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Tumor extracellular matrix has been associated with drug resistance and immune suppression. Here, proteomic and RNA profiling reveal increased collagen levels in lung tumors resistant to PD-1/PD-L1 blockade. Additionally, elevated collagen correlates with decreased total CD8 + T cells and increased exhausted CD8 + T cell subpopulations in murine and human lung tumors. Collagen-induced T cell exhaustion occurs through the receptor LAIR1, which is upregulated following CD18 interaction with collagen, and induces T cell exhaustion through SHP-1. Reduction in tumor collagen deposition through LOXL2 suppression increases T cell infiltration, diminishes exhausted T cells, and abrogates resistance to anti-PD-L1. Abrogating LAIR1 immunosuppression through LAIR2 overexpression or SHP-1 inhibition sensitizes resistant lung tumors to anti-PD-1. Clinically, increased collagen, LAIR1, and TIM-3 expression in melanoma patients treated with PD-1 blockade predict poorer survival and response. Our study identifies collagen and LAIR1 as potential markers for immunotherapy resistance and validates multiple promising therapeutic combinations. Tumor extracellular matrix has been associated with cancer progression, therapy resistance and immune suppression. Here, the authors show that collagen generates resistance to PD-1/PD-L1 immunotherapy by upregulating LAIR1 expression and downstream signaling, leading to increased CD8+ T cell exhaustion.

Multiplexed platforms for multiple epitope detection have emerged in the last years as very powerful tools to study tumor tissues. These revolutionary technologies provide important visual techniques for tumor examination in formalin-fixed paraffin-embedded specimens to improve the understanding of the tumor microenvironment, promote new treatment discoveries, aid in cancer prevention, as well as allowing translational studies to be carried out. The aim of this review is to highlight the more recent methodologies that use multiplexed staining to study simultaneous protein identification in formalin-fixed paraffin-embedded tumor tissues for immune profiling, clinical research, and potential translational analysis. New multiplexed methodologies, which permit the identification of several proteins at the same time in one single tissue section, have been developed in recent years with the ability to study different cell populations, cells by cells, and their spatial distribution in different tumor specimens including whole sections, core needle biopsies, and tissue microarrays. Multiplexed technologies associated with image analysis software can be performed with a high-quality throughput assay to study cancer specimens and are important tools for new discoveries. The different multiplexed technologies described in this review have shown their utility in the study of cancer tissues and their advantages for translational research studies and application in cancer prevention and treatments.

Although non-small cell lung cancer (NSCLC) remains a deadly disease, new predictive biomarkers have emerged to assist in managing the disease, of which one of the most promising is the programmed death-ligand 1 (PD-L1). Each, variant seem to modulate the function of immune checkpoints differently and affect response to adjuvant treatment and outcome in NSCLC patients. We thus investigated the influence of these PD-L1 genetic variations in genetically admixed NSCLC tissue samples, and correlated these values with clinicopathological characteristics, including prognosis. We evaluated PD-L1 non-coding genetic variants and protein expression in lung adenocarcinomas (ADC), squamous cell carcinomas (SqCC), and large cell carcinomas (LCC) in silico. Microarray paraffin blocks from 70 samples of ADC (N=33), SqCC (N=24), and LCC (N=13) were used to create PD-L1 multiplex immunofluorescence assays with a Cell Signaling E1L3N clone. Fifteen polymorphisms of the gene were investigated by targeted sequencing and evaluated in silico using dedicated tools. Although polymorphisms seemed not to interfere with protein expression, PD-L1 expression varied among different histological subtypes, as did clinical outcomes, with the rs4742098A>G, rs4143815G>C, and rs7041009G>A variants being associated with relapse ( =0.01; =0.05; =0.02, respectively). The rs7041009 GG genotype showed a significant correlation with younger and alive patients compared to carriers of the A allele ( =0.02 and 0.01, respectively). The Cox regression model showed that the rs7041009 GG genotype may influence OS ( <0.01) as a co-dependent factor associated with radiotherapy and recurrence in NSCLC patients. Furthermore, the Kaplan-Meier survival curves showed that rs7041009 and rs4742098 might impact PPS in relapsed patients. In silico approaches identified the variants as benign. non-coding variants play an important role in modulating immune checkpoint function and may be explored as immunotherapy biomarkers. We highlight the rs7041009 variant, which impacts OS and PPS in NSCLC patients.

Immunotherapy targeting T cells is increasingly utilized to treat solid tumors including non-small cell lung cancer (NSCLC). This requires a better understanding of the T cells in the lungs of patients with NSCLC. Here, we report T cell repertoire analysis in a cohort of 236 early-stage NSCLC patients. T cell repertoire attributes are associated with clinicopathologic features, mutational and immune landscape. A considerable proportion of the most prevalent T cells in tumors are also prevalent in the uninvolved tumor-adjacent lungs and appear specific to shared background mutations or viral infections. Patients with higher T cell repertoire homology between the tumor and uninvolved tumor-adjacent lung, suggesting a less tumor-focused T cell response, exhibit inferior survival. These findings indicate that a concise understanding of antigens and T cells in NSCLC is needed to improve therapeutic efficacy and reduce toxicity with immunotherapy, particularly adoptive T cell therapy. Relevant features of T cell repertoire in human cancer remain to be delineated. Here the authors show, by TCR sequencing in a large cohort of lung cancer patients, that while a majority of T cell clones are shared between tumor and adjacent lung tissue, less frequent tumor-unique T cell clones correlate with worse prognosis.

