherapy response, we applied cutting-edge geospatial whole-transcriptome profiling (NanoString GeoMx Digital Spatial Profiler) and spatial proteomics profiling (Akoya PhenoCycler-Fusion) on a tumor microarray consisting of 25 cores from 12 patients that included 4 immunotherapy-unresponsive (8 cores) and 2 immunotherapy-responsive patients (5 cores), as well as 6 immunotherapy naïve patients (12 cores). Through high-plex, regional-based transcriptomic mapping of the tumor and TME, pathways involved with the complement system and hypoxia were identified to be differentially expressed in patients who went on to experience a poor immunotherapy response. Single-cell, targeted proteomic analysis found that immune cell infiltration of the cancer cell mass and interactions of CD8 T cells with tumor and other immune cells were associated with positive immunotherapy response. The relative abundance of specific tumor phenotypes and their interactions with various immune cells was identified to be different between response groups. This study demonstrates how spatial transcriptomics and proteomics can resolve novel alterations in the TME of HNC that may contribute to therapy sensitivity and resistance.

Spatial insights into immunotherapy response in non-small cell lung cancer (NSCLC) by multiplexed tissue imaging.

The spatial localisation of immune cells within tumours are key to understand the intercellular communications that can dictate clinical outcomes. Here, we demonstrate an analysis pipeline for highly multiplexed CODEX data to phenotype and profile spatial features and interactions in NSCLC patients that subsequently received PD1 axis immunotherapy. We found that regulatory T cells (Tregs) are enriched in non-responding patients and this was consistent with their localization within stromal and peripheral tumour-margins. Proximity-based interactions between Tregs and both monocytes (p = 0.009) and CD8+ T cells (p = 0.009) were more frequently found in non-responding patients, while macrophages were more frequently located in proximity to HLADR+ tumour cells (p = 0.01) within responding patients. Cellular neighbourhoods analysis indicated that both macrophages (p = 0.003) and effector CD4+ T cells (p = 0.01) in mixed tumour neighbourhoods, as well as CD8+ T cells (p = 0.03) in HLADR+ tumour neighbourhoods were associated with favorable clinical response. Evaluation of the inferred regulatory functions between immune cells relative to the tumour suggested that macrophages exhibit an immunosuppressive phenotype against both CD4+ and CD8+ T cells, and that this association scores more highly in ICI refractory patients. These spatial patterns are associated with overall survival in addition to ICI response and may thus indicate features for the functional understanding of the tumour microenvironment.

Spatial dynamics of tertiary lymphoid aggregates in head and neck cancer: insights into immunotherapy response.

BACKGROUND: Recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) generally has a poor prognosis for patients with limited treatment options. While incorporating immune checkpoint inhibitors (ICIs) has now become the standard of care, the efficacy is variable, with only a subset of patients responding. The complexity of the tumor microenvironment (TME) and the role of tertiary lymphoid structures (TLS) have emerged as critical determinants for immunotherapeutic response. METHODS: In this study, we analyzed two independently collected R/M HNSCC patient tissue cohorts to better understand the role of TLS in response to ICIs. Utilizing a multi-omics approach, we first performed targeted proteomic profiling using the Nanostring GeoMx Digital Spatial Profiler to quantify immune-related protein expression with spatial resolution. This was further characterized by spatially resolved whole transcriptome profiling of TLSs and germinal centers (GCs). Deeper single-cell resolved proteomic profiling of the TLSs was performed using the Akoya Biosciences Phenocycler Fusion platform. RESULTS: Our proteomic analysis revealed the presence of T lymphocyte markers, including CD3, CD45, and CD8, expressing cells and upregulation of immune checkpoint marker PD-L1 within tumor compartments of patients responsive to ICIs, indicative of 'hot tumor' phenotypes. We also observed the presence of antigen-presenting cells marked by expression of CD40, CD68, CD11c, and CD163 with upregulation of antigen-presentation marker HLA-DR, in patients responding to ICIs. Transcriptome analysis of TLS and GCs uncovered a marked elevation in the expression of genes related to immune modulation, diverse immune cell recruitment, and a potent interferon response within the TLS structure. Notably, the distribution of TLS-tumor distance was found to be significantly different across response groups (H = 9.28, p = 0.026). The proximity of TLSs to tumor cells was found to be a critical indicator of ICI response, implying that patients with TLSs located further from tumor cells have worse outcomes. CONCLUSION: The study underscores the multifaceted role of TLSs in modulating the immunogenic landscape of the TME in R/M HNSCC, likely influencing the efficacy of ICIs. Spatially resolved multi-omics approaches offer valuable insights into potential biomarkers for ICI response and highlight the importance of profiling the TME complexity when developing therapeutic strategies and patient stratification.

