Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

Organotypic human lung bud microarrays identify BMP-dependent SARS-CoV-2 infection in lung cells.

Although lung disease is the primary clinical outcome in COVID-19 patients, how SARS-CoV-2 induces lung pathology remains elusive. Here we describe a high-throughput platform to generate self-organizing and commensurate human lung buds derived from hESCs cultured on micropatterned substrates. Lung buds resemble human fetal lungs and display proximodistal patterning of alveolar and airway tissue directed by KGF. These lung buds are susceptible to infection by SARS-CoV-2 and endemic coronaviruses and can be used to track cell type-specific cytopathic effects in hundreds of lung buds in parallel. Transcriptomic comparisons of infected lung buds and postmortem tissue of COVID-19 patients identified an induction of BMP signaling pathway. BMP activity renders lung cells more susceptible to SARS-CoV-2 infection and its pharmacological inhibition impairs infection by this virus. These data highlight the rapid and scalable access to disease-relevant tissue using lung buds that recapitulate key features of human lung morphogenesis and viral infection biology.

Quantitation of Murine Stroma and Selective Purification of the Human Tumor Component of Patient-Derived Xenografts for Genomic Analysis.

Patient-derived xenograft (PDX) mouse models are increasingly used for preclinical therapeutic testing of human cancer. A limitation in molecular and genetic characterization of PDX tumors is the presence of integral murine stroma. This is particularly problematic for genomic sequencing of PDX models. Rapid and dependable approaches for quantitating stromal content and purifying the malignant human component of these tumors are needed. We used a recently developed technique exploiting species-specific polymerase chain reaction (PCR) amplicon length (ssPAL) differences to define the fractional composition of murine and human DNA, which was proportional to the fractional composition of cells in a series of lung cancer PDX lines. We compared four methods of human cancer cell isolation: fluorescence-activated cell sorting (FACS), an immunomagnetic mouse cell depletion (MCD) approach, and two distinct EpCAM-based immunomagnetic positive selection methods. We further analyzed DNA extracted from the resulting enriched human cancer cells by targeted sequencing using a clinically validated multi-gene panel. Stromal content varied widely among tumors of similar histology, but appeared stable over multiple serial tumor passages of an individual model. FACS and MCD were superior to either positive selection approach, especially in cases of high stromal content, and consistently allowed high quality human-specific genomic profiling. ssPAL is a dependable approach to quantitation of murine stromal content, and MCD is a simple, efficient, and high yield approach to human cancer cell isolation for genomic analysis of PDX tumors.

A DLL3-targeted antibody-drug conjugate eradicates high-grade pulmonary neuroendocrine tumor-initiating cells in vivo.

The high-grade pulmonary neuroendocrine tumors, small cell lung cancer (SCLC) and large cell neuroendocrine carcinoma (LCNEC), remain among the most deadly malignancies. Therapies that effectively target and kill tumor-initiating cells (TICs) in these cancers should translate to improved patient survival. Patient-derived xenograft (PDX) tumors serve as excellent models to study tumor biology and characterize TICs. Increased expression of delta-like 3 (DLL3) was discovered in SCLC and LCNEC PDX tumors and confirmed in primary SCLC and LCNEC tumors. DLL3 protein is expressed on the surface of tumor cells but not in normal adult tissues. A DLL3-targeted antibody-drug conjugate (ADC), SC16LD6.5, comprised of a humanized anti-DLL3 monoclonal antibody conjugated to a DNA-damaging pyrrolobenzodiazepine (PBD) dimer toxin, induced durable tumor regression in vivo across multiple PDX models. Serial transplantation experiments executed with limiting dilutions of cells provided functional evidence confirming that the lack of tumor recurrence after SC16LD6.5 exposure resulted from effective targeting of DLL3-expressing TICs. In vivo efficacy correlated with DLL3 expression, and responses were observed in PDX models initiated from patients with both limited and extensive-stage disease and were independent of their sensitivity to standard-of-care chemotherapy regimens. SC16LD6.5 effectively targets and eradicates DLL3-expressing TICs in SCLC and LCNEC PDX tumors and is a promising first-in-class ADC for the treatment of high-grade pulmonary neuroendocrine tumors.

