The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate. The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways. Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.

A B S T R A C T PurposeAdjuvant chemotherapy for resected non-small-cell lung cancer (NSCLC) is now accepted on the basis of several randomized clinical trials (RCTs) that demonstrated improved survival. Although there is strong evidence that adjuvant chemotherapy is effective in stages II and IIIA NSCLC, its utility in stage IB disease is unclear. This report provides a mature analysis of Cancer and Leukemia Group B (CALGB) 9633, the only RCT designed specifically for stage IB NSCLC. Patients and MethodsWithin 4 to 8 weeks of resection, patients were randomly assigned to adjuvant chemotherapy or observation. Eligible patients had pathologically confirmed T2N0 NSCLC and had undergone lobectomy or pneumonectomy. Chemotherapy consisted of paclitaxel 200 mg/m 2 intravenously over 3 hours and carboplatin at an area under the curve dose of 6 mg/mL per minute intravenously over 45 to 60 minutes every 3 weeks for four cycles. The primary end point was overall survival. ResultsThree hundred-forty-four patients were randomly assigned. Median follow-up was 74 months. Groups were well-balanced with regard to demographics, histology, and extent of surgery. Grades 3 to 4 neutropenia were the predominant toxicity; there were no treatment-related deaths. Survival was not significantly different (hazard ratio [HR], 0.83; CI, 0.64 to 1.08; P ϭ .12). However, exploratory analysis demonstrated a significant survival difference in favor of adjuvant chemotherapy for patients who had tumors Ն 4 cm in diameter (HR, 0.69; CI, 0.48 to 0.99; P ϭ .043). ConclusionBecause a significant survival advantage was not observed across the entire cohort, adjuvant chemotherapy should not be considered standard care in stage IB NSCLC. Given the magnitude of observed survival differences, CALGB 9633 was underpowered to detect small but clinically meaningful improvements. A statistically significant survival advantage for patients who had tumors Ն 4 cm supports consideration of adjuvant paclitaxel/carboplatin for stage IB patients who have large tumors.

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.

Video-assisted thoracoscopic lobectomy is associated with a lower incidence of complications compared with lobectomy via thoracotomy. For appropriate candidates, video-assisted thoracoscopic lobectomy may be the preferred strategy for appropriately selected patients with lung cancer.

Using in vitro drug sensitivity data coupled with Affymetrix microarray data, we developed gene expression signatures that predict sensitivity to individual chemotherapeutic drugs. Each signature was validated with response data from an independent set of cell line studies. We further show that many of these signatures can accurately predict clinical response in individuals treated with these drugs. Notably, signatures developed to predict response to individual agents, when combined, could also predict response to multidrug regimens. Finally, we integrated the chemotherapy response signatures with signatures of oncogenic pathway deregulation to identify new therapeutic strategies that make use of all available drugs. The development of gene expression profiles that can predict response to commonly used cytotoxic agents provides opportunities to better use these drugs, including using them in combination with existing targeted therapies.

The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC.

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