High-grade Neuroendocrine Carcinoma Research Articles

Head-to-head: Should Ki67 proliferation index be included in the formal classification of pulmonary neuroendocrine neoplasms?

The reporting of lung neuroendocrine neoplasms (NENs) according to the 2021 World Health Organisation (WHO) is based on mitotic count per 2 mm2, necrosis assessment and a constellation of cytological and immunohistochemical details. Accordingly, typical carcinoid and atypical carcinoid are low- to intermediate-grade neuroendocrine tumours (NETs), while large-cell neuroendocrine carcinoma (NEC) and small-cell lung carcinoma are high-grade NECs. In small-sized diagnostic material (cytology and biopsy), the noncommittal term of carcinoid tumour/NET not otherwise specified (NOS) and metastatic carcinoid NOS have been introduced with regard to primary and metastatic diagnostic settings, respectively. Ki-67 antigen, a well-known marker of cell proliferation, has been included in the WHO classification as a non-essential but desirable criterion, especially to distinguish NETs from high-grade NECs and to delineate the provisional category of carcinoid tumours/NETs with elevated mitotic counts (> 10 mitoses per mm2) and/or Ki-67 proliferation index (≥ 30%). However, a wider use of this marker in the spectrum of lung NENs continues to be highly reported and debated, thus witnessing a never-subsided attention. Therefore, the arguments for and against incorporating Ki-67 in the classification and clinical practice of these neoplasms are discussed herein in detail.

Integrated mutational landscape analysis of poorly differentiated high-grade neuroendocrine carcinoma of the uterine cervix

High-grade neuroendocrine cervical cancers (NETc) are exceedingly rare, highly aggressive tumors. We analyzed 64 NETc tumor samples by whole-exome sequencing (WES). Human papillomavirus DNA was detected in 65.6% (42/64) of the tumors. Recurrent mutations were identified in PIK3CA, KMT2D/MLL2, K-RAS, ARID1A, NOTCH2, and RPL10. The top mutated genes included RB1, ARID1A, PTEN, KMT2D/MLL2, and WDFY3, a gene not yet implicated in NETc. Somatic CNV analysis identified two copy number gains (3q27.1 and 19q13.12) and five copy number losses (1p36.21/5q31.3/6p22.2/9q21.11/11p15.5). Also, gene fusions affecting the ACLY-CRHR1 and PVT1-MYC genes were identified in one of the eight samples subjected to RNA sequencing. To resolve evolutionary history, multiregion WES in NETc admixed with adenocarcinoma cells was performed (i.e., mixed-NETc). Phylogenetic analysis of mixed-NETc demonstrated that adenocarcinoma and neuroendocrine elements derive from a common precursor with mutations typical of adenocarcinomas. Over one-third (22/64) of NETc demonstrated a mutator phenotype of C > T at CpG consistent with deficiencies in MBD4, a member of the base excision repair (BER) pathway. Mutations in the PI3K/AMPK pathways were identified in 49/64 samples. We used two patient-derived-xenografts (PDX) (i.e., NET19 and NET21) to evaluate the activity of pan-HER (afatinib), PIK3CA (copanlisib), and ATR (elimusertib) inhibitors, alone and in combination. PDXs harboring alterations in the ERBB2/PI3K/AKT/mTOR/ATR pathway were sensitive to afatinib, copanlisib, and elimusertib (P < 0.001 vs. controls). However, combinations of copanlisib/afatinib and copanlisib/elimusertib were significantly more effective in controlling NETc tumor growth. These findings define the genetic landscape of NETc and suggest that a large subset of these highly lethal malignancies might benefit from existing targeted therapies.

Prognostic Model for High-Grade Neuroendocrine Carcinoma of the Lung Incorporating Genomic Profiling and Poly (ADP-ribose) Polymerase-1 Expression.