In situ characterization of the tumor microenvironment.

The development of new therapies for cancer is underpinned by an increasing need to comprehensively characterize the tumor microenvironment (TME). While traditional approaches have relied on bulk or single-cell approaches, these are limited in their ability to provide cellular context. Deconvolution of the complex TME is fundamental to understanding tumor dynamics and treatment resistance. Spatially resolved characterization of the TME is likely to provide greater insights into the cellular architecture, tumor-immune cell interactions, receptor-ligand interactions, and cell niches. In turn, these aid in dictating the optimal way in which to target each patient's individual cancer. In this review, we discuss a number of cutting-edge in situ spatial profiling methods giving us new insights into tumor biology.

Spatial proteomic profiling of tumor and stromal compartments in non-small-cell lung cancer identifies signatures associated with overall survival.

Objectives: Non-small-cell lung carcinoma (NSCLC) is the most prevalent and lethal form of lung cancer. The need for biomarker-informed stratification of targeted therapies has underpinned the need to uncover the underlying properties of the tumor microenvironment (TME) through high-plex quantitative assays. Methods: In this study, we profiled resected NSCLC tissues from 102 patients by targeted spatial proteomics of 78 proteins across tumor, immune activation, immune cell typing, immune-oncology, drug targets, cell death and PI3K/AKT modules to identify the tumor and stromal signatures associated with overall survival (OS). Results: Survival analysis revealed that stromal CD56 (HR = 0.384, P = 0.06) and tumoral TIM3 (HR = 0.703, P = 0.05) were associated with better survival in univariate Cox models. In contrast, after adjusting for stage, BCLXL (HR = 2.093, P = 0.02) and cleaved caspase 9 (HR = 1.575, P = 0.1) negatively influenced survival. Delta testing indicated the protective effect of TIM-3 (HR = 0.614, P = 0.04) on OS. In multivariate analysis, CD56 (HR = 0.172, P = 0.001) was associated with better survival in the stroma, while B7.H3 (HR = 1.72, P = 0.008) was linked to poorer survival in the tumor. Conclusions: Deciphering the TME using high-plex spatially resolved methods is giving us new insights into compartmentalised tumor and stromal protein signatures associated with clinical endpoints in NSCLC.

Characterisation of circulating tumor-associated and immune cells in patients with advanced-stage non-small cell lung cancer.

Objectives: Globally, non-small cell lung cancer (NSCLC) is the most prevalent form of lung cancer and the leading cause of cancer-related deaths. Tumor-associated circulating cells in NSCLC can have a wide variety of morphological and phenotypic characteristics, including epithelial, immunological or hybrid subtypes. The distinctive characteristics and potential clinical significance of these cells in patients with NSCLC are explored in this study. Methods: We utilised a spiral microfluidic device to enrich large cells and cell aggregates from the peripheral blood samples of NSCLC patients. These cells were characterised through high-resolution immunofluorescent imaging and statistical analysis, correlating findings with clinical information from our patient cohort. Results: We have identified varied populations of heterotypic circulating tumor cell clusters with differing immune cell composition that included a distinct class of atypical tumor-associated macrophages that exhibits unique morphology and cell size. This subtype's prevalence is positively correlated with the tumor stage, progression and metastasis. Conclusions: Our study reveals a heterogeneous landscape of circulating tumor cells and their clusters, underscoring the complexity of NSCLC pathobiology. The identification of a unique subtype of atypical tumor-associatedmacrophages that simultaneously express both tumor and immune markers and whose presence correlates with late disease stages, poor clinical outcomes and metastatic risk infers  the potential of these cells as biomarkers for NSCLC staging and prognosis. Future studies should focus on the role of these cells in the tumor microenvironment and their potential as therapeutic targets. Additionally, longitudinal studies tracking these cell types through disease progression could provide further insights into their roles in NSCLC evolution and response to treatment.

Targeting the hSSB1-INTS3 Interface: A Computational Screening Driven Approach to Identify Potential Modulators.

