A 10-gene progenitor cell signature predicts poor prognosis in lung adenocarcinoma

Activation of KrasG12D in Subset of Alveolar Type II Cells Enhances Cellular Plasticity in Lung Adenocarcinoma

We have previously identified alveolar type II cell as the cell-of-origin of KrasG12D-induced lung adenocarcinoma using cell lineage-specific inducible Cre mouse models. Using gain-of-function and loss-of-function genetic models, we discovered that active Notch signaling and low Sox2 levels dictate the ability of type II cells to proliferate and progress into lung adenocarcinoma upon KrasG12D activation. Here, we examine the phenotype of type II cells after Kras activation and find evidence for proliferation of cells that coexpress type I and type II markers. Three-dimensional organoid culture and transplantation studies determine that these dual-positive cells are highly plastic and tumor initiating in vivo. RNA sequencing analysis reveals that these dual-positive cells are enriched in Ras/MAPK, EGFR, and Notch pathways. Furthermore, the proliferation of these cells requires active Notch signaling and is inhibited by genetic/chemical Sox2 upregulation. Our findings could provide new therapeutic strategies to target KRAS-activated lung adenocarcinomas.

SIGNIFICANCE

Identification of progenitor like tumor-initiating cells in KRAS-mutant lung adenocarcinoma may allow development of novel targeted therapeutics.

Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer

BACKGROUND

Accurate survival stratification in early-stage non-small cell lung cancer (NSCLC) could inform the use of adjuvant therapy. We developed a clinically implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables.

METHODS

Gene expression profiles from 1106 nonsquamous NSCLCs were used for generation and internal validation of a nine-gene molecular prognostic index (MPI). A quantitative polymerase chain reaction (qPCR) assay was developed and validated on an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98). A prognostic score using clinical variables was generated using Surveillance, Epidemiology, and End Results data and combined with the MPI. All statistical tests for survival were two-sided.

RESULTS

The MPI stratified stage I patients into prognostic categories in three microarray and one FFPE qPCR validation cohorts (HR = 2.99, 95% CI = 1.55 to 5.76, P < .001 in stage IA patients of the largest microarray validation cohort; HR = 3.95, 95% CI = 1.24 to 12.64, P = .01 in stage IA of the qPCR cohort). Prognostic genes were expressed in distinct tumor cell subpopulations, and genes implicated in proliferation and stem cells portended poor outcomes, while genes involved in normal lung differentiation and immune infiltration were associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR = 3.43, 95% CI = 2.18 to 5.39, P < .001 in stage I patients of the largest microarray cohort; HR = 3.99, 95% CI = 1.67 to 9.56, P < .001 in stage I patients of the qPCR cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK.

CONCLUSION

The MPI incorporates genes expressed in the tumor and its microenvironment and can be implemented clinically using qPCR assays on FFPE tissues. A composite model integrating the MPI with clinical variables provides the most accurate risk stratification.

Developmental programs of lung epithelial progenitors: a balanced progenitor model

The daunting task of lung epithelium development is to transform a cluster of foregut progenitors into a three-dimensional (3D) tubular network with distinct cell types distributed at their appropriate locations. A complete understanding of lung development needs to address not only how, but also where, different cell types form. We propose that the lung epithelium forms through regulated deployment of three developmental programs: branching morphogenesis to expand progenitors and build a tree-like tubular network, airway differentiation to specify cells for the proximal conducting airways, and alveolar differentiation to specify cells for the peripheral gas exchange region. Each developmental program has its unique morphological features and molecular control mechanisms; their spatiotemporal coordination can be accounted for in a balanced progenitor model where progenitors balance between alternative developmental programs in response to spatiotemporal cues. This model integrates progenitor morphogenesis and differentiation, and provides new insights to lung immaturity in preterm birth and lung evolution. Advanced gene targeting and 3D imaging tools are needed to achieve a comprehensive understanding of lung epithelial progenitors on molecular, cellular, and morphological levels. For further resources related to this article, please visit the WIREs website.

CONFLICT OF INTEREST

The authors have declared no conflicts of interest for this article.

Wnt and Kras signaling-dark siblings in lung cancer

Aberrant Kras signaling is observed in a high percentage of human lung cancers while activating mutations in the Wnt/β-catenin signaling pathway are only rarely found. Our recent work has shown that the combined activation of both Kras and Wnt/β-catenin signaling leads to a dramatic increase in both tumor incidence and size. Moreover, lung tumors generated by the combined activation of both of these pathways exhibit a distinct phenotype similar to embryonic progenitors found in the developing lung. Thus, combinatorial activation of Kras and Wnt/β-catenin pathways leads to a significant increase in lung tumor formation characterized by a more progenitor like phenotype.

The Stem Cell Discovery Engine: an integrated repository and analysis system for cancer stem cell comparisons

Mounting evidence suggests that malignant tumors are initiated and maintained by a subpopulation of cancerous cells with biological properties similar to those of normal stem cells. However, descriptions of stem-like gene and pathway signatures in cancers are inconsistent across experimental systems. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), we have developed the Stem Cell Discovery Engine (SCDE)-an online database of curated CSC experiments coupled to the Galaxy analytical framework. The SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. Our initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. The SCDE is available at http://discovery.hsci.harvard.edu.