High-grade neuroendocrine carcinoma (HGNEC) of the lung is an aggressive cancer with a complex biology. We aimed to explore the prognostic value of genetic aberrations and poly(ADP-ribose) polymerase-1 (PARP1) expression in HGNEC and to establish a novel prognostic model. We retrospectively enrolled 191 patients with histologically confirmed HGNEC of the lung. Tumor tissues were analyzed using PARP1 immunohistochemistry (IHC; N = 191) and comprehensive cancer panel sequencing (n = 102). Clinical and genetic data were used to develop an integrated Cox hazards model. Strong PARP1 IHC expression (intensity 3) was observed in 153 of 191 (80.1%) patients, and the mean PARP1 H-score was 285 (range, 5-300). To develop an integrated Cox hazard model, our data set included information from 357 gene mutations and 19 clinical profiles. When the targeted mutation profiles were combined with clinical profiles, 12 genes (ATRX, CCND2, EXT2, FGFR2, FOXO1, IL21R, MAF, TGM7, TNFAIP3, TP53, TSHR, and DDR2) were identified as prognostic factors for survival. The integrated Cox hazard model, which combines mutation profiles with a baseline model, outperformed the baseline model (incremental area under the curve 0.84 v 0.78; P = 8.79e-12). The integrated model stratified patients into high- and low-risk groups with significantly different disease-free and overall survival (integrated model: hazard ratio, 7.14 [95% CI, 4.07 to 12.54]; P < .01; baseline model: 4.38 [2.56 to 7.51]; P < .01). We introduced a new prognostic model for HGNEC that combines genetic and clinical data. The integrated Cox hazard model outperformed the baseline model in predicting the survival of patients with HGNEC.

Prognostic factors and predictive models for patients with lung large cell neuroendocrine carcinoma: Based on SEER database.

Lung Large cell neuroendocrine carcinoma (LCNEC) is a rare, aggressive, high-grade neuroendocrine carcinoma with a poor prognosis, mainly seen in elderly men. To date, we have found no studies on predictive models for LCNEC. We extracted data from the Surveillance, Epidemiology, and End Results (SEER) database of confirmed LCNEC from 2010 to 2018. Univariate and multivariate Cox proportional risk regression analyses were used to identify independent risk factors, and then we constructed a novel nomogram and assessed the predictive effectiveness by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). A total of 2546 patients with LCNEC were included, excluding those diagnosed with autopsy or death certificate, tumor, lymph node, metastasis (TNM) stage, tumor grade deficiency, etc., and finally, a total of 743 cases were included in the study. After univariate and multivariate analyses, we concluded that the independent risk factors were N stage, intrapulmonary metastasis, bone metastasis, brain metastasis, and surgical intervention. The results of ROC curves, calibration curves, and DCA in the training and validation groups confirmed that the nomogram could accurately predict the prognosis. The nomogram obtained from our study is expected to be a useful tool for personalized prognostic prediction of LCNEC patients, which may help in clinical decision-making.

Abstract 5864: YAP1 defines a highly plastic, persister cell population in small cell lung cancer (SCLC) following relapse

Abstract SCLC is an aggressive, neuroendocrine malignancy notable for rapid, albeit transient, responses to therapy. We have previously shown that transcriptional heterogeneity among treatment-naïve SCLC tumors underlies four distinct transcriptional subtypes, each with distinct clinical vulnerabilities. Though previously hypothesized to delineate a distinct subtype, expression of YAP1 is largely absent from treatment-naïve SCLC. Less clearly defined is the transcriptional landscape of relapsed SCLC, the evolution of which may underlie SCLC’s capacity for insurmountable resistance. To better define the biology of relapsed SCLC, we performed mass cytometry analysis of patient circulating tumor cells (CTCs), immunohistochemistry for ASCL1, NEUROD1, POU2F3, MYC and YAP1, and single-cell (sc)RNAseq of core needle biopsies from SCLC patients and preclinical models following resistance to standard-of-care therapies. In contrast to treatment-naïve SCLC, YAP1 mRNA and protein are detectable in patient CTC populations and tumors from relapsed patients and PDXs, albeit at levels lower than subtype-defining transcription factors (e.g. ASCL1, NEUROD1, or POU2F3). Notably, however, scRNAseq reveals these YAP1 expressing cells to be mutually exclusive with ASCL1 and NEUROD1, though not necessarily POU2F3. YAP1-expressing cells possess unique mesenchymal, inflamed features and exhibit high levels of transcriptional plasticity. Consistent with the upregulation of YAP1 following chemotherapy, YAP1-positive cell populations express senescence associated secretory phenotype genes and cancer stem cell genes, suggesting that these populations represent drug tolerant persister cells that may serve as a source for renewal of classical neuroendocrine populations within the tumor. Targeting these resistant populations may be critical to re-establish response in relapsed SCLC, and these analyses identified high expression of several surface proteins that are currently under investigation as targets for antibody-drug conjugates in SCLC clinical trials, including B7H3, TROP2 and HER2 antibody drug conjugates. These data suggest that the acquisition of YAP1 expression delineates a particularly recalcitrant tumor cell population observed almost exclusively in relapsed SCLC that is capable of driving tumor persistence and treatment resistance. Clinically, these data underscore the importance of constraining transcriptional plasticity in the frontline management of SCLC, but also of developing therapies aimed specifically at emergent populations capable of driving resistance, as with the YAP1-high cells identified here. The emergence of YAP1 following resistance in SCLC and the observation of YAP1 as a common feature of other high-grade neuroendocrine carcinomas exclusive of SCLC, likely explains the initial mischaracterization of YAP1 as a subtype-defining feature of SCLC. Citation Format: C. Allison Stewart, Sarah M. Groves, Runsheng Wang, Kavya Ramkumar, Yuanxin Xi, Lixia Diao, Alejandra G. Serrano, Azusa Tanimoto, Ashley M. Victorian, Sayantan Bhattacharyya, Alexa J. Halliday, Neda Kalhor, Luisa Maren Soto, Pedro Filipe Da Rocha, Natalie Vokes, Loukia G. Karacosta, Jing Wang, John V. Heymach, Vito Quaranta, Bonnie Glisson, Lauren Averett Byers, Carl M. Gay. YAP1 defines a highly plastic, persister cell population in small cell lung cancer (SCLC) following relapse [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5864.

