Rachel score: a nomogram model for predicting the prognosis of lung neuroendocrine tumors.

BACKGROUND: Lung NET, classified in typical carcinoids (TC) and atypical carcinoids (AC), are highly heterogeneous in their biology and prognosis. The histological subtype and TNM stage are well-established prognostic factors for lung NET. In a previous work by our group, we demonstrated a significant impact of laterality on lung NET survival outcomes. MATERIALS AND METHODS: We developed a nomogram that integrates relevant prognostic factors to predict lung NET outcomes. By adding the scores for each of the variables included in the model, it was possible to obtain a prognostic score (Rachel score). Wilcoxon non-parametric statistical test was applied among parameters and Harrell's concordance index was used to measure the models' predictive power. To test the discriminatory power and the predictive accuracy of the model, we calculated Gonen and Heller concordance index. Time-dependent ROC curves and their area under the curve (AUC) were used to evaluate the models' predictive performance. RESULTS: By applying Rachel score, we were able to identify three prognostic groups (specifically, high, medium and low risk). These three groups were associate to well-defined ranges of points according to the obtained nomogram (I: 0-90, II: 91-130; III: > 130 points), providing a useful tool for prognostic stratification. The overall survival (OS) and progression free survival (PFS) Kaplan-Meier curves confirmed significant differences (p < 0.0001) among the three groups identified by Rachel score. CONCLUSIONS: A prognostic nomogram was developed, incorporating variables with significant impact on lung NET survival. The nomogram showed a satisfactory and stable ability to predict OS and PFS in this population, confirming the heterogeneity beyond the histopathological diagnosis of TC vs AC.

KEAP1-driven co-mutations in lung adenocarcinoma unresponsive to immunotherapy despite high tumor mutational burden.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have demonstrated significant overall survival (OS) benefit in lung adenocarcinoma (LUAD). Nevertheless, a remarkable interpatient heterogeneity characterizes immunotherapy efficacy, regardless of programmed death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). KEAP1 mutations are associated with shorter survival in LUAD patients receiving chemotherapy. We hypothesized that the pattern of KEAP1 co-mutations and mutual exclusivity may identify LUAD patients unresponsive to immunotherapy. PATIENTS AND METHODS: KEAP1 mutational co-occurrences and somatic interactions were studied in the whole MSKCC LUAD dataset. The impact of coexisting alterations on survival outcomes in ICI-treated LUAD patients was verified in the randomized phase II/III POPLAR/OAK trials (blood-based sequencing, bNGS cohort, N = 253). Three tissue-based sequencing studies (Rome, MSKCC and DFCI) were used for independent validation (tNGS cohort, N = 289). Immunogenomic features were analyzed using The Cancer Genome Atlas (TCGA) LUAD study. RESULTS: On the basis of KEAP1 mutational co-occurrences, we identified four genes potentially associated with reduced efficacy of immunotherapy (KEAP1, PBRM1, SMARCA4 and STK11). Independent of the nature of co-occurring alterations, tumors with coexisting mutations (CoMut) had inferior survival as compared with single-mutant (SM) and wild-type (WT) tumors (bNGS cohort: CoMut versus SM log-rank P = 0.048, CoMut versus WT log-rank P < 0.001; tNGS cohort: CoMut versus SM log-rank P = 0.037, CoMut versus WT log-rank P = 0.006). The CoMut subset harbored higher TMB than the WT disease and the adverse significance of coexisting alterations was maintained in LUAD with high TMB. Significant immunogenomic differences were observed between the CoMut and WT groups in terms of core immune signatures, T-cell receptor repertoire, T helper cell signatures and immunomodulatory genes. CONCLUSIONS: This study indicates that coexisting alterations in a limited set of genes characterize a subset of LUAD unresponsive to immunotherapy and with high TMB. An immune-cold microenvironment may account for the clinical course of the disease.

Che-1 modulates the decision between cell cycle arrest and apoptosis by its binding to p53.

The tumor suppressor p53 is mainly involved in the transcriptional regulation of a large number of growth-arrest- and apoptosis-related genes. However, a clear understanding of which factor/s influences the choice between these two opposing p53-dependent outcomes remains largely elusive. We have previously described that in response to DNA damage, the RNA polymerase II-binding protein Che-1/AATF transcriptionally activates p53. Here, we show that Che-1 binds directly to p53. This interaction essentially occurs in the first hours of DNA damage, whereas it is lost when cells undergo apoptosis in response to posttranscriptional modifications. Moreover, Che-1 sits in a ternary complex with p53 and the oncosuppressor Brca1. Accordingly, our analysis of genome-wide chromatin occupancy by p53 revealed that p53/Che1 interaction results in preferential transactivation of growth arrest p53 target genes over its pro-apoptotic target genes. Notably, exposure of Che-1(+/-) mice to ionizing radiations resulted in enhanced apoptosis of thymocytes, compared with WT mice. These results confirm Che-1 as an important regulator of p53 activity and suggest Che-1 to be a promising yet attractive drug target for cancer therapy.