Human single-stranded DNA binding protein 1 (hSSB1) forms a heterotrimeric complex, known as a sensor of single-stranded DNA binding protein 1 (SOSS1), in conjunction with integrator complex subunit 3 (INTS3) and C9ORF80. This sensory protein plays an important role in homologous recombination repair of double-strand breaks in DNA to efficiently recruit other repair proteins at the damaged sites. Previous studies have identified elevated hSSB1-mediated DNA repair activities in various cancers, highlighting its potential as an anticancer target. While prior efforts have focused on inhibiting hSSB1 by targeting its DNA binding domain, this study seeks to explore the inhibition of the hSSB1 function by disrupting its interaction with the key partner protein INTS3 in the SOSS1 complex. The investigative strategy entails a molecular docking-based screening of a specific compound library against the three-dimensional structure of INTS3 at the hSSB1 binding interface. Subsequent assessments involve in vitro analyses of protein-protein interaction (PPI) disruption and cellular effects through co-immunoprecipitation and immunofluorescence assays, respectively. Moreover, the study includes an evaluation of the structural stability of ligands at the INTS3 hot-spot site using molecular dynamics simulations. The results indicate a potential in vitro disruption of the INTS3-hSSB1 interaction by three of the tested compounds obtained from the virtual screening with one impacting the recruitment of hSSB1 and INTS3 to chromatin following DNA damage. To our knowledge, our results identify the first set of drug-like compounds that functionally target INTS3-hSSB1 interaction, and this provides the basis for further biophysical investigations that should help to speed up PPI inhibitor discovery.

Sequence- and Structure-Dependent Cytotoxicity of Phosphorothioate and 2'-O-Methyl Modified Single-Stranded Oligonucleotides.

Single-stranded oligonucleotides (SSOs) are a rapidly expanding class of therapeutics that comprises antisense oligonucleotides, microRNAs, and aptamers, with ten clinically approved molecules. Chemical modifications such as the phosphorothioate backbone and the 2'-O-methyl ribose can improve the stability and pharmacokinetic properties of therapeutic SSOs, but they can also lead to toxicity in vitro and in vivo through nonspecific interactions with cellular proteins, gene expression changes, disturbed RNA processing, and changes in nuclear structures and protein distribution. In this study, we screened a mini library of 277 phosphorothioate and 2'-O-methyl-modified SSOs, with or without mRNA complementarity, for cytotoxic properties in two cancer cell lines. Using circular dichroism, nucleic magnetic resonance, and molecular dynamics simulations, we show that phosphorothioate- and 2'-O-methyl-modified SSOs that form stable hairpin structures through Watson-Crick base pairing are more likely to be cytotoxic than those that exist in an extended conformation. In addition, moderate and highly cytotoxic SSOs in our dataset have a higher mean purine composition than pyrimidine. Overall, our study demonstrates a structure-cytotoxicity relationship and indicates that the formation of stable hairpins should be a consideration when designing SSOs toward optimal therapeutic profiles.

Whole transcriptome profiling of placental pathobiology in SARS-CoV-2 pregnancies identifies placental dysfunction signatures.

Objectives: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection in pregnancy is associated with higher incidence of placental dysfunction, referred to by a few studies as a 'preeclampsia-like syndrome'. However, the mechanisms underpinning SARS-CoV-2-induced placental malfunction are still unclear. Here, we investigated whether the transcriptional architecture of the placenta is altered in response to SARS-CoV-2 infection. Methods: We utilised whole-transcriptome, digital spatial profiling, to examine gene expression patterns in placental tissues from participants who contracted SARS-CoV-2 in the third trimester of their pregnancy (n = 7) and those collected prior to the start of the coronavirus disease 2019 (COVID-19) pandemic (n = 9). Results: Through comprehensive spatial transcriptomic analyses of the trophoblast and villous core stromal cell subpopulations in the placenta, we identified SARS-CoV-2 to promote signatures associated with hypoxia and placental dysfunction. Notably, genes associated with vasodilation (NOS3), oxidative stress (GDF15, CRH) and preeclampsia (FLT1, EGFR, KISS1, PAPPA2) were enriched with SARS-CoV-2. Pathways related to increased nutrient uptake, vascular tension, hypertension and inflammation were also enriched in SARS-CoV-2 samples compared to uninfected controls. Conclusions: Our findings demonstrate the utility of spatially resolved transcriptomic analysis in defining the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy, particularly its role in placental dysfunction. Furthermore, this study highlights the significance of digital spatial profiling in mapping the intricate crosstalk between trophoblasts and villous core stromal cells, thus shedding light on pathways associated with placental dysfunction in pregnancies with SARS-CoV-2 infection.