Abstract Immune infiltration shapes anti-tumor responses and is associated with patient outcomes. Yet, comprehensive studies comparing infiltration patterns and their clinical impact across cancer types are scarce.We profiled the tumor immune microenvironment across 16 solid tumor types from more than 2,700 patients using multiplex immunofluorescence with pathologist-curated image analysis to quantify major lymphoid and myeloid subsets and their spatial organization in situ.Across all cancer types, lung, endometrial, and high-grade serous ovarian cancers were highly infiltrated, whereas prostate and ER-positive breast cancers were comparatively “immune cold”. Cancer-agnostic consensus clustering resolved four reproducible immune archetypes with distinct outcomes, including an immune-hot group enriched for CD4, CD8, and B cells that associated with the best survival (p<0.001). Notably, the tumor type accounted for only a part of the immune contexture, as most cancers spanned multiple immune signature groups. Nevertheless, a machine-learning classifier trained on immune compositions distinguished tumor types with high accuracy (AUC = 0.96), confirming that each cancer maintains a recognizable immune imprint even among pan-cancer archetypes.Analysis of survival associations of individual cell classes revealed a rare CD8+FOXP3+ T-cell phenotype that emerged as a strongest positive prognostic factor across cancers (HR=0.79, 95%CI:[0.70-0.89], p=0.002). Single-cell RNA sequencing data indicated that CD8+FoxP3+ cells exhibit two distinct gene programs, with regulatory and cytotoxic capacities. Spatial mapping suggested context-dependency in the function of CD8+FoxP3+ cells, as their proximity to CD8 T cells was linked to better survival (enrichment at 10um: HR=0.76, 95%CI:[0.67-0.90], p=0.0006), whereas proximity to tumor cells was associated with worse prognosis (enrichment at 10um: HR=1.29, 95%CI:[1.12-1.49], p=0.0005).Together, our findings define pan-cancer immune archetypes that are both shared and disease-specific, explaining why “immune hot” and “cold” states are not synonymous with pure infiltration quantities. We identified CD8+FoxP3+ immune cells as a cell type with strong biomarker potential independent of cancer type. Citation Format: Artur Mezheyeuski, Emma Sandberg, Max Backman, Ali Teymur Kahraman, Amanda Lindberg, Carina Strell, Hans Brunnström, Jutta Huvila, Malin Sund, Fredrik Wärnberg, Bengt Glimelius, Ina Hrynchyk, Siarhei Mauchanski, Salome Khelashvili, Klara Hammarström, Margret Agnarsdottir, Gemma Garcia-Vicién, DAVID G. MOLLEVI, Aine O´Reilly, Sara Corvigno, Hanna Dahlstrand, Johan Botling, Ulrika Segersten, Agnieszka Krzyzanowska, Anders Bjartell, Jacob Elebro, Margareta Heby, Sebastian Lundgren, Charlotta Hedner, David Borg, Jenny Brändstedt, Hanna Sartor, Per-Uno Malmström, Martin Johansson, Anna Portyanko, Björn Nodin, Cecilia Lindskog, Karin Leandersson, Karin Jirström, Tobias Sjöblom, Patrick Micke. Tumor-agnostic analysis identified pan-cancer immune archetypes and CD8+FoxP3+ cells as novel in situ predictors of survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 193.

BACKGROUND:Non-small cell lung cancer (NSCLC) is a heterogenous disease with challenging prognosis despite clinical improvements in the last years. The tumor-microenvironment (TME) is a major factor with many cell types involved as well as distinct spatial organization. We assessed the global immune landscape and spatial architecture of excluded immune cell types within the stroma of NSCLC tissues. METHODS:Multiplex Immunofluorescence (mIF) staining was used to detect major immune cell lineages in tissues of 674 NSCLC patients. AI-based digital image analyses were conducted to stratify NSCLC tissues into stroma and tumor compartments as well as identify and classify single cells based on mIF marker combinations into major immune cell phenotypes. Quantitative single-cell resolved immune cell phenotypes within the stroma area were used to cluster patients based on their excluded immune signature and spatial architecture and explored for impact on overall-survival. RESULTS:NSCLC stroma harbored distinct immune cell as well as spatial organizational patterns with varying combinations. Among these, a mixed immune landscape together with a stromal organization dominated by long distances to B cells and short distances to Helper T cells was associated with long-term overall-survival. This was successfully reduced to a two-variable signature comprising three different cell types, where short distances of Helper T cells to Regulatory T cells in conjunction with high B cell densities provided superior prognostic value. CONCLUSIONS:The excluded immune cells within the stromal compartment are associated with strong prognostic effects based on their spatial architecture and represent a previously underappreciated cell population.