Patient-derived tumoroid models of pulmonary large-cell neuroendocrine carcinoma: a promising tool for personalized medicine and developing novel therapeutic strategies

Pulmonary large-cell neuroendocrine carcinoma (LCNEC), a disease with poor prognosis, is classified as pulmonary high-grade neuroendocrine carcinoma, along with small-cell lung cancer. However, given its infrequent occurrence, only a limited number of preclinical models have been established. Here, we established three LCNEC tumoroids for long-term culture. Whole-exome sequencing revealed that these tumoroids inherited genetic mutations from their parental tumors; two were classified as small-cell carcinoma (S-LCNEC) and one as non-small cell carcinoma (N-LCNEC). Xenografts from these tumoroids in immunodeficient mice mimicked the pathology of the parent LCNEC, and one reproduced the mixed-tissue types of combined LCNEC with a component of adenocarcinoma. Drug sensitivity tests using these LCNEC tumoroids enabled the evaluation of therapeutic agent efficacy. Based on translational research, we found that a CDK4/6 inhibitor might be effective for N-LCNEC and that Aurora A kinase inhibitors might be suitable for S-LCNEC or LCNEC with MYC amplification. These results highlight the value of preclinical tumoroid models in understanding the pathogenesis of rare cancers and developing treatments. LCNEC showed a high success rate in tumoroid establishment, indicating its potential application in personalized medicine.

NEN in a dish: A patient-derived organoid biobank illuminates potential novel therapeutic opportunities for neuroendocrine neoplasms

Neuroendocrine neoplasms are rare cancers with limited treatment options and preclinical models. In this issue of Cancer Cell, Dayton etal. establish a patient-derived tumor organoid biobank encompassing pulmonary low-grade neuroendocrine tumors (LNETs) and high-grade neuroendocrine carcinomas (LCNECs), identifying novel biomarker-dependent therapeutic vulnerabilities using niche perturbation and drug response assays.

Does subtyping of high-grade pulmonary neuroendocrine carcinomas have an impact on therapy selection?

