BACKGROUND: Small-cell lung cancer (SCLC) is a leading cause of cancer-related death. However, the prognostic value of the tumor shrinkage rate (TSR) after chemotherapy for SCLC is still unknown.
METHODS: We performed a retrospective analysis of 235 patients with SCLC. The TSR cutoff was determined based on receiver-operating characteristic curve analysis. The associations of TSR with progression-free survival (PFS) and overall survival (OS) were assessed using univariate and multivariate Cox proportional hazards models. Survival curves were obtained by the Kaplan-Meier method and compared using the log-rank test. Recurrence patterns after first-line treatment were summarized in a pie chart. A nomogram was constructed to validate the predictive role of the TSR in SCLC.
RESULTS: The TSR cutoff was identified to be  - 6.6%. Median PFS and OS were longer in the group with a TSR < -6.6% than in the group with a TSR ≥ - 6.6%. PFS and OS were also longer in patients with extensive SCLC when the TSR was < - 6.6% than when it was > - 6.6%. Brain metastasis-free survival was better in the group with a TSR < - 6.6%. There was a significant positive correlation between TSR and PFS. Furthermore, univariate and multivariate regression analyses showed that the TSR, patient age, and previous radiotherapy were independent prognostic factors for OS while TSR and M stage were independent prognostic factors for PFS.
CONCLUSIONS: The TSR may prove to be a good indicator of OS and PFS in patients receiving chemotherapy-based first-line treatment for SCLC.

Small-cell lung cancer (SCLC) is the most aggressive and lethal type of lung cancer, characterized by limited treatment options, early and frequent metastasis. However, the determinants of metastasis in SCLC are poorly defined. Here, we show that estrogen-related receptor gamma (ERRγ) is overexpressed in metastatic SCLC tumors, and is positively associated with SCLC progression. ERRγ functions as an essential activator of extracellular matrix (ECM) remodeling and cell adhesion, two critical steps in metastasis, by directly regulating the expression of major genes involved in these processes. Genetic and pharmacological inhibition of ERRγ markedly reduces collagen production, cell-matrix adhesion, microfilament production, and eventually blocks SCLC cell invasion and tumor metastasis. Notably, ERRγ antagonists significantly suppressed tumor growth and metastasis and restored SCLC vulnerability to chemotherapy in multiple cell-derived and patient-derived xenograft models. Taken together, these findings establish ERRγ as an attractive target for metastatic SCLC and provide a potential pharmacological strategy for treating this lethal disease.

UNASSIGNED: This retrospective study evaluates the efficacy of camrelizumab combined with anlotinib versus chemotherapy in patients with extensive-stage small-cell lung cancer (ES-SCLC) undergoing second-line treatment.
UNASSIGNED: Data were sourced from medical records at a Chinese medical facility, involving 34 patients diagnosed with ES-SCLC after failing first-line treatment. Patients were divided into two groups: one received camrelizumab (200 mg every 3 weeks) with anlotinib (12 mg daily for 14 days followed by a 7-day rest), while the other group received physician-chosen chemotherapy administered every 3 weeks. The primary endpoint was progression-free survival (PFS), with secondary endpoints including overall survival (OS), objective response rate (ORR), and disease control rate (DCR).
UNASSIGNED: The combination therapy group showed a significant improvement in PFS compared to the chemotherapy group (median PFS: 7 months vs. 3 months; hazard ratio (HR): 0.34; 95% confidence interval (CI): 0.15-0.77; p<0.001). However, there was no statistically significant difference in OS between the groups (16.3 months vs. 17.3 months; p=0.82). The ORR was 52.9% in the combination therapy group versus 23.5% in the chemotherapy group (p=0.08), and the DCR was 82.4% compared to 58.8% (p=0.26). Grade 3 or higher adverse events were observed in 17.6% of the combination therapy group and 29.4% of the chemotherapy group.
UNASSIGNED: The findings suggest that the combination of camrelizumab and anlotinib offers a superior anti-tumor response with a manageable safety profile in a second-line setting for ES-SCLC patients. This combination regimen may be a viable option for second-line ES-SCLC treatment.

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.

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.

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.

UNASSIGNED: The efficacy and safety of different immunosuppressants combined with chemotherapy in treating patients with small-cell lung cancer (extensive-disease small-cell lung cancer, limited-disease small-cell lung cancer and relapsed small-cell lung cancer) are still unknown, and there are no reports directly comparing the efficacy and safety of other immunotherapies.
UNASSIGNED: This study aimed to compare the efficacy and safety of first-line immunotherapy combined with chemotherapy in patients with small-cell lung cancer.
UNASSIGNED: We searched Pubmed, Embase, Cochrane Library, CNKI, and Wanfang databases for relevant articles published from inception to November 11, 2020. The risk of bias of the included studies was conducted using the Cochrane risk-of-bias (RoB) tool. Multiple Bayesian network meta-analyses were performed. They conducted data analysis using R Studio and STATA version 15.1. The outcomes comprised overall survival (OS), progression-free survival (PFS), stability of response (SOR), duration of response (DOR) and adverse events of grade 3 or higher (AE grade≥3). A 95% confidence interval (CI) was provided for each estimate.
UNASSIGNED: This meta-analysis included 16 RCT studies with 5898 patients. For OS, relative to chemotherapy (MD=-4.49; 95%CI [-7.97, -1.03]), durvalumab plus tremelimumab (MD=-4.62; 95%CI [-9.08, -0.11]), ipilimumab (MD=-4.26; 95%CI [-8.01, -0.3]) and nivolumab(MD=-5.66; 95%CI [-10.44, -1.11]) and nivolumab plus ipilimumab (MD=-4.56; 95%CI [-8.7, -0.1]), serplulimab can significantly increase the OS of SCLC patients. There was no significant difference between PFS, SOR and DOR. Analysis of AE showed that different immunotherapy combined chemotherapy regimens were similar to single chemotherapy regarding the overall incidence of AE grade≥3. However, after the cumulative ranking of the common symptoms of different adverse reactions, it was found that nivolumab ranked first in the occurrence probability of anemia (99.08%), fatigue (84.78%), and decreased appetite (89.66%). durvalumab was the most likely in nausea (75.4%). Pembrolizumab (76.24%) was most likely to cause pruritus. Chemotherapy combined with immunotherapy caused less diarrhea than chemotherapy alone (80.16%).
UNASSIGNED: According to our analysis, serplulimab combined with chemotherapy is more likely to show better efficacy with a manageable safety profile for small-cell lung cancer. However, the evidence for this comparison shows some limitations due to the number of literature.
UNASSIGNED: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023486053.