Increased stromal Platelet-derived growth factor receptor beta (PDGFRβ) expression is a hallmark of the desmoplastic tissue reaction in cancer and marks subsets of cancer-associated fibroblasts, pericytes, and smooth muscle cells. However, its functional status in situ has been anticipated from static expression measures, which cannot determine whether high receptor abundance reflects active signaling. We established two second-generation proximity ligation assays (PLAs) to quantify PDGFRβ activation in the in situ environment of human lung cancer by detecting either phosphorylated PDGFRβ or its interaction with the adaptor protein Grb2. The immunofluorescence-based assays were applied to tissue-microarrays including diagnostic samples from over 600 non-small cell lung cancer (NSCLC) patients. In lung cancer tissue, activation scores correlated with PDGFRβ expression but revealed a more nuanced receptor status, indicating variable activation despite similar expression levels. Higher PDGFRβ activation was associated with increased recurrence risk exclusively in squamous cell carcinoma, a finding not captured by conventional immunohistochemistry. This activation was accompanied by a specific stromal profile enriched for LRRC15- and FAP-positive cells, a pattern absent in adenocarcinomas. PDGFRβ activation status provides functional information beyond receptor expression, uncovering clinically relevant, otherwise overlooked, stromal phenotypes. The approach illustrates the diagnostic potential of functional protein assays in the era of precision medicine.

The mechanisms underlying how adrenocortical carcinoma (ACC) progresses into a metastatic and lethal disease remain poorly understood. To address this, we performed comprehensive genomic analyses to delineate the evolutionary trajectory of advanced ACC. Fresh frozen tumour samples (n = 29) were obtained from nine patients, all of whom had matched primary and relapse specimens, including recurrent (n = 4) and metastatic (n = 11) lesions. In four patients, multiple primary and metastatic samples were available, enabling detailed evolutionary comparisons. All tumours underwent whole-genome sequencing, RNA sequencing, and DNA methylation profiling. Our analyses revealed that seven of nine patients exhibited global loss of heterozygosity (LOH) often followed by whole-genome doubling, resulting in copy-neutral LOH. SNP-based analyses indicated that these alterations occurred as a single catastrophic event that was conserved across all matched samples within each patient, suggesting that this event constitutes a truncal feature of the evolutionary tree. These results support a model in which chromosomal aneuploidy is important in ACC tumourigenesis, potentially distinguishing carcinomas from benign adrenal adenomas. This may explain the rarity of adenoma-to-carcinoma transformation and suggest a diagnostic and therapeutic relevance of chromosomal instability in ACC.

Leaky blood vessels are a hallmark of solid tumors. However, the molecular mechanisms and clinical implications of vascular leakage in human cancer remain unexplored. Here, we identified fibrinopeptide-A (FpA) as a robust in-situ marker of vascular leakage, analyzing diagnostic specimens from two non-small cell lung cancer (NSCLC) cohorts (N = 327 and N = 200). Mechanistically, FpA+ staining localized to discrete stromal niches characterized by increased endothelial VEGF receptor-2 phosphorylation, elevated VEGFA production by tumor cells and loss of the endothelial tyrosine phosphatase PTPRB. Immune profiling revealed reduced density of mature dendritic cells and granzyme B-expressing cytotoxic T cells in tumors with high-leakage. This leakage-associated immunosuppression was linked to the presence of tertiary lymphoid structures (TLS) in lung adenocarcinoma (LUAD). However, compared to low-leakage, TLS in high-leakage tumors were enriched in regulatory T cells and conferred no survival advantage. Patients with high vascular leakage exhibited a reduced overall survival. Moreover, in a separate immunotherapy cohort (N = 64), high-leakage was associated with poor response to anti-PD-1/PD-L1 treatment. This study establishes vascular leakage as an important prognostic factor in NSCLC, and provides mechanistic understanding and a methodological framework to stratify NSCLC patients with regard to responsiveness to immunotherapy.