Small cell lung cancer (SCLC) and large cell neuroendocrine carcinomas (LCNEC) are characterized by a rapid progressive course. Therapy for SCLC has not much changed for decades, and in LCNEC controversies exist, favoring either SCLC-like or non-small cell lung cancer (NSCLC)-like therapy. Three subtypes of SCLC identified in cell cultures, namely ASCL1, NeuroD1, and POU2F3 have been confirmed by immunohistochemistry. The fourth type based on the expression of YAP1 was questioned, and another type, inflamed SCLC, was proposed. SCLC and LCNEC samples were investigated by immunohistochemistry for different subtypes. Additionally, immunohistochemical markers as potential tools to identify patients who might respond to targeted treatment were investigated. For validation a biopsy set was added. ASCL1, NeuroD1, and POU2F3 were expressed in different percentages in SCLC and LCNEC. Similar percentages of expression were found in biopsies. ATOH was expressed in combination with one of the subtypes. YAP1 and TAZ were expressed in some SCLC and LCNEC cases. HES1 expression was seen in few cases. Predominantly stroma cells expressed programmed cell death ligand 1 (PD-L1). The dominant MYC protein was N-MYC. Aurora kinase A (AURKA) was expressed in the majority of both carcinomas, whereas fibroblast growth factor receptor 2 (FGFR2) in few. SCLC and LCNEC can be subtyped into ASCL1-, NeuroD1-, and POU2F3-positive types. AURKA expression and positivity for N-MYC protein was not associated with subtypes. AURKA and FGFR2 are both possible targets for inhibition in SCLC and LCNEC, but patients' selection should be based on expression of the enzyme. Combined chemo- and immunotherapy might be decided by PD-L1 staining of stroma cells.

Abstract B028: WEE1 inhibition enhances the antitumor immune response to PD-L1 blockade by the concomitant activation of STING and STAT1 pathways in small cell lung cancer

Abstract Background: Small cell lung cancer (SCLC) is a poorly immunogenic, high-grade neuroendocrine carcinoma arising in the lung. Immune checkpoint blockade (ICB) added to chemotherapy is now the standard upfront therapy for SCLC but leads to a modest increase in overall survival and progression-free survival. These modest benefits underscore the critical need to identify pathways and targets that can durably enhance the antitumor responses of ICB in SCLC. SCLC is characterized by a ubiquitous loss of TP53 which disrupts the G1-S cell cycle checkpoint and as a result, most SCLC is dependent on G2-M cell cycle checkpoint regulators including WEE1. We and others have shown that DNA damage response (DDR) components are overexpressed in SCLC and targeting DDR could be an effective therapeutic strategy in SCLC. Methods: In this study, we have performed WEE1 inhibition either alone or in combination with PD-L1 blockade in a panel of SCLC models. Results: We demonstrate that inhibition of WEE1 induces G2/M cell cycle arrest, DNA damage, and cytosolic DNA accumulation in SCLC models. We further show that WEE1 targeting activates the STING-TBK1-IRF3 pathway which increases type I interferons (IFN-α and IFN-β) and pro-inflammatory chemokines (CXCL10 and CCL5), facilitating an immune response via CD8+ cytotoxic T-cell infiltration. We further show that WEE1 inhibition concomitantly activates the STAT1 pathway, increasing IFN-γ and PD-L1 expression. Consistent with these findings, combined WEE1 inhibition (AZD1775) and PD-L1 blockade caused remarkable tumor regression, activation of type I and II interferon pathways, and infiltration of cytotoxic T-cells in multiple immunocompetent SCLC genetically engineered mouse models, including an aggressive model with stabilized MYC. Conclusions: Our study demonstrates the cell-autonomous and immune-stimulating activity of WEE1 inhibition in SCLC. Given the increasing importance of immunotherapy for the management of SCLC and that WEE1 inhibitors are already in clinical trials, combining a WEE1 inhibitor with PD-L1 blockade may offer a particularly attractive strategy for the treatment of SCLC and contribute to the rapid translation of this combination into the clinic. Citation Format: Triparna Sen. WEE1 inhibition enhances the antitumor immune response to PD-L1 blockade by the concomitant activation of STING and STAT1 pathways in small cell lung cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B028.

Small Cell Neuroendocrine Carcinoma of Bladder

Being a very rare histopathological type, neuroendocrine tumors are rather aggressive tumors that are usually diagnosed at an advanced stage. Neuroendocrine bladder tumor represents less than 1% of all bladder cancers. Though diagnosed in similar age period of 6th to 8th decade like urothelial carcinoma, its histopathological features and its poor prognosis are apart and rather similar to the small cell cancer of the lung. In this case report, we present a case of high-grade small cell neuroendocrine carcinoma of bladder in an elderly man.

