Small Cell Lung Cancer Patients Research Articles

Aprospective study of detection and clinical significance of bone marrow tumor cells in small cell lung cancer

Objective: To investigate the detection of bone marrow tumor cells in small cell lung cancer (SCLC) patients and their relationship with clinical features, treatment response and prognosis. Methods: A total of 113patients with newly diagnosed SCLC from January 2018 to October 2022 at Beijing Chest Hospital were prospectively enrolled. Before treatment, bone marrow was aspirated and separately submitted for tumor cells detection by liquid-based cytology and disseminated tumor cells (DTCs) detection by the substrction enrichment and immunostaining fluorescence in situ hybridization (SE-iFISH) platform. The correlation between the detection results of the two methods with patients' clinical features and treatment response was evaluated by Chi-square. Kaplan-Meier method was applied to create survival curves and the Cox regression model was used for multivariate analysis. Results: The positive rate of bone marrow liquid-based cytology in SCLC was 15.93% (18/113). The liver and bone metastases rates were significantly higher (55.56% vs 11.58% for liver metastasis, P＜0.001; 77.78% vs 16.84% for bone metastasis, P＜0.001) and thrombocytopenia was more common (16.67% vs 2.11%, P=0.033) in patients with tumor cells detected in liquid-based cytology than those without detected tumor cells. As for SE-iFISH, DTCs were detected in 92.92% of patients (105/113), the liver and bone metastasis rates were significantly higher (37.93% vs 11.90% for liver metastasis, P=0.002; 44.83% vs 20.23 % for bone metastasis, P=0.010), and the incidence of thrombocytopenia was significantly increased (13.79% vs 1.19%, P=0.020) in patients with DTCs≥111 per 3 ml than those with DTCs＜111 per 3 ml. The positive rates of bone marrow liquid-based cytology in the disease control group and the disease progression group were 12.00% (12/100) and 46.15% (6/13), respectively, and the difference was statistically significant (P=0.002). However, the result of SE-iFISH revealed the DTCs quantities of the above two groups were 29 (8,110) and 64 (15,257) per 3 ml, and there was no statistical difference between the two groups (P=0.329). Univariate analysis depicted that the median progression-free survival (PFS) and median overall survival (OS) of liquid-based cytology positive patients were significantly shorter than those of tumor cell negative patients (6.33 months vs 9.27 months for PFS, P=0.019; 8.03 months vs 19.50 months for OS, P=0.019, P=0.033). The median PFS and median OS in patients with DTCs≥111 per 3 ml decreased significantly than those with DTCs＜111 per 3 ml (6.83 months vs 9.50 months for PFS, P=0.004; 11.2 months vs 20.60 months for OS, P=0.019). Multivariate analysis showed that disease stage (HR=2.806, 95%CI:1.499-5.251, P=0.001) and DTCs quantity detected by SE-iFISH (HR=1.841, 95%CI:1.095-3.095, P=0.021) were independent factors of PFS, while disease stage was the independent factor of OS (HR=2.538, 95%CI:1.169-5.512, P=0.019). Conclusions: Both bone marrow liquid-based cytology and SE-iFISH are clinically feasible. The positive detection of liquid-based cytology or DTCs≥111 per 3 ml was correlated with distant metastasis, and DTCs≥111 per 3 ml was an independent prognostic factor of decreased PFS in SCLC.