The biology of metastatic pancreatic neuroendocrine tumors (panNET) may alter over time. It remains to be defined if, how, and when this patient group should be recommended to re‐evaluate the characteristics of their disease. This prospective single‐center, longitudinal cohort study at Uppsala University Hospital, Sweden (NCT03130205), included metastatic panNET patients with progressive disease to participate in a standardized re‐characterization protocol: clinical and biochemical analyses, core‐needle biopsy, and dual‐positron emission tomography/computed tomography (PET/CT) ( 18 F‐fluorodeoxyglucose ( 18 F‐FDG) and Gallium‐68 DOTATOC ( 68 Ga‐DOTATOC)) with NETPET score assessments. At further disease progression, a second re‐characterization was offered. The proportion of patients with a clinically significant change is reported and defined as information that could lead to a change in the therapeutic algorithm proposed in the European Neuroendocrine Tumor Society (ENETS) guidelines. Between 2017 and 2021, 21 patients with progressive metastatic panNETs were included. Before inclusion, 19 tumors were grade (G) 1 or 2, and two were G3. Sixteen patients underwent biopsy with collection of adequate tumor material, of whom 81.3% ( n = 13/16) displayed an increase in the Ki‐67 index, with transition from G2 to G3 in 50% ( n = 8/16). Twelve and 15 patients were positive on 18 F‐FDG‐ and 68 Ga‐DOTATOC‐positron emission tomography (PET), respectively. This corresponded to NETPET grades P1 ( n = 2), P2b ( n = 12), and P3b ( n = 1). A clinically significant change was noted among 62% ( n = 13/21) of patients at first re‐characterization, leading to therapy change in 7 positron emission tomography/computed tomography (PET/CT) patients. After the second re‐characterization, a significant clinical change occurred in 43% ( n = 3/7) with a shift in therapy for one patient. This study shows that a considerable number of progressive metastatic panNETs experience significant changes in their disease characteristics over time. This may result in a revised treatment plan and highlights the need to re‐evaluate all relevant aspects of panNET disease. Such comprehensive re‐characterization is particularly crucial in the context of clinical trial inclusion.

BackgroundTumour-infiltrating T cells can mediate both antitumour immunity and promote tumour progression by creating an immunosuppressive environment. This dual role is especially relevant in hepatocellular carcinoma (HCC), characterised by a unique microenvironment and limited success with current immunotherapy.ObjectiveWe evaluated T cell responses in patients with advanced HCC by analysing tumours, liver flushes and liver-draining lymph nodes, to understand whether reactive T cell populations could be identified despite the immunosuppressive environment.DesignT cells isolated from clinical samples were tested for reactivity against predicted neoantigens. Single-cell RNA sequencing was employed to evaluate the transcriptomic and proteomic profiles of antigen-experienced T cells. Neoantigen-reactive T cells expressing 4-1BB were isolated and characterised through T-cell receptor (TCR)-sequencing.ResultsBioinformatic analysis identified 542 candidate neoantigens from seven patients. Of these, 78 neoantigens, along with 11 hotspot targets from HCC driver oncogenes, were selected for ex vivo T cell stimulation. Reactivity was confirmed in co-culture assays for 14 targets, with most reactive T cells derived from liver flushes and lymph nodes. Liver flush-derived T cells exhibited central memory and effector memory CD4+ with cytotoxic effector profiles. In contrast, tissue-resident memory CD4+ and CD8+ T cells with an exhausted profile were primarily identified in the draining lymph nodes.ConclusionThese findings offer valuable insights into the functional profiles of neoantigen-reactive T cells within and surrounding the HCC microenvironment. T cells isolated from liver flushes and tumour-draining lymph nodes may serve as a promising source of reactive T cells and TCRs for further use in immunotherapy for HCC.