Prognostic implications of synaptophysin, CD56, thyroid transcription factor-1, and Ki-67 in pulmonary high-grade neuroendocrine carcinomas

BackgroundThe correlation between the expression of immunohistochemical markers and the clinicopathological characteristics of pulmonary high-grade neuroendocrine carcinomas (HGNEC) and its impact on the clinical outcomes of individuals with HGNEC has not yet been explored. MethodsThis study enrolled patients diagnosed with HGNEC between April 2015 and July 2023. Based on the expression levels of synaptophysin (Syn), the neural cell adhesion molecule (CD56), thyroid transcription factor-1 (TTF-1), and Ki-67, a comprehensive analysis was conducted. This involved a comparison of clinicopathological characteristics, chemosensitivity, overall survival (OS), and progression-free survival (PFS). Furthermore, the study identified prognostic factors associated with patient survival through univariate and multivariate analyses. ResultsEighty-two patients were analyzed. Significant differences were identified in tumor stage (χ2 = 5.473, P = 0.019), lymphatic invasion (χ2 = 8.839, P = 0.003), and distant metastasis (χ2 = 5.473, P = 0.019), respectively, between the CD56 positive and negative groups. A significant difference in lymphatic invasion was observed (χ2 = 9.949, P = 0.002) between the CD56 positive and negative groups. A significant difference in vascular invasion was observed (χ2 = 5.106, P = 0.024) between the low and high Ki-67 groups. Compared to the Syn negative group, the Syn positive group had significantly shorter PFS (P = 0.006). Compared to the Syn negative group, the Syn positive group had significantly shorter OS (P = 0.004). The CD56 positive group also had significantly shorter OS than the CD56 negative group (P = 0.027). Univariate analysis revealed that tumor stage and Syn expression were associated with OS and PFS. Lymphatic invasion and CD56 expression were associated with OS. Multivariate analysis revealed that tumor stage was the strongest predictor of poor prognosis for OS (hazard ratio [HR] 0.551, 95 % confidence interval [CI] 0.328–0.927, P = 0.025) and PFS (HR 0.409, 95 % CI 0.247–0.676, P < 0.001). ConclusionsPositive expression of Syn was associated with reduced PFS and OS, while positive CD56 expression was correlated with a shorter OS in HGNEC. The TNM stage was an independent risk factor that significantly influenced PFS and OS in patients with HGNEC. More studies are needed to make further progress in future treatment.

Chemokine Receptor CXCR4 Radioligand Targeted Therapy Using 177Lutetium-pentixather for Pulmonary Neuroendocrine Cancers.

Intermediate to high-grade lung neuroendocrine tumors (NETs; i.e., atypical carcinoid tumors) and neuroendocrine carcinomas (NECs) are currently difficult to cure. These tumors were found to express the CXCR4 G-protein coupled receptor that can be targeted with radioligands. PCR and flow cytometric analysis of lung NET and NEC cell lines using an anti-CXCR4 antibody demonstrated that all cell lines tested expressed CXCR4. PET/CT imaging with 68Galium-pentixafor in mouse xenografts of NETs and NECs verified tumor targeting that was blocked by a CXCR4 agonist. Clonogenic survival analysis demonstrated a more than additive enhancement of killing when 1 μM auranofin (a thioredoxin reductase inhibitor) was used as a radiosensitizer in combination with 177Lu-pentixather (10 μCi). DMS273 small cell lung cancer xenografts in female nude mice treated with 25 μCi/g 177Lu-pentixather induced inhibition of tumor growth and resulted in an increase in overall survival without causing unacceptable normal tissue toxicities. Immunohistochemical staining of 95 retrospective human samples (containing 90 small cell lung carcinomas) demonstrated 84% CXCR4 positivity. In a multivariable analysis of this cohort that included age, gender, stage, primary site, SSTR2 status, and CXCR4 status, Cox regression models determined that only distant metastasis at presentation (P < 0.01) and a CXCR4 H-score >30 (P = 0.04) were significantly associated with reduced survival. Prospective clinical testing of patient tumors identified CXCR4-positivity in 76% of 21 NECs, 67% of 15 lung NETs (including 8 of 10 atypical carcinoids), and 0% of 25 non-lung NETs (including 5 NETS G3s). These data support the hypothesis that CXCR4-targeted theranostics can be utilized effectively for select NETs and NECs.

Pathologic diagnosis of lung cancer - recent developments.

