OBJECTIVE: To investigate the association between human leukocyte antigen (HLA) and paraneoplastic neurological syndromes (PNS) with Hu antibodies, and potential specificities according to clinical presentation and cancer status.
METHODS: HLA genotypes at four-digit resolution were imputed from available genome-wide association data. Allele carrier frequencies were compared between patients (whole cohort, n = 100, and according to clinical presentation and cancer status) and matched healthy controls (n = 508) using logistic regression controlled by the three main principal components.
RESULTS: The clinical presentation of 100 anti-Hu patients involved the central nervous system (28, 28%), the peripheral nervous system (36, 36%) or both combined (36, 36%). Cancer diagnosis was certain in 75 (75%). HLA association analyses revealed that anti-Hu PNS patients were more frequently carriers of DQA1*05:01 (39% vs. 19%, OR = 2.8 [1.74-4.49]), DQB1*02:01 (39% vs. 18%, OR = 2.88 [1.79-4.64]) and DRB1*03:01 (41% vs. 19%, OR = 2.92 [1.80-4.73]) than healthy controls. Remarkably, such DR3 ~ DQ2 association was absent in patients with pure central involvement, but more specific to those manifesting with peripheral involvement: DQA1*05:01 (OR = 3.12 [1.48-6.60]), DQB1*02:01 (OR = 3.35 [1.57-7.15]) and DRB1*03:01 (OR = 3.62 [1.64-7.97]); being even stronger in cases with sensory neuropathy, DQA1*05:01 (OR = 4.41 [1.89-10.33]), DQB1*02:01 (OR = 4.85 [2.04-11.53]) and DRB1*03:01 (OR = 5.79 [2.28-14.74]). Similarly, DR3 ~ DQ2 association was only observed in patients with cancer.
CONCLUSIONS: Patients with anti-Hu PNS show different HLA profiles according to clinical presentation and, probably, cancer status, suggesting pathophysiological differences.

UNASSIGNED: The Geriatric Nutritional Risk Index (GNRI) indicates nutritional status based on serum albumin concentration and ideal body weight. Pretreatment GNRI has been suggested as a prognostic factor for various malignancies. However, little is known about the clinical value of GNRI for small-cell lung cancer (SCLC), especially in elderly patients.
UNASSIGNED: We retrospectively analyzed 53 elderly (≥71) patients with extensive-disease (ED) SCLC treated with first-line platinum-doublet chemotherapy in relation to the pretreatment GNRI level in a real-world setting.
UNASSIGNED: Thirty-six patients with a low GNRI (<92) had statistically poorer progression-free survival (PFS) and overall survival (OS) than 17 patients with a high GNRI (≥92) (median PFS=80 days vs. 133 days, respectively; p=0.002; median OS=123 days vs. 274 days, respectively; p=0.004). In a multivariate analysis, a low GNRI was also an independent poor prognostic factor for PFS [hazard ratio (HR)=0.396; 95% confidence interval (CI)=0.199-0.789; p=0.008] and OS (HR=0.295; 95%CI=0.143-0.608; p<0.001).
UNASSIGNED: The GNRI might be a predictive and prognostic marker in elderly patients with ED-SCLC treated with platinum-doublet chemotherapy.

One of the immune-related adverse events from immune checkpoint inhibitors (ICIs) is skin toxicity. Oral corticosteroids are the first-line treatment for severe cutaneous immune-related adverse events. However, corticosteroids may conflict with the efficacy of ICIs. A 55-year-old Japanese man with a history of psoriasis vulgaris was diagnosed with small-cell lung cancer (Stage ⅣA) and administered combined chemoimmunotherapy, including atezolizumab, which resulted in exacerbation of psoriasis. In response, he was treated with biological agents, such as anti-IL-23 and IL-17 antibodies, risankizumab, and secukinumab, respectively, and achieved long-term survival with continued treatment with atezolizumab. This case report suggests that biological agents might be the best course of treatment against autoimmune-related adverse events caused by ICI therapy.

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC\'s adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.

BACKGROUND: We explored potential predictive biomarkers of immunotherapy response in patients with extensive-stage small-cell lung cancer (ES-SCLC) treated with durvalumab (D) + tremelimumab (T) + etoposide-platinum (EP), D + EP, or EP in the randomized phase 3 CASPIAN trial.
METHODS: 805 treatment-naïve patients with ES-SCLC were randomized (1:1:1) to receive D + T + EP, D + EP, or EP. The primary endpoint was overall survival (OS). Patients were required to provide an archived tumor tissue block (or ≥ 15 newly cut unstained slides) at screening, if these samples existed. After assessment for programmed cell death ligand-1 expression and tissue tumor mutational burden, residual tissue was used for additional molecular profiling including by RNA sequencing and immunohistochemistry.
RESULTS: In 182 patients with transcriptional molecular subtyping, OS with D ± T + EP was numerically highest in the SCLC-inflamed subtype (n = 10, median 24.0 months). Patients derived benefit from immunotherapy across subtypes; thus, additional biomarkers were investigated. OS benefit with D ± T + EP versus EP was greater with high versus low CD8A expression/CD8 cell density by immunohistochemistry, but with no additional benefit with D + T + EP versus D + EP. OS benefit with D + T + EP versus D + EP was associated with high expression of CD4 (median 25.9 vs. 11.4 months) and antigen-presenting and processing machinery (25.9 vs. 14.6 months) and MHC I and II (23.6 vs. 17.3 months) gene signatures, and with higher MHC I expression by immunohistochemistry.
CONCLUSIONS: These findings demonstrate the tumor microenvironment is important in mediating better outcomes with D ± T + EP in ES-SCLC, with canonical immune markers associated with hypothesized immunotherapy mechanisms of action defining patient subsets that respond to D ± T.
BACKGROUND: ClinicalTrials.gov, NCT03043872.