INTRODUCTION:Many studies have aimed at identifying additional prognostic tools to guide treatment choices and patient surveillance in lung cancer by assessing the expression of individual proteins through immunohistochemistry (IHC) or, more recently, through gene expression-based signatures. As a proof-of-concept, we used a multi-cohort, gene expression-based discovery and validation strategy to identify genes with prognostic potential in lung adenocarcinoma. The clinical applicability of this strategy was further assessed by evaluating a selection of the markers by IHC. MATERIALS AND METHODS:Publicly available gene expression data sets from six microarray-based studies were divided into four discovery and two validation data sets. First, genes associated with overall survival (OS) in all four discovery data sets were identified. The prognostic potential of each identified gene was then assessed in the two validation data sets, and genes associated with OS in both data sets were considered as potential prognostic markers. Finally, IHC for selected potential prognostic markers was performed in two independent and clinically well-characterized lung cancer cohorts. RESULTS AND CONCLUSIONS:The gene expression-based strategy identified 19 genes with correlation to OS in all six data sets. Out of these genes, we selected Ki67, MCM4 and TYMS for further assessment with IHC. Although an independent prognostic ability of the selected markers could not be confirmed by IHC, this proof-of-concept study demonstrates that by employing a gene expression-based discovery and validation strategy, potential prognostic markers can be identified and further assessed by a technique universally applicable in the clinical practice. The concept of studying potential prognostic markers through gene expression-based strategies, with a subsequent evaluation of the clinical utility, warrants further exploration.

T-cell activation and clonal expansion are essential for the efficacy of immunotherapy in non-small cell lung cancer (NSCLC) patients. Since the distribution of T-cell clones might provide insights into immunogenic mechanisms, we determined the α/β TCR clonality using RNA-sequencing from frozen tumor tissue of 182 NSCLC patients and paired the results with extensive in situ image and sequence analyses of the immune microenvironment of NSCLC. TCR clonality (Gini index) patterns ranged from high T-cell clone diversity with high evenness (Gini index low) to clonal dominance with low evenness (Gini index high). TCR clonality in cancer tissue was lower than in matched normal lung (p=0.021). High Gini index correlated strongly with distinct mutations (EGFR, P53), tumor mutation burden (p<0.001), and inflamed tumor phenotypes (PRF1, GZMA, GZMB, INFG) with exhaustion signatures (LAG3, TIGIT, IDO1, PD-1, PD-L1). Correspondingly, PD-1+, CD3+, CD8A+, CD163+, and CD138+ immune cells infiltrated cancer tissue with high TCR clonality. In situ sequencing revealed that dominant T-cell clones were more often of CD8-subtype and tended to approximate the tumor cell compartment (p<0.03). In a checkpoint inhibitor-treated NSCLC patient cohort, high TCR clonality was associated with therapy response (p=0.016) and prolonged survival (p=0.003, median survival 13.8 vs 2.9 months). Our robust analysis pipeline revealed diverse TCR repertoires related to genotypes and immune phenotypes. The in situ positioning of expanded T-cell clones indicated functional impact, which was clinically confirmed in NSCLC patients receiving immunotherapy. ### Competing Interest Statement The authors have declared no competing interest.

INTRODUCTION:Tertiary lymphoid structures (TLS) are lymphocyte aggregates resembling secondary lymphoid organs and are pivotal in cancer immunity. The ambiguous morphological definition of TLS makes it challenging to ascertain their clinical impact on patient survival and response to immunotherapy. OBJECTIVES:This study aimed to characterize TLS in hematoxylin-eosin tissue sections from lung cancer patients, assessing their occurrence in relation to the local immune environment, mutational background, and patient outcome. METHODS:Two pathologists evaluated one whole tissue section from resection specimens of 680 NSCLC patients. TLS were spatially quantified within the tumor area or periphery and further categorized based on the presence of germinal centers (mature TLS). Metrics were integrated with immune cell counts, genomic and transcriptomic data, and correlated with clinical parameters. RESULTS:TLS were present in 86% of 536 evaluable cases, predominantly in the tumor periphery, with a median of eight TLS per case. Mature TLS were found in 24% of cases. TLS presence correlated positively with increased plasma cell (CD138+) and lymphocytic cell (CD3+, CD8+, FOXP3+) infiltration. Tumors with higher tumor mutational burden exhibited higher numbers of peripheral TLS. The overall TLS quantity was independently associated with improved patient survival, irrespective of TLS maturation status. This prognostic association held true for peripheral TLS but not for tumor TLS. CONCLUSION:TLS in NSCLC is common and their correlation with a specific immune phenotype suggests biological relevance in the local immune reaction. The prognostic significance of this scoring system on routine hematoxylin-eosin sections has the potential to augment diagnostic algorithms for NSCLC patients.