CDK9 inhibition as an effective therapy for small cell lung cancer

Treatment-naïve small cell lung cancer (SCLC) is typically susceptible to standard-of-care chemotherapy consisting of cisplatin and etoposide recently combined with PD-L1 inhibitors. Yet, in most cases, SCLC patients develop resistance to first-line therapy and alternative therapies are urgently required to overcome this resistance. In this study, we tested the efficacy of dinaciclib, an FDA-orphan drug and inhibitor of the cyclin-dependent kinase (CDK) 9, among other CDKs, in SCLC. Furthermore, we report on a newly developed, highly specific CDK9 inhibitor, VC-1, with tumour-killing activity in SCLC. CDK9 inhibition displayed high killing potential in a panel of mouse and human SCLC cell lines. Mechanistically, CDK9 inhibition led to a reduction in MCL-1 and cFLIP anti-apoptotic proteins and killed cells, almost exclusively, by intrinsic apoptosis. While CDK9 inhibition did not synergise with chemotherapy, it displayed high efficacy in chemotherapy-resistant cells. In vivo, CDK9 inhibition effectively reduced tumour growth and improved survival in both autochthonous and syngeneic SCLC models. Together, this study shows that CDK9 inhibition is a promising therapeutic agent against SCLC and could be applied to chemo-refractory or resistant SCLC.

Correlation between small-cell lung cancer serum protein/peptides determined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and chemotherapy efficacy

BackgroundCurrently, 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.MethodsWe 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.ResultsA 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).ConclusionsThese 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.

CD3, CD8, IFN-γ, tumor and stroma inflammatory cells as prognostic indicators for surgically resected SCLC: evidences from a 10-year retrospective study and immunohistochemical analysis

Current clinical guidelines limit surgical intervention to patients with cT1-2N0M0 small cell lung cancer (SCLC). Our objective was to reassess the role of surgery in SCLC management, and explore novel prognostic indicators for surgically resected SCLC. We reviewed all patients diagnosed with SCLC from January 2011 to April 2021 in our institution. Survival analysis was conducted using the Kaplan–Meier method, and independent prognostic factors were assessed through the Cox proportional hazard model. In addition, immunohistochemistry (IHC) staining was performed to evaluate the predictive value of selected indicators in the prognosis of surgically resected SCLC patients. In the study, 177 SCLC patients undergoing surgical resection were ultimately included. Both univariate and multivariate Cox analysis revealed that incomplete postoperative adjuvant therapy emerged as an independent risk factor for adverse prognosis (p < 0.001, HR 2.96). Survival analysis revealed significantly superior survival among pN0-1 patients compared to pN2 patients (p < 0.0001). No significant difference in postoperative survival was observed between pN1 and pN0 patients (p = 0.062). Patients with postoperative stable disease (SD) exhibited lower levels of tumor inflammatory cells (TIC) (p = 0.0047) and IFN-γ expression in both area and intensity (p < 0.0001 and 0.0091, respectively) compared to those with postoperative progressive disease (PD). Conversely, patients with postoperative SD showed elevated levels of stromal inflammatory cells (SIC) (p = 0.0453) and increased counts of CD3+ and CD8+ cells (p = 0.0262 and 0.0330, respectively). Survival analysis indicated that high levels of SIC, along with low levels of IFN-γ+ cell area within tumor tissue, may correlate positively with improved prognosis in surgically resected SCLC (p = 0.017 and 0.012, respectively). In conclusion, the present study revealed that the patients with pT1-2N1M0 staging were a potential subgroup of SCLC patients who may benefit from surgery. Complete postoperative adjuvant therapy remains an independent factor promoting a better prognosis for SCLC patients undergoing surgical resection. Moreover, CD3, CD8, IFN-γ, TIC, and SIC may serve as potential indicators for predicting the prognosis of surgically resected SCLC.

Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points

Background and purposeRecently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients.MethodsThis research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients’ overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell’s C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan–Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26.ResultsThis study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell’s C-index in the training and validation sets of the model was 0.85 (95% CI 0.76–0.93) and 0.88 (95% CI 0.76–0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy.ConclusionThis study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.

Alterations in Peripheral Lymphocyte Subsets under Immunochemotherapy in Stage IV SCLC Patients: Th17 Cells as Potential Early Predictive Biomarker for Response.

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.

Initial screening for neuronal autoantibodies and their putative impact on survival in patients with small-cell lung cancer.