DNA methylation in small cell lung cancer defines distinct disease subtypes and correlates with high expression of EZH2.

Small cell lung cancer (SCLC) is an aggressive malignancy characterized by early metastasis, rapid development of resistance to chemotherapy and genetic instability. This study profiles DNA methylation in SCLC, patient-derived xenografts (PDX) and cell lines at single-nucleotide resolution. DNA methylation patterns of primary samples are distinct from those of cell lines, whereas PDX maintain a pattern closely consistent with primary samples. Clustering of DNA methylation and gene expression of primary SCLC revealed distinct disease subtypes among histologically indistinguishable primary patient samples with similar genetic alterations. SCLC is notable for dense clustering of high-level methylation in discrete promoter CpG islands, in a pattern clearly distinct from other lung cancers and strongly correlated with high expression of the E2F target and histone methyltransferase gene EZH2. Pharmacologic inhibition of EZH2 in a SCLC PDX markedly inhibited tumor growth.

Evaluation of azacitidine and entinostat as sensitization agents to cytotoxic chemotherapy in preclinical models of non-small cell lung cancer.

Recent clinical data in lung cancer suggests that epigenetically targeted therapy may selectively enhance chemotherapeutic sensitivity. There have been few if any studies rigorously evaluating this hypothesized priming effect. Here we describe a series of investigations testing whether epigenetic priming with azacitidine and entinostat increases sensitivity of NSCLC to cytotoxic agents. We noted no differences in chemosensitivity following treatment with epigenetic therapy in in vitro assays of viability and colony growth. Using cell line and patient derived xenograft (PDX) models, we also observed no change in responsiveness to cisplatin in vivo. In select models, we noted differential responses to irinotecan treatment in vivo. In vitro epigenetic therapy prior to tumor implantation abrogated response of H460 xenografts to irinotecan. Conversely, in vitro epigenetic therapy appeared to sensitize A549 xenografts (tumor growth inhibition 51%, vs. 22% in mock-pretreated control). In vivo epigenetic therapy enhanced the response of adenocarcinoma PDX to irinotecan. Taken together, these data do not support broadly applicable epigenetic priming in NSCLC. Priming effects may be context-specific, dependent on both tumor and host factors. Further preclinical study is necessary to determine whether, and in which contexts, priming with epigenetic therapy has potential to enhance chemotherapeutic efficacy in NSCLC patients.

MYC, MAX, and small cell lung cancer.

SUMMARY: In this issue of Cancer Discovery, Romero and colleagues identify somatic mutations and deletions of MAX, and also define what seem to be mutually exclusive alterations in MYC family members and other MYC-associated factors in small cell lung cancer. Taken together, these data highlight the importance of MYC signaling in small cell lung cancer and suggest possible avenues for therapeutic intervention.

Selective tropism of Seneca Valley virus for variant subtype small cell lung cancer.

We assessed the efficacy of Seneca Valley virus (SVV-001), a neuroendocrine cancer-selective oncolytic picornavirus, in primary heterotransplant mouse models of small cell lung cancer (SCLC), including three lines each of classic and variant SCLC. Half-maximal effective concentrations for cell lines derived from three variant heterotransplants ranged from 1.6×10(-3) (95% confidence interval [CI] = 1×10(-3) to 2.5×10(-3)) to 3.9×10(-3) (95% CI = 2.8×10(-3) to 5.5×10(-3)). Sustained tumor growth inhibition in vivo was only observed in variant lines (two-sided Student t test, P < .005 for each). Doses of 10(14) vp/kg were able to completely and durably eradicate tumors in a variant SCLC heterotransplant model in two of six mice. Gene expression profiling revealed that permissive lines are typified by lower expression of the early neurogenic transcription factor ASCL1 and, conversely, by higher expression of the late neurogenic transcription factor NEUROD1. This classifier demonstrates a sensitivity of .89, specificity of .92, and accuracy of .91. The NEUROD1 to ASCL1 ratio may serve as a predictive biomarker of SVV-001 efficacy.