Background:Chemoradiotherapy (CRT) is regarded as the treatment of choice for inoperable stage III non-small cell lung cancer (NSCLC) patients. Despite the curative intent, recurrence is frequent, and overall prognosis is poor. Thus, there is a need for clinical biomarkers to better predict outcome and to optimize treatment and follow-up. The aim of this study was to characterize a large cohort of real-world stage III NSCLC patients who received CRT with curative intent and to define parameters that could predict recurrence patterns, overall survival (OS) and survival time from recurrence. Methods:This study is based on a cohort of 193 stage III NSCLC patients receiving CRT with curative intent in mid-Sweden during the years 2009-2018. Data was retrospectively collected from medical records. Clinical parameters, recurrence patterns, salvage treatment, histological and molecular data were analyzed and correlated to outcome. Results:Median follow-up was 52 months, with a median OS of 33 months. Most patients (66%) progressed, commonly within the first 3 years following CRT. Performance status and common blood markers at recurrence were associated with worse survival. The presence of driver mutations [epidermal growth factor receptor (EGFR), Kirsten rat sarcoma viral oncogene homolog (KRAS)] or metastatic spread to N3 lymph nodes increased the risk of distant recurrence. Immunotherapy as salvage treatment was associated with a significantly better prognosis. Conclusions:Routine diagnostic parameters can be used to predict survival and recurrence patterns in patients receiving curative CRT. Additionally, salvage treatment with immunotherapy was the strongest factor associated with longer survival after disease recurrence.

Background T-cell activation and clonal expansion are essential to effective immunotherapy responses in non-small cell lung cancer (NSCLC). The distribution of T-cell clones may offer insights into immunogenic mechanisms and imply potential prognostic and predictive information.Methods We analyzed α/β T-cell receptor (TCR) clonality using RNA-sequencing of bulk frozen tumor tissue from 182 patients with NSCLC. The data was integrated with molecular and clinical characteristics, extensive in situ imaging, and spatial sequencing of the tumor immune microenvironment. TCR clonality was also determined in an independent cohort of nine patients with immune checkpoint-treated NSCLC.Results TCR clonality (Gini index) patterns ranged from high T-cell clone diversity with high evenness (low Gini index) to clonal dominance with low evenness (high Gini index). Generally, TCR clonality in cancer was lower than in matched normal lung parenchyma distant from the tumor (p=0.021). The TCR clonality distribution between adenocarcinoma and squamous cell carcinoma was similar; however, smokers showed a higher Gini index. While in the operated patient with NSCLC cohort, TCR clonality was not prognostic, in an immune checkpoint inhibitor-treated cohort, high TCR clonality was associated with better therapy response (p=0.016) and prolonged survival (p=0.003, median survival 13.8 vs 2.9 months). On the genomic level, a higher Gini index correlated strongly with a lower frequency of epidermal growth factor receptor (EGFR) and adenomatous polypsis coli (APC) gene mutations, but a higher frequency of P53 mutations, and a higher tumor mutation burden. In-depth characterization of the tumor tissue revealed that high TCR clonality was associated with an activated, inflamed tumor phenotype (PRF1, GZMA, GZMB, INFG) with exhaustion signatures (LAG3, TIGIT, IDO1, PD-1, PD-L1). Correspondingly, PD-1+, CD3+, CD8A+, CD163+, and CD138+immune cells infiltrated cancer tissue with high TCR clonality. In situ sequencing recovered single dominant T-cell clones within the patient tumor tissue, which were predominantly of the CD8 subtype and localized closer to tumor cells.Conclusion Our robust analysis pipeline characterized diverse TCR repertoires linked to distinct genotypes and immunologic tumor phenotypes. The spatial clustering of expanded T-cell clones and their association with immunological activation underscores a functional, clinically relevant immune response, particularly in patients with NSCLC treated with checkpoint inhibitors.