Small-cell lung cancer (SCLC) may be associated with neuronal autoantibodies and paraneoplastic neurological syndromes. It has been suggested that neuronal autoantibodies, especially antineuronal nuclear antibody type 1 (Hu) autoantibodies, are associated with longer survival of patients with SCLC. The objective of this study was to determine the frequency and distribution of neuronal autoantibodies at the time of diagnosis of SCLC patients and assess survival rates in relation to autoimmunity. In this retrospective study, serum from 40 patients with biopsy-proven SCLC at the time of diagnosis was studied prior to treatment. The sera originated from a cancer registry at the Oncology Department, Vejle Hospital from 2007 to 2010. The sera were analyzed blindly to clinical status for the presence of neuronal autoantibodies. Medical records were reviewed for neurological symptoms. Neuronal autoantibodies were detected in 22/40 (55%) of the SCLC patients. A broad range of neurological symptoms was recorded in 28/40 (70%) patients, of which 14/28 (50%) were positive for neuronal autoantibodies. The most frequently detected autoantibodies were Hu (7/40, 17.5%) followed by GAD65 (6/22, 15.0%). Striational and P/Q- or N-type voltage-gated calcium channel antibodies were less common, with each found in five patients (12.5%). Eight patients (20%) had coexisting autoantibodies. Autoantibody-positivity was not associated with survival. Neuronal autoantibodies were at time of diagnosis found in approximately half of the treatment-naïve SCLC patients. Neither autoantibody positivity at diagnosis nor neurological manifestations correlated with survival and their clinical importance requires further studies in larger, prospective cohorts.

Expression patterns of novel immunotherapy targets in intermediate- and high-grade lung neuroendocrine neoplasms

BackgroundAdvancements in immunotherapeutic approaches only had a modest impact on the therapy of lung neuroendocrine neoplasms (LNENs). Our multicenter study aimed to investigate the expression patterns of novel immunotherapy targets in intermediate- and high-grade LNENs.MethodsThe expressions of V-domain Ig suppressor of T cell activation (VISTA), OX40L, Glucocorticoid-induced TNF receptor (GITR), and T cell immunoglobulin and mucin domain 3 (TIM3) proteins were measured by immunohistochemistry in surgically resected tumor samples of 26 atypical carcinoid (AC), 49 large cell neuroendocrine lung cancer (LCNEC), and 66 small cell lung cancer (SCLC) patients. Tumor and immune cells were separately scored.ResultsTumor cell TIM3 expression was the highest in ACs (p < 0.001), whereas elevated tumor cell GITR levels were characteristic for both ACs and SCLCs (p < 0.001 and p = 0.011, respectively). OX40L expression of tumor cells was considerably lower in ACs (vs. SCLCs; p < 0.001). Tumor cell VISTA expression was consistently low in LNENs, with no significant differences across histological subtypes. ACs were the least immunogenic tumors concerning immune cell abundance (p < 0.001). Immune cell VISTA and GITR expressions were also significantly lower in these intermediate-grade malignancies than in SCLCs or in LCNECs. Immune cell TIM3 and GITR expressions were associated with borderline prognostic significance in our multivariate model (p = 0.057 and p = 0.071, respectively).ConclusionsLNEN subtypes have characteristic and widely divergent VISTA, OX40L, GITR, and TIM3 protein expressions. By shedding light on the different expression patterns of these immunotherapy targets, the current multicenter study provides support for the future implementation of novel immunotherapeutic approaches.

Natural history of SCLC patients treated in third-line and beyond: A retrospective real world study