Diagnosis of lung cancer has previously been based on the evaluation of resection specimen. However, approximately 80% of lung cancers are diagnosed in stage IV. Targeted therapy has changed the practice of pathology. Diagnosis is usually based on small biopsies or even needle aspirations. Subtyping is important, as a molecular classification has to be added. Molecular analysis has to be done in adenocarcinomas and on some of the rarer carcinoma types. Molecular analysis of squamous cell carcinomas should be done in never or former smokers, as they might present with targetable oncogenes. The same applies for adenosquamous carcinomas. Both high-grade neuroendocrine carcinomas should be subtyped. These subtypes might become relevant for new treatment options, currently investigated. Subtyping is done by immunohistochemistry with antibodies for ASCL1, NeuroD1, and POU2F3. In carcinoids, molecular investigation can better define cases with a higher risk of recurrence and metastasis. Diagnosis of lung cancer is most often done on small biopsies or cytological preparations. Only a minimal number of tissues or cellular material is used for diagnosis. A considerable portion is reserved for molecular analysis. Molecular investigation is important in adenocarcinomas, but also for other rare tumor types.

Targeting CXCR4 and Thioredoxin Reductase in High Grade Neuroendocrine Tumors & Neuroendocrine Carcinomas

Targeting CXCR4 and Thioredoxin Reductase in High Grade Neuroendocrine Tumors & Neuroendocrine Carcinomas

PET/CT scan improves detection of metastatic disease compared with CT scan alone in women with high-grade neuroendocrine cervical cancer: a NeCTuR study

ObjectiveTo determine the optimal imaging modality for women with high-grade neuroendocrine carcinoma of the cervix.MethodsWomen with high-grade neuroendocrine carcinoma of the cervix who had undergone a computed tomography (CT) scan...

Novel Mouse Cell Lines and In Vivo Models for Human High-Grade Neuroendocrine Lung Carcinoma, Small Cell Lung Carcinoma (SCLC), and Large Cell Neuroendocrine Carcinoma (LCNEC).

There is a clear need to expand the toolkit of adequate mouse models and cell lines available for preclinical studies of high-grade neuroendocrine lung carcinoma (small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC)). SCLC and LCNEC are two highly aggressive tumor types with dismal prognoses and few therapeutic options. Currently, there is an extreme paucity of material, particularly in the case of LCNEC. Given the lack of murine cell lines and transplant models of LCNEC, the need is imperative. In this study, we generated and examined new models of LCNEC and SCLC transplantable cell lines derived from our previously developed primary mouse LCNEC and SCLC tumors. RNA-seq analysis demonstrated that our cell lines and syngeneic tumors maintained the transcriptome program from the original transgenic primary tumor and displayed strong similarities to human SCLC or LCNEC. Importantly, the SCLC transplanted cell lines showed the ability to metastasize and mimic this characteristic of the human condition. In summary, we generated mouse cell line tools that allow further basic and translational research as well as preclinical testing of new treatment strategies for SCLC and LCNEC. These tools retain important features of their human counterparts and address the lack of LCNEC disease models.

Personalized prognostic prediction tool for high-grade neuroendocrine cervical cancer: a SEER database analysis and single-center validation

PurposeCervical high-grade neuroendocrine carcinoma (CHGNEC) is a rare but highly aggressive cancer. The purpose of this study is to develop a prognostic nomogram that can accurately predict the outcomes for CHGNEC patients.MethodsWe analyzed clinical data from the Surveillance, Epidemiology, and End Results (SEER) database of CHGNEC patients, including small-cell neuroendocrine carcinoma (SCNEC) and large-cell neuroendocrine carcinoma (LCNEC). We investigated patient characteristics and prognosis, and developed a prognostic nomogram model for cancer-specific survival in CHGNEC patients. External validation was conducted using real clinical cases from our hospital.ResultsOur study included 306 patients from SEER database, with a mean age of 49.9 ± 15.5 years. Most of the patients had SCNEC (86.9%). Among them, 170 died from the disease, while 136 either survived or died from other causes. Our final predictive model identified age at diagnosis, stage 1 status, stage 4 status, T1, N0, and surgery of the primary site as independent prognostic factors for CHGNEC. We validated our model using a group of 16 CHGNEC patients who underwent surgery at our center. The external validation showed that the prognostic nomogram had excellent discriminative ability, with an area under the receiver operating characteristic curve (AUC) of 0.76 (95% CI 0.49–1.00) for the prediction of 3-year cancer-specific survival (CSS) and an AUC of 0.85 (95% CI 0.62–1.00) for the prediction of 5-years CSS. The random survival forest model achieved an AUC of 0.80 (95% CI 0.56–1.00) for 3-years CSS and 0.91 (95% CI 0.72–1.00) for 5-years CSS, indicating its adequacy in predicting outcomes for CHGNEC patients.ConclusionOur study provides an excellent nomogram for predicting the prognosis of CHGNEC patients. The prognostic nomogram can be a useful tool for clinicians in identifying high-risk patients and making personalized treatment decisions.