Background: Precision cancer medicine (PCM) is key to advancing cancer treatment beyond the standard of care. We performed an explorative clinical trial, MEGALiT, to investigate the feasibility, safety, and clinical benefit of genomics-based PCM in advanced cancer. Methods: MEGALiT recruited adult patients with advanced solid tumors refractory to standard treatment. Tumor DNA from newly acquired biopsies or ctDNA were analyzed for alterations targetable with the PD-L1 inhibitor atezolizumab, the MEK inhibitor cobimetinib, the mTOR inhibitor everolimus, or the PARP-inhibitor niraparib. Any other ‘in study’ treatment was left to the discretion of the physician. Results: Outcome data are reported for 153 patients. The median age was 65 years and the most common diagnoses were colorectal, prostate, and ovarian cancer. The median time from study inclusion to the Molecular Tumor Board was 35 days for tumor sampling by biopsy and 21 days by ctDNA. Of the 44 patients allocated to a study drug, 38 started treatment. The median follow-up was 1.9 years. Of the patients on a study drug and evaluable for tumor response, 6% (2/32) had partial remission, and 25% (8/32) had disease control at 16 weeks. Median overall survival for patients starting a study drug was longer, 7.4 months, compared to 2.7 months for the 61 untreated patients (HR 0.43; log-rank p < 0.0001), but shorter than for the 50 patients receiving treatment of physician’s choice, 11.8 months (HR 0.55; log-rank p = 0.012). No significant procedure- or drug-related severe adverse events were observed. Interpretation: Genomics-guided treatment selection in advanced cancer is feasible and safe. However, evidence of patient benefit warrants further investigation.

For patients with advanced stage non-small cell lung cancer (NSCLC), treatment strategies have changed significantly due to the introduction of targeted therapies and immunotherapy. In the last few years, we have seen an explosive growth of newly introduced targeted therapies in oncology and this development is expected to continue in the future. Besides primary targetable aberrations, emerging diagnostic biomarkers also include relevant co-occurring mutations and resistance mechanisms involved in disease progression, that have impact on optimal treatment management. To accommodate testing of pending biomarkers, it is necessary to establish routine large-panel next-generation sequencing (NGS) for all patients with advanced stage NSCLC. For cost-effectiveness and accessibility, it is recommended to implement predictive molecular testing using large-panel NGS in a dedicated, centralized expert laboratory within a regional oncology network. The central molecular testing center should host a regional Molecular Tumor Board and function as a hub for interpretation of rare and complex testing results and clinical decision-making.

Abstract Background: Immune checkpoint therapies (ICT) are now widely introduced in clinical oncology and most often guided by PDL1 expression in diagnostic biopsies. However, the predictive value of this testing is only modest, leading to over- and undertreatment. Conceptually, the prevention of binding of ligand PDL1 to PD1 receptor is decisive for the efficacy of ICT. Therefore, directly detecting the spatial PD1-PDL1 interaction would provide more predictive information. Methods: A second-generation in situ proximity ligation assay (isPLA; Navinci Diagnostics) was established to detect PD1-PD-L1 interactions in diagnostic patient samples and linked to an automated analysis pipeline (QuPath). For basic validation, we used pan-cancer tissue microarrays (TMA) including 16 solid tumor types, and a non-small cell lung cancer (NSCLC) TMA (359 ICT-naïve surgically treated patients). In addition, we analyzed diagnostic tissue biopsies from 75 advanced NSCLC patients treated with anti-PD1-PDL1 regiments. Results: The pan-cancer analysis revealed varying levels of PD1-PDL1 interaction among the solid cancer types, with the lowest levels detected in liver cancer and the highest in testicular cancer. A general positive association was observed between the literature-reported objective ICT response rate (ORR) per tumor type and its corresponding PD1-PDL1 interaction status. Conventional immunohistochemical analysis of the ICT-naïve, surgically treated NSCLC cohort revealed variable protein expression level for both, PDL1 and PD1, for 200 cases, but only 108 (54%) of them demonstrated a detectable PD1-PDL1 interaction with our isPLA assay. EGFR mutated cases showed generally lower PD1-PDL1 interaction scores (p=0.01). PD1-PDL1 interaction was not associated with survival (p=0.46). A subsequent analysis of the ICT-NSCLC cohort revealed a significant positive association between PD1-PDL1 interaction status and prolonged overall survival upon ICT (median survival 14.8 vs 32.3 months; p=0.022). The standard tumor proportional score (TPS) of membranous PDL1 expression did not correlate with ICT-specific survival (p=0.40). Conclusions: The second generation isPLA successfully distinguishes a previously difficult-to-define patient subset with positive PD1-PDL1 interaction status. Our data suggest that the PD1-PDL1 interaction is a superior clinical biomarker for patient selection for ICT in NSCLC. The interaction analysis is applicable to sections from minute diagnostics biopsies and accessible by light microscopy either semi-quantitatively by a pathologist or by an automated image analysis program. Thus, the assay holds great potential to be integrated into routine clinical pathological workflow to stratify cancer patients for ICT. Citation Format: Patrick Micke, Amanda Lindberg, Rebecca Artursson, Louise Hellberg, Hui Yu, Max Backman, Johan Botling, Hans Brunnström, Artur Mezheyeuski, Johan Isaksson, Carina Strell. PD1-PDL1 interaction as a superior predictor for response to immune checkpoint therapy in NSCLC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5139.