N-myc downstream-regulated gene 2 (NDRG2) has been recognised as a negative regulator of the progression of numerous tumours, yet its specific role in small-cell lung carcinoma (SCLC) is not fully understood. The purpose of the current study was to investigate the biological role and mechanism of NDRG2 in SCLC. Initial investigation using the Gene Expression Omnibus (GEO) dataset revealed marked downregulation of NDRG2 transcripts in SCLC. The decreased abundance of NDRG2 in SCLC was verified by examining clinical specimens. Increasing NDRG2 expression in SCLC cell lines caused significant changes in cell proliferation, cell cycle progression, colony formation, and chemosensitivity. NDRG2 overexpression decreased the levels of phosphorylated PTEN, AKT and mTOR. In PTEN-depleted SCLC cells, the upregulation of NDRG2 did not result in any noticeable impact on AKT or mTOR activation. Additionally, the reactivation of AKT reversed the antitumour effects of NDRG2 in SCLC cells. Notably, increasing NDRG2 expression retarded the growth of SCLC cell-derived xenografts in vivo. In conclusion, NDRG2 serves as an inhibitor of SCLC, and its cancer-inhibiting effects are achieved through the suppression of AKT/mTOR via the activation of PTEN. This work suggests that NDRG2 is a potential druggable target for SCLC treatment.

Small-cell lung cancer (SCLC) is an aggressive form of lung cancer with limited treatment options, especially for extensive-stage (ES) patients. We present a case of a 70-year-old male with ES-SCLC and asymptomatic brain metastasis who opted for immune monotherapy with serplulimab (an anti-PD-1 antibody). After four cycles, the patient achieved a confirmed partial response and a progression-free survival of over 1 year. Moreover, we observed a consistent decline in tumor biomarkers, and brain MRI indicated reduced metastatic activity. Remarkably, the patient tolerated the treatment well, with only mild diarrhea. This case highlights serplulimab\'s potential as a first-line treatment in select ES-SCLC patients, emphasizing the importance of further research on immunotherapy predictive biomarkers.
Small-cell lung cancer (SCLC) is a severe type of lung cancer that often does not have many treatment options, especially in its advanced stages. This article discusses the experience of a 70-year-old man with advanced SCLC who also had cancer spread to his brain but did not show symptoms. He chose to try a new kind of cancer treatment called serplulimab, which works by helping the immune system fight the cancer. After receiving this treatment four-times, his cancer showed significant improvement, and he did not experience further cancer growth for more than 1 year. Tests also revealed that his cancer markers decreased, and the cancer in his brain became less active. Notably, he tolerated this agent with only mild diarrhea occurring. This case is important because it suggests that serplulimab could be an effective first treatment for some patients with advanced SCLC, and it highlights the need for more research to find ways to predict who will benefit from this type of therapy.

UNASSIGNED: Currently, there is a lack of well-established markers to predict the efficacy of chemoimmunotherapy in small-cell lung cancer (SCLC). Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), advanced lung cancer inflammation index (ALI) and prognostic nutritional index (PNI) are associated with prognosis in several tumors, whereas their predictive role in SCLC remains unclear.
UNASSIGNED: A retrospective study was conducted at Sun Yat-sen University Cancer Center, involving extensive-stage SCLC (ES-SCLC) patients who received first-line chemoimmunotherapy between January 2020 and December 2021. Peripheral blood biomarkers were extracted from medical records and their correlation with prognosis and immune-related adverse events (IRAEs) was analyzed.
UNASSIGNED: A total of 114 patients were included. Patients with a low PLR, high ALI and high PNI had prolonged progression-free survival (PFS) compared to those with a high PLR, low ALI and low PNI. Patients with a low NLR, low PLR, high ALI and high PNI had prolonged overall survival (OS) compared to those with a high NLR, high PLR, low ALI and low PNI. Cox regression model showed that PNI was an independent risk factor for both PFS and OS. ROC curve showed that PNI outperforms NLR, PLR and ALI in predicting both PFS and OS. The PNI-based nomogram demonstrated strong predictive capability for both PFS and OS. In addition, there was a significant correlation between PNI and IRAEs.
UNASSIGNED: A high baseline PNI might be associated with improved prognosis and the occurrence of IRAEs in ES-SCLC patients treated with first-line chemoimmunotherapy.