Development and Validation of a Nomogram for Patients with Lung Large Cell Neuroendocrine Carcinoma

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rarely high-grade neuroendocrine carcinoma of the lung with features of both small cell and non-small cell lung cancer. We aim to construct a prognostic nomogram combined with the clinical features and treatment options to predict disease-specific survival (DSS), meanwhile, evaluating the role of prophylactic cranial irradiation (PCI) in LCNEC by subgroup analysis. A total of 713 patients diagnosed with LCNEC from the US National Cancer Institute's Surveillance Epidemiology and End Results (SEER) registry between 2010 and 2016. Cox proportional hazards analysis was conducted to choose the significant predictors of DSS. External validation was performed using 77 patients with LCNEC in the West China Hospital Sichuan University between 2010 and 2018, subgroup analysis was carried out for the whole brain radiotherapy (WBRT) and PCI population. The predictive accuracy and discriminative capability were estimated by the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve. The clinical applicability of the nomogram was verified through the decision curve analysis (DCA). Six independent risk factors for DSS were identified and integrated into the nomogram. The nomogram achieved good C- indexes of 0.803 and 0.767 in the training and validation group respectively. Moreover, the calibration curves of both cohorts for the probability of survival showed good agreement between prediction by nomogram and actual observation in 1-, 3- and 5-year DSS. The ROC curves demonstrated the prediction accuracy of the established nomogram (all AUC>0.8). DCA confirmed the better potential clinical practicality of the nomogram in the prediction of LCNEC survival than AJCC staging. A risk classification system was built which could perfectly classify LCNEC patients into high- and low-risk groups(p<0.001). Subgroup analysis showed that WBRT did not bring survival benefits, PCI appeared to have survival benefits in LCNEC patients without brain metastases (p>0.05). The prognostic nomogram developed in this study has certain prognostic value and clinical practicality for LCNEC patients. PCI might be investigated as a means of improving prognosis.

Exploring the molecular features and genetic prognostic factors of pulmonary high-grade neuroendocrine carcinomas

Molecular research on large-cell neuroendocrine carcinoma (LCNEC) and small-cell lung cancer (SCLC) has progressed significantly. However, there are still fewer molecular markers related to prognostic/therapeutic strategies for these conditions compared to those for adenocarcinoma. We therefore investigated the molecular characteristics of neuroendocrine carcinomas (NECs). We enrolled patients surgically diagnosed with NECs between 2011 and 2019, with complete follow-up records. All were analyzed using whole exome sequencing and p53/Rb immunohistochemistry (IHC). A total of 92 cases, comprising 45 pure SCLC, 15 combined SCLC, 27 pure LCNEC, and 5 combined LCNEC, were included. TP53 (78.3%) and RB1 (34.8%) were the most common molecular alterations, followed by KMT2D, LRP1B, FAT3, NCOR2, SPTA1, and NOTCH1. The mutation frequency for EGFR was 10.9%. Sixteen patients with LCNEC who had TP53/RB1 co-alterations were SCLC-like, while the remaining were NSCLC-like. There was no statistically significant difference between the groups regarding overall survival (OS; p=0.458) and progression-free survival (PFS; p=0.157). The frequency of the loss of Rb expression by IHC in SCLC-like LCNEC was 100%. Significant pathway alterations unique to SCLC included Notch and AMPK, while HIF-1 was enriched exclusively in LCNEC. NCOR2 mutation was linked to worse OS (p=0.029) and PFS (p=0.015), while wild-type SPTA1 was associated with poor PFS (p=0.018). IHC for Rb was reliable for predicting LCNEC molecular subtypes, indicating its clinical value. NCOR2 and SPTA1 alterations were identified as prognostic factors that may provide therapeutic targets for patients with NEC.

The role of neoadjuvant chemotherapy in patients with high-grade neuroendocrine carcinoma of the uterine cervix (1313)

The role of neoadjuvant chemotherapy in patients with high-grade neuroendocrine carcinoma of the uterine cervix (1313)