Tumour evolution with acquisition of more aggressive disease characteristics is a hallmark of disseminated cancer. Metastatic pancreatic neuroendocrine tumours (PanNETs) in particular, show frequent progression from a low/intermediate to a high-grade disease. To understand the molecular mechanisms underlying this phenomenon, we performed multi-omics analysis of 32 longitudinal samples from six metastatic PanNET patients. Following MEN1 inactivation, PanNETs exhibit genetic heterogeneity on both spatial and temporal dimensions with parallel and convergent tumuor evolution involving the ATRX/DAXX and mTOR pathways. Following alkylating chemotherapy treatment, some PanNETs develop mismatch repair deficiency and acquire a hypermutator phenotype. This DNA hypermutation phenotype was only found in cases that also showed transformation into a high-grade PanNET. Overall, our findings contribute to broaden the understanding of metastatic PanNET, and suggests that therapy driven disease evolution is an important hallmark of this disease.

INTRODUCTION:Immune checkpoint inhibitors (ICIs) have transformed lung cancer treatment, yet their effectiveness seem restricted to certain patient subsets. Current clinical stratification on the basis of programmed death ligand 1 (PD-L1) expression offers limited predictive value. Given the mechanism of action, directly detecting spatial programmed cell death protein 1 (PD1)-PD-L1 interactions might yield more precise insights into immune responses and treatment outcomes. METHODS:We applied a second-generation in situ proximity ligation assay to detect PD1-PD-L1 interactions in diagnostic tissue samples from 16 different cancer types, a tissue microarray with surgically resected early-stage NSCLC, and finally diagnostic biopsies from 140 patients with advanced NSCLC with and without ICI treatment. RNA sequencing analysis was used to identify potential resistance mechanisms. RESULTS:In the early-stage NSCLC, only approximately half of the cases with detectable PD-L1 and PD1 expression exhibited PD1-PD-L1 interactions, with significantly lower levels in EGFR-mutated tumors. Interaction levels varied across cancer types, aligning with reported ICI response rates. In ICI-treated patients with NSCLC, higher PD1-PD-L1 interactions were linked to complete responses and longer survival, outperforming standard PD-L1 expression assays. Patients who did not respond to ICIs despite high PD1-PD-L1 interactions exhibited additional expression of stromal immune mediators (EOMES, HAVCR1/TIM-1, JAML, FCRL1). CONCLUSION:Our study proposes a diagnostic shift from static biomarker quantification to assessing active immune pathways, providing more precise ICI treatment. This functional concept applies to tiny lung biopsies and can be extended to further immune checkpoints. Accordingly, our results indicate concerted ICI resistance mechanisms, highlighting the need for combination diagnostics and therapies.

In the past two decades, the treatment of metastatic non-small cell lung cancer (NSCLC), has undergone significant changes due to the introduction of targeted therapies and immunotherapy. These advancements have led to the need for predictive molecular tests to identify patients eligible for targeted therapy. This review provides an overview of the development and current application of targeted therapies and predictive biomarker testing in European patients with advanced stage NSCLC. Using data from eleven European countries, we conclude that recommendations for predictive testing are incorporated in national guidelines across Europe, although there are differences in their comprehensiveness. Moreover, the availability of recently EMA-approved targeted therapies varies between European countries. Unfortunately, routine assessment of national/regional molecular testing rates is limited. As a result, it remains uncertain which proportion of patients with metastatic NSCLC in Europe receive adequate predictive biomarker testing. Lastly, Molecular Tumor Boards (MTBs) for discussion of molecular test results are widely implemented, but national guidelines for their composition and functioning are lacking. The establishment of MTB guidelines can provide a framework for interpreting rare or complex mutations, facilitating appropriate treatment decision-making, and ensuring quality control.