ObjectivesTo describe treatment patterns and estimate outcomes among real-world small cell lung cancer (SCLC) patients in the US who received three or more lines of therapy. Materials and methodsWe conducted a retrospective analysis of adult patients with SCLC who received a front-line platinum-based regimen and two additional lines of therapy (ie., a cohort of at least three lines of therapy). De-identified patients were selected from a United States Flatiron Health oncology database of electronic health records. Treatment patterns were captured by line of therapy. Outcomes evaluated by line of therapy included real-world overall survival (rwOS), real-world progression free survival (rwPFS), real-world response rate (rwRR) and real-world duration of response (rwDOR). ResultsThe analysis included 326 3L SCLC patients, of which 103 (32 %) received 4L treatment, and 38 % (39/103) of 4L treated received 5L of therapy. Among the 3L cohort, the average age was 67 years, 49 % were male, and nearly all had a history of smoking (96 %). In the 3L setting, the median rwOS was 5.3 months (95 % Confidence Interval (CI): 4.5, 6.0), median rwPFS was 2.5 months (95 % CI: 2.1, 2.7), rwRR was 19.3 % (95 % CI: 15.2, 24.0) and median DOR was 3.4 months (95 % CI: 2.8, 4.4). No differences were seen in outcomes between the overall cohort and a subgroup of patients treated with front-line platinum-based regimen with an anti-programmed cell death ligand 1 (PD-L1) agent (atezolizumab or durvalumab), in each respective line of therapy. ConclusionResults from this large, real-world study of US patients with SCLC in the 3L setting and beyond highlight the poor treatment outcomes in advanced SCLC patients with existing therapies and underscore the dire need for new therapies for SCLC patients.

Nomograms Predict PFS and OS for SCLC Patients After Standardized Treatment: A Real-World Study.

This study aims to investigate the process of small cell lung cancer (SCLC) patients from achieving optimal efficacy to experiencing disease progression until death. It examines the predictive value of the treatment response on progression free survival (PFS) and overall survival (OS) of SCLC patients. We conducted a retrospective analysis on 136 SCLC patients diagnosed from 1992 to 2018. Important prognostic factors were identified to construct nomogram models. The predictive performance of the models was evaluated using the receiver operating characteristic curves and calibration curves. Survival differences between groups were compared using Kaplan-Meier survival curves. Subsequently, an independent cohort consisting of 106 SCLC patients diagnosed from 2014 to 2021 was used for validation. We constructed two nomograms to predict first-line PFS (PFS1) and OS of SCLC. The area under the receiver operating characteristic curves for the PFS1 nomogram predicting PFS at 3-, 6-, and 12-months were 0.919 (95% CI: 0.867-0.970), 0.908 (95% CI: 0.860-0.956) and 0.878 (95% CI: 0.798-0.958), and for the OS nomogram predicting OS at 6-, 12-, and 24-months were 0.814 (95% CI: 0.736-0.892), 0.819 (95% CI: 0.749-0.889) and 0.809 (95% CI: 0.678-0.941), indicating those two models with a high discriminative ability. The calibration curves demonstrated the models had a high degree of consistency between predicted and observed values. According to the risk scores, patients were divided into high-risk and low-risk groups, showing a significant difference in survival rate. And these findings were validated in another independent validation cohort. Based on the patients' treatment response after standardized treatment, we developed and validated two nomogram models to predict PFS1 and OS of SCLC. The models demonstrated good accuracy, reliability and clinical applicability by validating in an independent cohort.

Aspartate Transaminase-to-Albumin Ratio (ATAR), a Novel Prognostic Index, Predicts Outcomes in Patients with Small-Cell Lung Cancer.

Small cell lung cancer (SCLC) is characterized by high invasion rates, rapid progression, and poor prognoses. Thus, identifying SCLC patients at high risk of progression and death is critical to improve long-term survival. In this study, the aspartate transaminase-to-albumin ratio (ATAR) was examined as a prognostic factor for SCLC patients. We screened 196 SCLC patients from December 2013 to September 2022 at the Sichuan Cancer Hospital. The data was collected from patients' medical information as well as from their blood results during diagnosis. Using the Youden index as a cutoff value, patients were divided into high-risk（> 0.54) and low-risk (≤ 0.54) ATAR groups. We analyzed the prognostic factors for overall survival (OS) using the Kaplan-Meier method, univariate and multivariate analyses, Cox regression, and the C-index. There were 109 (55.6%) smokers among the patients, and the median OS was 17.55 months. The Kaplan-Meier analysis indicated that patients with high-risk ATAR had significantly lower OS (p < 0.0001). A multivariate analysis demonstrated that elevated ATAR is an independent adverse predictor of OS (p < 0.001, HR = 1.907). Our study found that ATAR is an independent predictor of survival outcomes in SCLC, which was superior to ALB, PNI, and SII in predicting outcomes in low-risk and high-risk groups (all p < 0.05). Models combining ATAR with ALB, PNI, and SII showed more powerful prognostic value than their corresponding original models. Moreover, the prognostic indicator ATAR can significantly stratify stage I - II and III - IV SCLC patients (p ＜ 0.05). Peripheral blood ATAR prognostic index can be used as an independent predictor of SCLC patients before treatment.

