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Background Greater understanding of differential therapeutic sensitivity, specifically to immunotherapy, in small-cell lung cancer (SCLC) is required. Methods We explored SCLC heterogeneity through integrated molecular characterization of tumor tissue samples from 159 treatment-naive patients, utilizing genetic, epigenetic, transcriptional, and proteomic profiling, immunohistochemistry staining for multiple biologically relevant markers including transcriptional subtype-defining proteins, and spatial immune profiling using multiplex immunofluorescence. Results Multi-omics analysis confirmed high heterogeneity across/within neuroendocrine and non-neuroendocrine subtypes. Methylomics analysis identified four methylome clusters that may enhance subtype prediction, prognosis, and longitudinal monitoring of subtype evolution. Immunohistochemistry analysis showed high MHC-I expression in non-neuroendocrine subtypes, which have greatest potential benefit from adding immunotherapy to chemotherapy; high DLL3 expression associated with neuroendocrine subtypes and an immune-cold tumor microenvironment. Multiplex immunofluorescence demonstrated associations of MHC-I with spatial arrangement and phenotypic features of immune cells in the tumor microenvironment of high-MHC-I-expressing SCLC, providing mechanistic rationale for MHC-I as a potential biomarker of immunotherapy response. Conclusions This multimodal profiling analysis provides further insights into the biologic complexity of SCLC and highlights potential therapeutic vulnerabilities of distinct disease subtypes. Graphical abstract

Tertiary Lymphoid Structures (TLS) are lymphoid structures commonly associated with improved survival of cancer patients and response to immunotherapies. However, conflicting reports underscore the need to consider TLS heterogeneity and multiple features such as TLS size, composition, and maturation status, when assessing their functional impact. With the aim of gaining insights into TLS biology and evaluating the prognostic impact of TLS maturity in Non-Small Cell Lung Carcinoma (NSCLC), we developed a multiplex immunofluorescent (mIF) panel including T cell (CD3, CD8), B cell (CD20), Follicular Dendritic cell (FDC) (CD21, CD23) and mature dendritic cell (DC-LAMP) markers. We deployed this panel across a cohort of primary tumor resections from NSCLC patients (N=406) and established a mIF image analysis workstream to specifically detect TLS structures and evaluate the density of each cell phenotype. We assessed the prognostic significance of TLS size, number, and composition, to develop a TLS scoring system representative of TLS biology within a tumor. TLS relative area, (total TLS area divided by the total tumor area), was the most prognostic TLS feature (C-index: 0.54, p = 0.04). CD21 positivity was a marker driving the favorable prognostic impact, where CD21 + CD23 - B cells (C-index: 0.57, p = 0.04) and CD21 + CD23 - FDC (C-index: 0.58, p = 0.01) were the only prognostic cell phenotypes in TLS. Combining the three most robust prognostic TLS features: TLS relative area, the density of B cells, and FDC CD21 + CD23 - we generated a TLS scoring system that demonstrated strong prognostic value in NSCLC when considering the effect of age, sex, histology, and smoking status. This TLS Score also demonstrated significant association with Immunoscore, EGFR mutational status and gene expression-based B-cell and TLS signature scores. It was not correlated with PD-L1 status in tumor cells or immune cells. In conclusion, we generated a prognostic TLS Score representative of the TLS heterogeneity and maturity undergoing within NSCLC tissues. This score could be used as a tool to explore how TLS presence and maturity impact the organization of the tumor microenvironment and support the discovery of spatial biomarker surrogates of TLS maturity, that could be used in the clinic.