BACKGROUND: This study aimed to explore the incidence of occult lymph node metastasis (OLM) in clinical T1 - 2N0M0 (cT1 - 2N0M0) small cell lung cancer (SCLC) patients and develop machine learning prediction models using preoperative intratumoral and peritumoral contrast-enhanced CT-based radiomic data.
METHODS: By conducting a retrospective analysis involving 242 eligible patients from 4 centeres, we determined the incidence of OLM in cT1 - 2N0M0 SCLC patients. For each lesion, two ROIs were defined using the gross tumour volume (GTV) and peritumoral volume 15 mm around the tumour (PTV). By extracting a comprehensive set of 1595 enhanced CT-based radiomic features individually from the GTV and PTV, five models were constucted and we rigorously evaluated the model performance using various metrics, including the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curve, and decision curve analysis (DCA). For enhanced clinical applicability, we formulated a nomogram that integrates clinical parameters and the rad_score (GTV and PTV).
RESULTS: The initial investigation revealed a 33.9% OLM positivity rate in cT1 - 2N0M0 SCLC patients. Our combined model, which incorporates three radiomic features from the GTV and PTV, along with two clinical parameters (smoking status and shape), exhibited robust predictive capabilities. With a peak AUC value of 0.772 in the external validation cohort, the model outperformed the alternative models. The nomogram significantly enhanced diagnostic precision for radiologists and added substantial value to the clinical decision-making process for cT1 - 2N0M0 SCLC patients.
CONCLUSIONS: The incidence of OLM in SCLC patients surpassed that in non-small cell lung cancer patients. The combined model demonstrated a notable generalization effect, effectively distinguishing between positive and negative OLMs in a noninvasive manner, thereby guiding individualized clinical decisions for patients with cT1 - 2N0M0 SCLC.

UICC stage IV small-cell lung cancer (SCLC) is a highly aggressive malignancy without curative treatment options. Several randomized trials have demonstrated improved survival rates through the addition of checkpoint inhibitors to first-line platin-based chemotherapy. Consequently, a combination of chemo- and immunotherapy has become standard palliative treatment. However, no reliable predictive biomarkers for treatment response exist. Neither PD-L1 expression nor tumor mutational burden have proven to be effective predictive biomarkers. In this study, we compared the cellular immune statuses of SCLC patients to a healthy control cohort and investigated changes in peripheral blood B, T, and NK lymphocytes, as well as several of their respective subsets, during treatment with immunochemotherapy (ICT) using flow cytometry. Our findings revealed a significant decrease in B cells, while T cells showed a trend to increase throughout ICT. Notably, high levels of exhausted CD4+ and CD8+ cells, alongside NK subsets, increased significantly during treatment. Furthermore, we correlated decreases/increases in subsets after two cycles of ICT with survival. Specifically, a decrease in Th17 cells indicated a better overall survival. Based on these findings, we suggest conducting further investigation into Th17 cells as a potential early predictive biomarkers for response in patients receiving palliative ICT for stage IV SCLC.

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

Small-cell lung cancer (SCLC) is a biologically aggressive subtype of lung cancer, a lethal disease characterized by rapid tumor growth, early relapse, a strong tendency for early widespread metastasis, and high genomic instability, making it a formidable foe in modern oncology practice. While the management of non-SCLC has been revolutionized in the era of immunotherapy, progress in SCLC has been more muted. Recent randomized phase III clinical trials have combined programmed death ligand-1 inhibitors to a chemotherapy backbone and demonstrated improved survival; however, the absolute benefit observed is short months. There is an undeniable urgent need for better responses, better agents, novel therapeutic approaches, and more rational, biomarker-driven clinical trials in SCLC. In this review, we discuss the rationale and current understanding of the biology of SCLC in the modern era of immunotherapy, discuss recent advances in front-line immunotherapeutic approaches that have changed clinical practice globally, provide an overview of some of the challenges and limitations that have staggered immune checkpoint blockade in SCLC, and explore some of the novel immunotherapeutic approaches currently being investigated.

BACKGROUND: Currently, no effective measures are available to predict the curative efficacy of small-cell lung cancer (SCLC) chemotherapy. We expect to develop a method for effectively predicting the SCLC chemotherapy efficacy and prognosis in clinical practice in order to offer more pertinent therapeutic protocols for individual patients.
METHODS: We adopted matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinPro Tools system to detect serum samples from 154 SCLC patients with different curative efficacy of standard chemotherapy and analyze the different peptides/proteins of SCLC patients to discover predictive tumor markers related to chemotherapy efficacy. Ten peptide/protein peaks were significantly different in the two groups.
RESULTS: A genetic algorithm model consisting of four peptides/proteins was developed from the training group to separate patients with different chemotherapy efficacies. Among them, three peptides/proteins (m/z 3323.35, 6649.03 and 6451.08) showed high expression in the disease progression group, whereas the peptide/protein at m/z 4283.18 was highly expressed in the disease response group. The classifier exhibited an accuracy of 91.4% (53/58) in the validation group. The survival analysis showed that the median progression-free survival (PFS) of 30 SCLC patients in disease response group was 9.0 months; in 28 cases in disease progression group, the median PFS was 3.0 months, a statistically significant difference (χ2 = 46.98, P < 0.001). The median overall survival (OS) of the two groups was 13.0 months and 7.0 months, a statistically significant difference (χ2 = 40.64, P < 0.001).
CONCLUSIONS: These peptides/proteins may be used as potential biological markers for prediction of the curative efficacy and prognosis for SCLC patients treated with standard regimen chemotherapy.