The Role and Mechanism of IFITM1 in Developing Acquired Cisplatin Resistance in Small Cell Lung Cancer

Platinum-based chemotherapies, historically the cornerstone of first-line treatment for small-cell lung cancer (SCLC), face a major hurdle: the frequent emergence of chemoresistance, notably to cisplatin (CDDP). Current understanding of the mechanisms driving CDDP resistance in SCLC is incomplete. Notably, Interferon inducible transmembrane protein1 (IFITM1) has been identified as a key player in the distant metastasis of SCLC. Analysis of The Cancer Genome Atlas (TCGA) database revealed that IFITM1 expression is markedly elevated in tumor tissues as compared to that from adjacent normal tissues, correlating with a worse prognosis for patients with SCLC. Our research focused on investigating the role of IFITM1 in the acquisition of cisplatin resistance in SCLC. Further clinical sample analysis highlighted a significant increase in IFITM1 levels in SCLC tissues from cisplatin-resistant patients versus those were responsive to CCDP treatment, with similar trends observed in cisplatin-resistant SCLC cells. Crucially, overexpression of IFITM1 reduced the sensitivity of SCLC cells to cisplatin, while silencing IFITM1 enhanced chemosensitivity in cisplatin-resistant strains. Our in vivo studies further confirmed that silencing IFITM1 significantly boosted the efficacy of cisplatin in inhibiting growth of subcutaneous tumors of NCI-H466/CDDP cells (cisplatin-resistant SCLC cells) in a mouse model. Mechanistically, IFITM1 appears to foster cisplatin resistance through activation of the Wnt/β-catenin pathway. In summary, our findings suggest that targeting IFITM1, alongside cisplatin treatment, could offer a promising therapeutic strategy to overcome resistance and improve outcomes for SCLC patients.

Oncogenic functions and therapeutic potentials of targeted inhibition of SMARCAL1 in small cell lung cancer

Small cell lung cancer (SCLC) is a recalcitrant cancer characterized by high frequency loss-of-function mutations in tumor suppressors with a lack of targeted therapy due to absence of high frequency gain-of-function abnormalities in oncogenes. SMARCAL1 is a member of the ATP-dependent chromatin remodeling protein SNF2 family that plays critical roles in DNA damage repair and genome stability maintenance. Here, we showed that SMARCAL1 was overexpressed in SCLC patient samples and was inversely associated with overall survival of the patients. SMARCAL1 was required for SCLC cell proliferation and genome integrity. Mass spectrometry revealed that PAR6B was a downstream SMARCAL1 signal molecule which rescued inhibitory effects caused by silencing of SMARCAL1. By screening of 36 FDA-approved clinically available agents related to DNA damage repair, we found that an aza-anthracenedione, pixantrone, was a potent SMARCAL1 inhibitor which suppressed the expression of SMARCAL1 and PAR6B at protein level. Pixantrone caused DNA damage and exhibited inhibitory effects on SCLC cells in vitro and in a patient-derived xenograft mouse model. These results indicated that SMARCAL1 functions as an oncogene in SCLC, and pixantrone as a SMARCAL1 inhibitor bears therapeutic potentials in this deadly disease.

Correlation of Systemic Inflammation Parameters and Serum SLFN11 in Small Cell Lung Cancer-A Prospective Pilot Study.