Cell migration on microlanes represents a suitable and simple platform for the exploration of the molecular mechanisms underlying cell cytoskeleton dynamics. Here, we report on the quasi-periodic movement of cells confined in stripe-shaped microlanes. We observe persistent polarized cell shapes and directed pole-to-pole motion within the microlanes. Cells depolarize at one end of a given microlane, followed by delayed repolarization towards the opposite end. We analyze cell motility via the spatial velocity distribution, the velocity frequency spectrum and the reversal time as a measure for depolarization and spontaneous repolarization of cells at the microlane ends. The frequent encounters of a boundary in the stripe geometry provides a robust framework for quantitative investigations of the cytoskeleton protrusion and repolarization dynamics. In a first advance to rigorously test physical models of cell migration, we find that the statistics of the cell migration is recapitulated by a Cellular Potts model with a minimal description of cytoskeleton dynamics. Using LifeAct-GFP transfected cells and microlanes with differently shaped ends, we show that the local deformation of the leading cell edge in response to the tip geometry can locally either amplify or quench actin polymerization, while leaving the average reversal times unaffected.

Quantification and discrimination of pharmaceutical and disease-related effects on cell migration requires detailed characterization of single-cell motility. In this context, micropatterned substrates that constrain cells within defined geometries facilitate quantitative readout of locomotion. Here, we study quasi-one-dimensional cell migration in ring-shaped microlanes. We observe bimodal behavior in form of alternating states of directional migration (run state) and reorientation (rest state). Both states show exponential lifetime distributions with characteristic persistence times, which, together with the cell velocity in the run state, provide a set of parameters that succinctly describe cell motion. By introducing PEGylated barriers of different widths into the lane, we extend this description by quantifying the effects of abrupt changes in substrate chemistry on migrating cells. The transit probability decreases exponentially as a function of barrier width, thus specifying a characteristic penetration depth of the leading lamellipodia. Applying this fingerprint-like characterization of cell motion, we compare different cell lines and demonstrate that the cancer drug candidate salinomycin affects transit probability and resting time, but not run time or run velocity. Hence, the presented assay allows to assess multiple migration-related parameters, permits detailed characterization of cell motility and has potential applications in cell biology and advanced drug screening.

Tumor programmed cell death ligand-1 (PD-L1) expression is a key biomarker to identify patients with non-small cell lung cancer who may have an enhanced response to anti-programmed cell death-1 (PD-1)/PD-L1 treatment. Such treatments are used in conjunction with PD-L1 diagnostic immunohistochemistry assays. We developed a computer-aided automated image analysis with customized PD-L1 scoring algorithm that was evaluated via correlation with manual pathologist scores and used to determine comparability across PD-L1 immunohistochemistry assays. The image analysis scoring algorithm was developed to quantify the percentage of PD-L1 positive tumor cells on scans of whole-slide images of archival tumor samples from commercially available non-small cell lung cancer cases, stained with four immunohistochemistry PD-L1 assays (Ventana SP263 and SP142 and Dako 22C3 and 28-8). The scans were co-registered and tumor and exclusion annotations aligned to ensure that analysis of each case was restricted to comparable tissue areas. Reference pathologist scores were available from previous studies. F1, a statistical measure of precision and recall, and overall percentage agreement scores were used to assess concordance between pathologist and image analysis scores and between immunohistochemistry assays. In total, 471 PD-L1-evalulable samples were amenable to image analysis scoring. Image analysis and pathologist scores were highly concordant, with F1 scores ranging from 0.8 to 0.9 across varying matched PD-L1 cutoffs. Based on F1 and overall percentage agreement scores (both manual and image analysis scoring), the Ventana SP263 and Dako 28-8 and 22C3 assays were concordant across a broad range of cutoffs; however, the Ventana SP142 assay showed very different characteristics. In summary, a novel automated image analysis scoring algorithm was developed that was highly correlated with pathologist scores. The algorithm permitted quantitative comparison of existing PD-L1 diagnostic assays, confirming previous findings that indicate a high concordance between the Ventana SP263 and Dako 22C3 and 28-8 PD-L1 immunohistochemistry assays.

