The Cancers-Specific Survival of Metastatic Pulmonary Carcinoids and Sites of Distant Metastasis: A Population-Based Study

Background: Lung cancer is the leading cause of cancer-related deaths and pulmonary carcinoids (PCs) account for almost 2% of all pulmonary malignancies. However, few published articles have reported prognosis and related factors of pulmonary carcinoid patients. Material and Method: The Surveillance, Epidemiology, and End Results (SEER) database was used to collect data of patients diagnosed with metastatic PCs from 2010 to 2016. The prognosis and survival of these patients were compared by employing Cox proportional hazards and the Kaplan-Meier survival analysis. Results: A total of 1763 patients were analyzed. The liver (668, 25.6%) was shown to be the most common metastatic site in the isolated organ metastasis cohort, followed by the lung (636, 24.4%), bone (562, 21.6%), and brain (460, 17.6%). Among the patients, the tumor metastasized to a single distant site included the liver, bone, lung, and brain. Cancer-specific survival (CSS) in metastatic PCs is determined by the site of metastasis and the total number of such sites. Pulmonary carcinoid patients with isolated liver metastasis manifested more favorable survival rates in comparison to patients having isolated metastasis in the lung, brain, or bone. The median CSS was 45, 7, 6, 5 months ( P = 0.011). The number of distant metastatic sites and the location of distant metastasis were found to be independent risk factors for CSS. For patients with distant isolated metastasis, liver metastasis ( P < 0.0001) had better CSS in comparison to those with bone metastasis. When compared to patients whose carcinoids had metastasized to the bones, patients with a brain ( P = 0.273) or lung ( P = 0.483) metastasis had the same CSS. Conclusion: Cancer-specific survival in metastatic PCs depends on the site of metastasis and the total number of such locations. PC patients with isolated liver metastasis manifested more favorable survival in comparison to patients with isolated metastasis in the lung, brain, or bone.

An unusual 7 cm large typical carcinoid managed by surgery: a rare case report

Carcinoid tumors of the lung are uncommon group of pulmonary neoplasms. Most common site is gastrointestinal tract followed by lungs. Typical pulmonary carcinoids are usually small as described in various case series size of a typical carcinoid may ranges from 0.5-2 cm and are managed surgically. Here we present a case of unusually large typical carcinoid measuring up to 7 cm which was managed surgically.

A molecular map of lung neuroendocrine neoplasms

Background Lung neuroendocrine neoplasms (LNENs) are rare solid cancers, with most genomic studies including a limited number of samples. Recently, generating the first multi-omic dataset for atypical pulmonary carcinoids and the first methylation dataset for large-cell neuroendocrine carcinomas led us to the discovery of clinically relevant molecular groups, as well as a new entity of pulmonary carcinoids (supra-carcinoids). Results To promote the integration of LNENs molecular data, we provide here detailed information on data generation and quality control for whole-genome/exome sequencing, RNA sequencing, and EPIC 850K methylation arrays for a total of 84 patients with LNENs. We integrate the transcriptomic data with other previously published data and generate the first comprehensive molecular map of LNENs using the Uniform Manifold Approximation and Projection (UMAP) dimension reduction technique. We show that this map captures the main biological findings of previous studies and can be used as reference to integrate datasets for which RNA sequencing is available. The generated map can be interactively explored and interrogated on the UCSC TumorMap portal (https://tumormap.ucsc.edu/?p=RCG_lungNENomics/LNEN). The data, source code, and compute environments used to generate and evaluate the map as well as the raw data are available, respectively, in a Nextjournal interactive notebook (https://nextjournal.com/rarecancersgenomics/a-molecular-map-of-lung-neuroendocrine-neoplasms/) and at the EMBL-EBI European Genome-phenome Archive and Gene Expression Omnibus data repositories. Conclusions We provide data and all resources needed to integrate them with future LNENs transcriptomic studies, allowing meaningful conclusions to be drawn that will eventually lead to a better understanding of this rare understudied disease.