The objective of this research was to analyze the correlation of the neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), soluble programmed cell death ligand 1 (sPD-L1), and Schlafen 11 (SLFN11) with the response to first-line chemotherapy in a cohort of small cell lung cancer (SCLC) patients, and to determine their potential as predictive serum biomarkers. A total of 60 SCLC patients were included. Blood samples were taken to determine CRP, sPD-L1, and SLFN11 levels. The first sampling was performed before the start of chemotherapy, the second after two cycles, and the third after four cycles of chemotherapy. The patients who died earlier during the study had NLR and SLFN11 concentrations significantly higher compared to the survivor group. In the group of survivors, after two cycles of chemotherapy, the NLR ratio decreased significantly (p < 0.01), but after four cycles, the NLR ratio increased (p < 0.05). Their serum SLFN11 concentration increased significantly (p < 0.001) after two cycles of chemotherapy, but after four cycles, the level of SLFN11 fell significantly (p < 0.01). CRP, NLR, and SLFN11 were significant predictors of patient survival according to Kaplan-Meier analysis. The combination of inflammatory parameters and SLFN11 with a cutoff value above the 75th percentile of the predicted probability was associated with significantly lower overall survival in SCLC patients (average survival of 3.6 months vs. 4.8 months). The combination of inflammatory markers and the levels of two specific proteins (sPD-L1, SLFN11) could potentially serve as a non-invasive biomarker for predicting responses to DNA-damaging therapeutic agents in SCLC.

A Clinical Analysis of Anti-Programmed Death-Ligand 1 (PD-L1) Immune Checkpoint Inhibitor Treatments Combined with Chemotherapy in Untreated Extensive-Stage Small-Cell Lung Cancer.

Real-world clinical experience of using anti-programmed death-ligand 1 (PD-L1) immune checkpoint inhibitors (ICIs) combined with chemotherapy in the first-line treatment of extensive-stage small-cell lung cancer (SCLC) patients has rarely been reported. In this study, we aimed to perform a retrospective multicenter clinical analysis of extensive-stage SCLC patients receiving first-line therapy with anti-PD-L1 ICIs combined with chemotherapy. Between November 2018 and March 2022, 72 extensive-stage SCLC patients receiving first-line atezolizumab or durvalumab in combination with chemotherapy, according to the cancer center databases of Linkou, Chiayi, and Kaohsiung Chang Gung Memorial Hospitals, were retrospectively included in the analysis. Twenty-one patients (29.2%) received atezolizumab and fifty-one (70.8%) received durvalumab. Objective response (OR) and disease control (DC) rates of 59.7% and 73.6%, respectively, were observed with first-line ICI plus chemotherapy. The median progression-free survival (PFS) was 6.63 months (95% confidence interval (CI), 5.25-8.02), and the median overall survival (OS) was 16.07 months (95% CI, 15.12-17.0) in all study patients. A high neutrophil-to-lymphocyte ratio (NLR; >4) and a high serum lactate dehydrogenase (LDH) concentration (>260 UL) were identified as independent unfavorable factors associated with shorter OS in the multivariate analysis. Regarding safety, neutropenia was the most common grade 3 treatment-related adverse event (AE), but no treatment-related deaths occurred in the study patients. First-line anti-PD-L1 ICIs combined with chemotherapy are effective and safe for male extensive-stage SCLC patients. Further therapeutic strategies may need to be developed for patients with unfavorable outcomes (e.g., baseline high NLR and serum LDH level).

CircIARS: a potential plasma biomarker for diagnosing non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is one of the most prevalent cancers in the world, and early diagnosis can effectively improve patient survival. Here, differentially expressed circIARS genes are screened from the sequencing results, and their molecular characteristics are examined by Sanger sequencing, RNase R assay, agarose gel electrophoresis (AGE), and fluorescence in situ hybridization (FISH). Real-time fluorescence quantitative polymerase chain reaction (qRT-PCR) is performed to detect the expression level of circIARS. The diagnostic value of the signature is analyzed using a subject operating characteristic (ROC) curve. Moreover, plasma is collected from postsurgical, chemotherapy, and relapse patients to investigate the prognostic value of circIARS in NSCLC. The expression of circIARS is greater in both the plasma and tissues of NSCLC patients than in those of healthy individuals, and could be used to distinguish NSCLC patients from patients with benign pulmonary disease (BPD), small cell lung cancer (SCLC) patients, and healthy individuals. The expression level of circIARS relatively decreases after antitumor therapy, such as chemotherapy, and relatively increases after recurrence. ROC analysis reveals that circIARS has better detection efficiency than traditional markers. In addition, circIARS expression level is strongly correlated with several clinicopathological parameters. Finally, we tentatively predict the downstream miRNAs or RBP that might bind to circIARS. Plasma circIARS is significantly greater in NSCLC patients and has good stability and specificity as a diagnostic marker, which could aid in the adjuvant diagnosis and dynamic monitoring of NSCLC.

