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Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

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.

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.

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 PARPinhibitor 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; logrank 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.

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.

Background

Immune checkpoint inhibitors (ICIs) have transformed lung cancer treatment, yet their effectiveness appears restricted to certain patient subsets. Current clinical stratification based on PD-L1 expression offers limited predictive value. Given the mechanism of action, directly detecting spatial 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 (PLA) to detect PD1–PD-L1 interactions in diagnostic tissue samples from 16 different cancer types, a tissue microarray from 352 surgically resected early-stage non-small cell lung cancer (NSCLC) patients, and finally diagnostic biopsies from 242 advanced NSCLC patients with and without ICI treatment. RNAseq analysis was used to identify potential resistance mechanisms.

Results

In the early-stage NSCLC, only about half of the cases with detectable PD-L1 and PD1 expression showed 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 NSCLC patients, higher PD1–PD-L1 interactions were linked to complete responses and longer survival, outperforming standard PD-L1 expression assays. Patients who, despite high PD1–PD-L1 interactions, did not respond to ICIs, showed 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 used to further immune checkpoints. Accordingly, our results indicate concerted ICI resistance mechanisms, highlighting a need for combination diagnostics and therapies.

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.

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 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 alpha/beta 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.

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) (¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) and Gallium-68 DOTATOC (⁶⁸Ga-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 ¹⁸F-FDG- and ⁶⁸Ga-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.