Purpose: Transcriptomic subtyping holds promise for personalized therapy in extensive-stage small cell lung cancer (ES-SCLC). In this study, we aimed to assess intratumoral transcriptomic subtype diversity and to identify biomarkers of long-term chemoimmunotherapy benefit in human ES-SCLC.Experimental Design: We analyzed tumor samples from 58 patients with ES-SCLC enrolled in two multicenter single-arm phase IIIb studies evaluating frontline chemoimmunotherapy in Spain: n = 32 from the IMfirst trial and n = 26 from the CANTABRICO trial. We used the GeoMx Digital Spatial Profiler system to perform multi-region transcriptomic analysis. For subtype classification, we performed hierarchical clustering using the relative expression of ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P), and YAP1 (SCLC-Y).Results: Subtype distribution was found to be similar between bothcohorts, except for SCLC-P, which was not identified in the CANTABRICO_DSP cohort. A total of 44% of the patients in both cohorts had tumors with multiple coexisting transcriptional subtypes. Transcriptional subtypes or subtype heterogeneity was not associated with outcomes. Most potential targets did not show subtype-specific expression. Consistently in both cohorts, tumors from patients with long-term benefit (time to progression ≥12 months) contained an IFNγ-dominated mRNA profile, including enhanced capacity for antigen presentation. Hypoxia and glycolytic pathways were associated with resistance to chemoimmunotherapy.Conclusions: This work suggests that intratumoral heterogeneity, inconsistent association with outcome, and unclear subtype-specific target expression might be significant challenges for subtype-based precision oncology in SCLC. Preexisting IFNγ-driven immunity and mitochondrial metabolism seem to be correlates of long-term efficacy in this study, although the absence of a chemotherapy control arm precludes concluding that these are predictive features specific for immunotherapy.

Aims To study programmed death ligand 1 (PD-L1) expression and tumour infiltrating lymphocytes (TILs) in patients with early-stage non-small cell lung carcinoma (NSCLC) with artificial intelligence (AI) algorithms. Methods The study included samples from 50 early-stage NSCLCs. PD-L1 immunohistochemistry (IHC) stained slides (clone SP263) were scored manually and with two different AI tools (PathAI and Navify Digital Pathology) by three pathologists. TILs were digitally assessed on H&E and CD8 IHC stained sections with two different algorithms (PathAI and Navify Digital Pathology, respectively). The agreement between observers and methods for each biomarker was analysed. For PD-L1, the turn-around time (TAT) for manual versus AI-assisted scoring was recorded. Results Agreement was higher in tumours with low PD-L1 expression regardless of the approach. Both AI-powered tools identified a significantly higher number of cases equal or above 1% PD-L1 tumour proportion score as compared with manual scoring (p=0.00015), a finding with potential therapeutic implications. Regarding TAT, there were significant differences between manual scoring and AI use (p value <0.0001 for all comparisons). The total TILs density with the PathAI algorithm and the total density of CD8+ cells with the Navify Digital Pathology software were significantly correlated (τ=0.49 (95% CI 0.37, 0.61), p value<0.0001). Conclusions This preliminary study supports the use of AI algorithms for the scoring of PD-L1 and TILs in patients with NSCLC.

Malignant fibrous histiocytoma is an aggressive tumor, the most common soft-tissue sarcoma of adult age. It is usually located in the extremities and retroperitoneum, and very rarely there is skeletal involvement. Surgery is the preferred treatment in early disease; in advanced disease, chemotherapy is the main therapeutic strategy. We present a 25-year-old female patient diagnosed with a vertebral mass in T5 with a severely compromised spinal cord. She underwent surgical decompression and the pathological findings were consistent with malignant fibrous histiocytoma. After several surgical treatments she had pulmonary progression and was therefore started on chemotherapy. She had a very poor response to most of the administered regimens until she initiated trabectedin 1 mg/m² every three weeks. She showed a significant improvement with a major response of the lung metastases. This report indicates that trabectedin is an active drug in advanced, previously treated metastatic malignant fibrous histiocytoma.

Background/Objectives: The non-small-cell lung cancer (NSCLC) therapeutic landscape has undergone a profound transformation with the introduction of multiple personalized treatment options. Mutations in ERBB2 (HER2) have recently emerged as promising novel targets for the treatment of non-squamous NSCLC (nsNSCLC). Accurate, rapid, and efficient molecular profiling is crucial for identifying patients who may benefit from targeted therapies, including HER2-directed agents. Materials and Methods: Here, we aimed to retrospectively assess the performance of the Oncomine™ Precision Assay* (OPA) in combination with the Ion Torrent Genexus™ Integrated Sequencer* (Thermo Fisher Scientific. Waltham, MA, USA) for detecting ERBB2 mutations in nsNSCLC. A total of 108 archived nsNSCLC samples, consisting of biopsies, resections, and cytological specimens, were used to assess concordance with in-house-validated orthogonal tests. Results: The OPA showed high sensitivity and specificity with an overall accuracy of 100% for single-nucleotide variants (SNVs) and insertions and deletions (Indels). SNVs and Indels with allele frequencies as low as 5% were correctly identified across samples with a tumor cell content ranging from 5% to 95%. Additionally, the assay demonstrated high reproducibility across the six participating laboratories. The turnaround time of the OPA was notably shorter compared to traditional orthogonal methods, facilitating rapid molecular report generation. Conclusions: The OPA in combination with the Ion Torrent Genexus™ System allows for highly sensitive and specific detection of relevant ERBB2 mutations. The assay’s streamlined workflow, coupled with its automated data analysis pipeline, enables a fast turnaround time for testing across a range of sample types. This includes samples with reduced tumor cell content and limited available input. This study demonstrates the future potential of using this assay in a clinical setting.