A practical nomogram for predicting early death in elderly small cell lung cancer patients: A SEER-based study.

This study aimed to identify risk factors for early death in elderly small cell lung cancer (SCLC) patients and develop nomogram prediction models for all-cause and cancer-specific early death to improve patient management. Data of elderly patients diagnosed with SCLC were extracted from the SEER database, then randomly divided into training and validation cohorts. Univariate and stepwise multivariable Logistic regression analyses were performed on the training cohort to identify independent risk factors for early death in these patients. Nomograms were developed based on these factors to predict the overall risk of early death. The efficacy of the nomograms was validated using various methods, including ROC analysis, calibration curves, DCA, NRI, and IDI. Among 2077 elderly SCLC patients, 773 died within 3 months, 713 due to cancer-specific causes. Older age, higher AJCC staging, brain metastases, and lack of surgery, chemotherapy, or radiotherapy increase the risk of all-cause early death, while higher AJCC staging, brain metastases, lung metastases, and lack of surgery, chemotherapy, or radiotherapy increase the risk of cancer-specific death (P < .05). These identified factors were used to construct 2 nomograms to predict the risk of early death. The ROC indicated that the nomograms performed well in predicting both all-cause early death (AUC = 0.823 in the training cohort and AUC = 0.843 in the validation cohort) and cancer-specific early death (AUC = 0.814 in the training cohort and AUC = 0.841 in the validation cohort). The results of calibration curves, DCAs, NRI and IDI also showed that the 2 sets of nomograms had good predictive power and clinical utility and were superior to the commonly used TNM staging system. The nomogram prediction models constructed in this study can effectively assist clinicians in predicting the risk of early death in elderly SCLC patients, and can also help physicians screen patients at higher risk and develop personalized treatment plans for them.

Peripheral NK cells identified as the predictor of response in extensive-stage small cell lung cancer patients treated with first-line immunotherapy plus chemotherapy.

Although immunotherapy improves outcomes in extensive-stage small-cell lung cancer (ES-SCLC), the search for biomarkers predicting treatment success is crucial. Natural killer (NK) cells are potential indicators in various cancers, however, their precise role in ES-SCLC prognosis remains unclear. In this retrospective study, 33 patients with ES-SCLC treated with first-line immuno-chemotherapy were enrolled. The peripheral NK cell percentage and its longitudinal dynamics were analyzed using flow cytometry. Progression-free survival (PFS) and overall survival (OS) were calculated as hazard ratio (HR) and compared statistically. The median PFS was better in the group with normal baseline NK cell levels than the low group (7.0 vs. 4.6months; HR = 0.17; 95% CI 0.07-0.41; P < 0.0001), but there was no association with OS (14.9 vs. 10.3months; HR = 0.55; 95% CI 0.23-1.31; P = 0.171). Furthermore, the NK cell% for 95.0% of patients increased after immunochemotherapy in the clinical response group (P = 0.0047), which led to a better median PFS (6.3 vs. 2.1months; HR = 0.23; 95% CI 0.05-0.98; P < 0.0001) and OS (14.9 vs. 5.9months; HR = 0.20; 95% CI 0.04-1.02; P < 0.0001). Similar trends were observed with NK cell% changes up to disease progression, improving PFS (6.5 vs. 4.3; HR = 0.41; 95% CI 0.12-0.92; P = 0.0049) and OS (17.4 vs. 9.7; HR = 0.42; 95% CI 0.17-1.02; P < 0.0001). In patients with ES-SCLC, the percentage and changes in peripheral NK cells can predict the response to combined immunotherapy and chemotherapy.