Cell migration on microlanes represents a suitable and simple platform for the exploration of the molecular mechanisms underlying cell cytoskeleton dynamics. Here, we report on the quasi-periodic movement of cells confined in stripe-shaped microlanes. We observe persistent polarized cell shapes and directed pole-to-pole motion within the microlanes. Cells depolarize at one end of a given microlane, followed by delayed repolarization towards the opposite end. We analyze cell motility via the spatial velocity distribution, the velocity frequency spectrum and the reversal time as a measure for depolarization and spontaneous repolarization of cells at the microlane ends. The frequent encounters of a boundary in the stripe geometry provides a robust framework for quantitative investigations of the cytoskeleton protrusion and repolarization dynamics. In a first advance to rigorously test physical models of cell migration, we find that the statistics of the cell migration is recapitulated by a Cellular Potts model with a minimal description of cytoskeleton dynamics. Using LifeAct-GFP transfected cells and microlanes with differently shaped ends, we show that the local deformation of the leading cell edge in response to the tip geometry can locally either amplify or quench actin polymerization, while leaving the average reversal times unaffected.

Unsupervised and unpaired domain translation using generative adversarial neural networks, and more precisely CycleGAN, is state of the art for the stain translation of histopathology images. It often, however, suffers from the presence of cycle-consistent but non structure-preserving errors. We propose an alternative approach to the set of methods which, relying on segmentation consistency, enable the preservation of pathology structures. Focusing on immunohistochemistry (IHC) and multiplexed immunofluorescence (mIF), we introduce a simple yet effective guidance scheme as a loss function that leverages the consistency of stain translation with stain isolation. Qualitative and quantitative experiments show the ability of the proposed approach to improve translation between the two domains.

The spontaneous formation of vortices is a hallmark of collective cellular activity. Here, we study the onset and persistence of coherent angular motion (CAMo) as a function of the number of cells \\(N\\) confined in circular micropatterns. We find that the persistence of CAMo increases with \\(N\\) but exhibits a pronounced discontinuity accompanied by a geometric rearrangement of cells to a configuration containing a central cell. Computer simulations based on a generalized Potts model reproduce the emergence of vortex states and show in agreement with experiment that their stability depends on the interplay of spatial arrangement and internal polarization of neighboring cells. Hence, the distinct migrational states in finite size ensembles reveal significant insight into the local interaction rules guiding collective migration.