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns—an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions. The spatial distribution of cellular compartments within the tumour microenvironment in non-small cell lung cancer (NSCLC) remains to be investigated. Here, the authors identify distinct cell populations of tumour cells and tumour-associated immune cell phenotypes with different spatial distributions in NSCLC.

There has been a dramatic increase in the detection of lung nodules, many of which are preneoplasia atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (ADC). The molecular landscape and the evolutionary trajectory of lung preneoplasia have not been well defined. Here, we perform multi-region exome sequencing of 116 resected lung nodules including AAH (n = 22), AIS (n = 27), MIA (n = 54) and synchronous ADC (n = 13). Comparing AAH to AIS, MIA and ADC, we observe progressive genomic evolution at the single nucleotide level and demarcated evolution at the chromosomal level supporting the early lung carcinogenesis model from AAH to AIS, MIA and ADC. Subclonal analyses reveal a higher proportion of clonal mutations in AIS/MIA/ADC than AAH suggesting neoplastic transformation of lung preneoplasia is predominantly associated with a selective sweep of unfit subclones. Analysis of multifocal pulmonary nodules from the same patients reveal evidence of convergent evolution. There has been a drastic increase in detection of lung nodules, many of which are precancers, preinvasive, minimally invasive or sometimes invasive lung cancers. Here, Hu et al. perform multi-region exome sequencing to discern the evolutional trajectory from precancers to invasive lung cancers.

Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient’s TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.

Multiplex immunofluorescence (mIF) has arisen as an important tool for immuno-profiling tumor tissues. We updated our manual protocol into an automated protocol that allows the use of up to seven markers in five mIF panels to apply to formalin-fixed paraffin-embedded tumor tissues. Using a tyramide signal amplification system, we optimized five mIF panels that included cytokeratin to characterize malignant cells (MCs), immune checkpoint markers (i.e., PD-L1, B7-H3, B7-H4, IDO-1, VISTA, LAG3, ICOS, TIM3, and OX40), tumor-infiltrating lymphocytic markers (i.e., CD3, CD8, CD45RO, granzyme B, PD-1, and FOXP3), and markers to characterize myeloid-derived suppressor cells (i.e., CD68, CD66b, CD14, CD33, Arg-1, and CD11b). To determine analytical reproducibility and the impact of those panels for immuno-profiling tumor tissues, we performed an exploratory analysis in a set of non–small cell lung cancer (NSCLC) samples. The slides were scanned, and the different cell phenotypes were quantified by simultaneous co-localizations with the markers using image analysis software. Comparison between the time points of staining showed high analytical reproducibility. The analysis of NSCLC cases showed an immunosuppressive microenvironment with PD-L1/PD-1 expression as a predominant axis. Interestingly, high density of MCs expressing B7-H4 was correlated with recurrence. Unexpectedly, MCs expressing OX40 were also detected, and those cells were a closer distance to CD3+T-cells than were MCs expressing other immune checkpoints. Two different cellular patterns of spatial distribution were determined according the CD3 distribution, and the predominant pattern was related with active immunosuppressive interaction with MCs. Our study shows that these five mIF panels can identify multiple targets in a single cell with high reproducibility. The study of different cell populations and their spatial relationship can open new ideas for therapeutic approaches.

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.

Small-cell lung cancer (SCLC) is speculated to harbor complex genomic intratumor heterogeneity (ITH) associated with high recurrence rate and suboptimal response to immunotherapy. Here, using multi-region whole exome/T cell receptor (TCR) sequencing as well as immunohistochemistry, we reveal a rather homogeneous mutational landscape but extremely cold and heterogeneous TCR repertoire in limited-stage SCLC tumors (LS-SCLCs). Compared to localized non-small cell lung cancers, LS-SCLCs have similar predicted neoantigen burden and genomic ITH, but significantly colder and more heterogeneous TCR repertoire associated with higher chromosomal copy number aberration (CNA) burden. Furthermore, copy number loss of IFN-γ pathway genes is frequently observed and positively correlates with CNA burden. Higher mutational burden, higher T cell infiltration and positive PD-L1 expression are associated with longer overall survival (OS), while higher CNA burden is associated with shorter OS in patients with LS-SCLC. Small-cell lung cancer (SCLC) is an aggressive disease with limited therapeutic options. Here the authors perform an immunogenomic analysis of limited-stage SCLC, revealing a homogeneous mutational landscape, but limited T-cell infiltration and a cold and heterogeneous T cell repertoire.