Consistency Analysis of Programmed Death Ligand 1 Expression in Non–Small Cell Lung Cancer Between Pleural Effusion and Matched Primary Lung Cancer Tissues by Immunohistochemical Double Staining

In clinical practice, programmed death ligand 1 (PD-L1) detection is prone to nonspecific staining due to the complex cellular composition of pleural effusion smears. In this study, diaminobenzidine (DAB) and 3-amino-9-ethylcarbazole (AEC) immunohistochemistry double staining was performed to investigate PD-L1 expression in tumor cells from malignant pleural effusion (MPE). MPE was considered as a metastasis in non–small cell lung cancer patients; thus, the heterogeneity between metastatic and primary lung cancer was revealed as well. Ninety paired specimens of MPE cell blocks and matched primary lung cancer tissues from non–small cell lung cancer patients were subjected to PD-L1 and thyroid transcription factor-1(TTF-1)/p63 immunohistochemistry double staining. Two experienced pathologists independently evaluated PD-L1 expression using 3 cutoffs (1%, 10%, and 50%). PD-L1 expression in MPE was strongly correlated with that in matched primary lung cancer tissues (R = 0.813; P < .001). Using a 4-tier scale (cutoffs: 1%, 10%, and 50%), the concordance was 71.1% (Cohen’s κ = .534). Using a 2-tier scale, the concordance was 75.6% (1%, Cohen’s κ = 0.53), 78.9% (10%, Cohen’s κ = 0.574), and 95.6% (50%, Cohen’s κ = 0.754). The rates of PD-L1 positivity in MPE (56.7%) were higher than that in lung tissues (32.2%). All 27 discordant cases had higher scores in MPE. The double-staining method provided superior identification of PD-L1-positive tumor cells on a background with nonspecific staining. In conclusion, PD-L1 expression was moderately concordant between metastatic MPE cell blocks and matched primary lung carcinoma tissues, with variability related to tumor heterogeneity. MPE should be considered to detect PD-L1 when histological specimens are unattainable, especially when PD-L1 expression is >50%. PD-L1 positivity rates were higher in MPE. Double staining can improve PD-L1 detection by reducing false-negative/positive results.

Prediction of Pleural Lavage Cytology According to Thin-Section Computed Tomography in Non–Small-Cell Lung Cancer

BackgroundAlthough the positive rate of preresection pleural lavage cytology (PLC) is low, it is an important indicator of poor prognosis for non–small-cell lung cancer patients with frequent pleural dissemination (PD) recurrence. Thin-section computed tomography (TSCT) can reveal relationships between a primary tumor and the pleura at 1 to 2 mm intervals, and this is associated with visceral pleural invasion (VPI). However, its association with PLC remains unclear. Therefore, we aimed to improve PLC efficiency and predict PD recurrence by understanding the relationship between PLC and preoperative TSCT findings. Patients and MethodsBetween January 2014 and December 2018, we reviewed 978 patients with non–small-cell lung cancer who underwent PLC tests during complete resection surgery. Preoperative TSCT findings were evaluated, and factors with the highest specificity (proportion of patients with radiologically to pathologically diagnosed positive PLC) were investigated. We also evaluated their relationships with VPI and PD recurrence. ResultsPLC positive was identified in 55 (5.6%) of the 978 patients. The 2 TSCT findings predicting PLC results, “the absence of pleural findings,” ie, tumor not attached to pleura or without pleural tag, and “consolidation-to-tumor ratio ≤0.5” , had a specificity of 100% (95% confidence interval: 90.4%-100%); additionally, all cases with these findings were VPI negative and had no PD recurrence. And 24% of the cohort had either of these findings. ConclusionThe absence of pleural findings and/or consolidation-to-tumor ratio ≤0.5 of primary tumor on preoperative TSCT can predict PLC negativity with very high probability; therefore, PLC can be omitted for such patients.