BackgroundSmall cell lung cancer (SCLC) is an aggressive and largely immune-cold cancer type, for which chemotherapy combined with Immuno-oncology (IO) therapies is providing benefit only in a subgroup of patients. SCLC is a highly heterogeneous cancer with at least four major subtypes.1 Among them, the ‘inflamed’ subtype is characterized by an inflamed immune gene signature and high expression of MHC class I (MHC-I) antigen presentation and shows the greatest benefit from the addition of IO treatment to chemotherapy,2 suggesting that MHC-I could serve as a biomarker for IO therapies. Here, we aimed to assess the spatial characteristics of immune cells in MHC-I high SCLC cases to investigate and support its role as a potential biomarker for IO therapies.MethodsWe combined a computational pathology approach with multiplex immunofluorescence (mIF) to profile the SCLC tumor microenvironment (TME). To this end, 126 SCLC formalin-fixed, paraffin-embedded tissue samples were stained with two mIF panels consisting of six markers each: (A) PanCK, CD8, CD68, PD-1, PD-L1, and Ki67; (B) CD20, NKp46, CD1c, CD66b, ICOS, and FOXP3. Based on these panels, we investigated the location and phenotype of each cell in the tumor center and within the stroma and tumor parenchyma. Additional slides from the same tissue blocks were immunohistochemically stained with MHC-I and scored by pathologists. Starting from the observation that high MHC-I expression was associated with higher densities of CD8+ T-cells,3 we further explored the TME characteristics of MHC-I SCLC cases.ResultsBeyond higher densities of CD8+ cytotoxic T-cells, we observed higher densities of FOXP3+ regulatory T-cells, and ICOS+ T-cells in the tumor center of MHC-I high cases. Considering the role of MHC-I in antigen presentation and T-cell activation, we investigated the proportion of CD8;PD-1;Ki67+ T-cells out of all CD8+ cells. Of note, we observed a compelling association of a high proportion of CD8;PD-1;Ki67+ T-cells with high MHC-I. This effect was particularly prominent in the tumor parenchyma and absent in the stroma, revealing an association with functionally relevant presentation of tumor antigens by MHC-I on SCLC tumor cells. Interestingly, we did not observe alterations in other immune cell populations like myeloid dendritic cells, macrophages, and granulocytes.ConclusionsWe utilized computational pathology to comprehensively profile the composition and spatial arrangement of the TME in inflamed SCLC cases defined by high MHC-I expression. Our findings provide the functional rationale for MHC-I as a biomarker for a potentially increased response to IO therapies.4 ReferencesGay CM, Stewart CA, Park EM, Diao L, Groves SM, Heeke S, Nabet BY, Fujimoto J, Solis LM, Lu W, Xi Y, Cardnell RJ, Wang Q, Fabbri G, Cargill KR, Vokes NI, Ramkumar K, Zhang B, Della Corte CM, Robson P, Swisher SG, Roth JA, Glisson BS, Shames DS, Wistuba II, Wang J, Quaranta V, Minna J, Heymach JV, Byers LA. Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities. Cancer Cell. 2021 Mar 8;39(3):346–360.e7. doi: 10.1016/j.ccell.2020.12.014. Epub 2021 Jan 21. PMID: 33482121; PMCID: PMC8143037.Mahadevan NR, Knelson EH, Wolff JO, Vajdi A, Saigí M, Campisi M, Hong D, Thai TC, Piel B, Han S, Reinhold BB, Duke-Cohan JS, Poitras MJ, Taus LJ, Lizotte PH, Portell A, Quadros V, Santucci AD, Murayama T, Cañadas I, Kitajima S, Akitsu A, Fridrikh M, Watanabe H, Reardon B, Gokhale PC, Paweletz CP, Awad MM, Van Allen EM, Lako A, Wang XT, Chen B, Hong F, Sholl LM, Tolstorukov MY, Pfaff K, Jänne PA, Gjini E, Edwards R, Rodig S, Reinherz EL, Oser MG, Barbie DA. Intrinsic Immunogenicity of Small Cell Lung Carcinoma Revealed by Its Cellular Plasticity. Cancer Discov. 2021 Aug;11(8):1952–1969. doi: 10.1158/2159–8290.CD-20–0913. Epub 2021 Mar 11. PMID: 33707236; PMCID: PMC8338750.Vuko M, Xie M, Gavaldon MA, Segerer F, Spitzmueller A, Hessel H, Testori M, Zimmermann J, Surace M, Heininen-Brown M, Canales JR, Saran S, Angell H, Schmidt G, Sade H, Barrett C, Schick M, Fabbri G. 155 MHC class I antigen presentation is associated with an inflamed SCLC tumor microenvironment characterized by a higher density of cytotoxic T-cells in closer proximity to tumor cells. Journal for ImmunoTherapy of Cancer 2022;10:doi: 10.1136/jitc-2022-SITC2022.0155Rudin CM, Balli D, Lai WV, Richards AL, Nguyen E, Egger JV, Choudhury NJ, Sen T, Chow A, Poirier JT, Geese WJ, Hellmann MD, Forslund A. Clinical benefit from immunotherapy in patients with small cell lung cancer is associated with tumor capacity for antigen presentation. J Thorac Oncol. 2023 May 18:S1556–0864(23)00554–3. doi: 10.1016/j.jtho.2023.05.008. Epub ahead of print. PMID: 37210008.Ethics ApprovalAll samples from which data in this report were generated, were obtained from an internal repository. All protocols, amendments, and participant informed consent documents were approved by the appropriate institutional review boards.

BackgroundSmall cell lung cancer (SCLC) is generally known to exclude immune cells and durable responses to immunotherapies are rare. Only very few biomarkers to inform immuno-oncology (IO) treatments are established in clinical practice thus far. Recently, four major SCLC subtypes (SCLC-A, SCLC-N, SCLC-P and SCLC-I) were described. Whereas the first three are characterized by activation of specific transcription factors, the SCLC-I (inflamed) subtype is characterized by an inflamed gene signature, high expression of MHC class I (MHC-I) antigen presentation and shows the greatest benefit from addition of immunotherapy to chemotherapy treatment [1,2]. Importantly, MHC-I is epigenetically silenced in the vast majority of SCLC and the presence of MHC-I could serve as a biomarker for the identification of SCLC-I cases. [2]. Here, we aimed to assess the biology of MHC-I high SCLC cases to investigate its role as a biomarker to inform cancer immunotherapies.MethodsWe combined the power of artificial intelligence (AI)-driven computational pathology with multiplex immunofluorescence (mIF) to gain critical insight into the tumor microenvironment (TME) of SCLC. 125 SCLC formalin-fixed, paraffin-embedded tissue samples were stained with a mIF panel consisting of six markers: PanCK, CD8, CD68, PD-1, PD-L1, and Ki67. We assessed the phenotype and spatial location of each cell in the pathologist-annotated tumor center and within the AI-segmented stroma and tumor epithelium. Pathologists classified immunohistochemically stained MHC-I slides from the same tissue blocks as MHC-I high, medium, or low according to their H-scores (low: ≤30; medium: 31–139; high: ≥140). TME characteristics between those groups were compared.ResultsIn all measured regions, we found higher densities of CD8+ and particularly PD-1/CD8 double positive T-cells in the MHC-I high group. Moreover, we observed the highest proportion of PD-1 positivity among cytotoxic T-cells in the tumor epithelium of MHC-I high samples, which also showed a high density of PD-L1+ tumor cells. Average distance of PD-1+ T-cells to their nearest tumor cell was lowest in the MHC-I high group. In the same group, an average of 19.3% of tumor cells in the epithelium had at least one PD-1+ T-cell within a 50 µm radius, while in the MHC-I low group this average was only 8.9%.ConclusionsWe utilized cutting-edge computational pathology to establish MHC-I as orchestrator of the composition and spatial arrangement of an inflamed SCLC TME. Beyond that, our findings corroborate the role of MHC-I as a potential biomarker for inflamed SCLC cases, which benefit most from cancer immunotherapies.ReferencesGay CM, Stewart CA, Park EM, Diao L, Groves SM, Heeke S, Nabet BY, Fujimoto J, Solis LM, Lu W, Xi Y, Cardnell RJ, Wang Q, Fabbri G, Cargill KR, Vokes NI, Ramkumar K, Zhang B, Della Corte CM, Robson P, Swisher SG, Roth JA, Glisson BS, Shames DS, Wistuba II, Wang J, Quaranta V, Minna J, Heymach JV, Byers LA. Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities. Cancer Cell. 2021 Mar 8;39(3):346–360.e7. doi: 10.1016/j.ccell.2020.12.014. Epub 2021 Jan 21. PMID: 33482121; PMCID: PMC8143037.Mahadevan NR, Knelson EH, Wolff JO, Vajdi A, Saigí M, Campisi M, Hong D, Thai TC, Piel B, Han S, Reinhold BB, Duke-Cohan JS, Poitras MJ, Taus LJ, Lizotte PH, Portell A, Quadros V, Santucci AD, Murayama T, Cañadas I, Kitajima S, Akitsu A, Fridrikh M, Watanabe H, Reardon B, Gokhale PC, Paweletz CP, Awad MM, Van Allen EM, Lako A, Wang XT, Chen B, Hong F, Sholl LM, Tolstorukov MY, Pfaff K, Jänne PA, Gjini E, Edwards R, Rodig S, Reinherz EL, Oser MG, Barbie DA. Intrinsic Immunogenicity of Small Cell Lung Carcinoma Revealed by Its Cellular Plasticity. Cancer Discov. 2021 Aug;11(8):1952–1969. doi: 10.1158/2159-8290.CD-20-0913. Epub 2021 Mar 11. PMID: 33707236; PMCID: PMC8338750.Ethics ApprovalAll samples from which data in this report were generated, were obtained from an internal repository. All protocols, amendments, and participant informed consent documents were approved by the appropriate institutional review boards.