Project description:Purpose: Although immunotherapy is the mainstay of therapy for advanced non-small cell lung cancer (NSCLC), robust biomarkers of clinical response are lacking. The heterogeneity of clinical responses together with the limited value of radiographic response assessments to timely and accurately predict therapeutic effect -especially in the setting of stable disease- call for the development of molecularly-informed real-time minimally invasive predictive biomarkers. In addition to capturing tumor regression, liquid biopsies may be informative in evaluating immune-related adverse events (irAEs). Experimental design: We investigated longitudinal changes in circulating tumor DNA (ctDNA) in patients with metastatic NSCLC who received immunotherapy-based regimens. Using ctDNA targeted error-correction sequencing together with matched sequencing of white blood cells and tumor tissue, we tracked serial changes in cell-free tumor load (cfTL) and determined molecular response for each patient. Peripheral T-cell repertoire dynamics were serially assessed and evaluated together with plasma protein expression profiles. Results: Molecular response, defined as complete clearance of cfTL, was significantly associated with progression-free (log-rank p=0.0003) and overall survival (log-rank p=0.01) and was particularly informative in capturing differential survival outcomes among patients with radiographically stable disease. For patients who developed irAEs, peripheral blood T-cell repertoire reshaping, assessed by significant TCR clonotypic expansions and regressions were noted on-treatment. Conclusions: Molecular responses assist with interpretation of heterogeneous clinical responses especially for patients with stable disease. Our complementary assessment of the tumor and immune compartments by liquid biopsies provides an approach for monitoring of clinical benefit and immune-related toxicities for patients with NSCLC receiving immunotherapy. Statement of translational relevance: Longitudinal dynamic changes in cell-free tumor load and reshaping of the peripheral T-cell repertoire capture clinical outcomes and immune-related toxicities during immunotherapy for patients with non-small cell lung cancer.

Project description:The presence of tumor cells in effusions within serosal cavities is a clinical manifestation of advanced-stage cancer and is generally associated with poor survival. Identifying molecular targets may help to design efficient treatments to eradicate these aggressive cancer cells and improve patient survival. Using a state-of-the-art Taqman-based qRT-PCR assay, we investigated the multidrug resistance (MDR) transcriptome of 32 unpaired ovarian serous carcinoma effusion samples obtained at diagnosis or at disease recurrence following chemotherapy. MDR genes were selected a priori based on an extensive curation of the literature published during the last three decades. We found three gene signatures with a statistically significant correlation with overall survival (OS), response to treatment (complete response - CR vs. other), and progression free survival (PFS). The median log-rank p-values for the signatures were 0.023, 0.034, and 0.008, respectively. No correlation was found with residual tumor status after cytoreductive surgery, treatment (with or without chemotherapy) and stage defined according to the International Federation of Gynecology and Obstetrics. Further analyses demonstrated that gene expression alone can effectively predict the survival outcome of women with ovarian serous carcinoma (OS: log-rank p=0.0000 and PFS: log-rank p=0.002). Interestingly, the signature for overall survival is the same in patients at first presentation and those who had chemotherapy and relapsed. This pilot study highlights two new gene signatures that may help in optimizing the treatment for ovarian carcinoma patients with effusions. In the study presented here, effusion samples were obtained from 32 patients diagnosed with serous ovarian carcinoma (n=25), primary peritoneal serous carcinoma (n=6) or tubal serous carcinoma (n=1). They were accrued at the Division of Pathology in the Norwegian Radium Hospital from 2000-2006. RNA was used to study the expression profile of 381 multidrug resistant-related genes.

Project description:Background: Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. Methods: Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 59 patients with operable laryngeal cancer. All patients were treated locally with surgery, with or without radiation therapy. We performed Cox regression proportional hazards modeling to identify multigene predictors of recurrence. The end-point of our analysis was disease-free survival (DFS). Gene models were directly validated in a separate, similarly treated cohort of 50 patients using Affymetrix chips. In an attempt to further validate our results, we profiled 12 selected genes of our model in formalin-fixed tumor tissues from an independent cohort of 75 patients, using quantitative real time-polymerase chain reaction (qRT-PCR). Results: We focused on genes univariately associated with DFS (p<0.05) in the training set. Among several gene models comprising different numbers of genes, a 30-gene model demonstrated optimal performance (log-rank, p<0.001). We directly applied these gene models to the validation set, after adjusting for non-biological experimental variability, and observed similar results. Specifically, median DFS, as predicted by the 30-gene model, was 34 and 80 months for high- and low-risk patients, respectively (p=0.01). Hazard Ratio (HR) for recurrence for the high-risk group was 3.87 (95% CI 1.28-11.73, p=0.017). Furthermore, unsupervised hierarchical clustering of the 75 patients, based on the qRT-PCR 12-gene profile, yielded two groups, which differed significantly in DFS (log-rank, p=0.027). HR= for recurrence was 2.26, (95% CI 1.08-4.76, p=0.031). Conclusion: We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. Thus, patients with unfavorable prognosis, when accurately identified, could be ideal candidates for the application of more aggressive treatment modalities. Training set comprises 59 samples and validation set 50 samples

Project description:Background: Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. Methods: Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 59 patients with operable laryngeal cancer. All patients were treated locally with surgery, with or without radiation therapy. We performed Cox regression proportional hazards modeling to identify multigene predictors of recurrence. The end-point of our analysis was disease-free survival (DFS). Gene models were directly validated in a separate, similarly treated cohort of 50 patients using Affymetrix chips. In an attempt to further validate our results, we profiled 12 selected genes of our model in formalin-fixed tumor tissues from an independent cohort of 75 patients, using quantitative real time-polymerase chain reaction (qRT-PCR). Results: We focused on genes univariately associated with DFS (p<0.05) in the training set. Among several gene models comprising different numbers of genes, a 30-gene model demonstrated optimal performance (log-rank, p<0.001). We directly applied these gene models to the validation set, after adjusting for non-biological experimental variability, and observed similar results. Specifically, median DFS, as predicted by the 30-gene model, was 34 and 80 months for high- and low-risk patients, respectively (p=0.01). Hazard Ratio (HR) for recurrence for the high-risk group was 3.87 (95% CI 1.28-11.73, p=0.017). Furthermore, unsupervised hierarchical clustering of the 75 patients, based on the qRT-PCR 12-gene profile, yielded two groups, which differed significantly in DFS (log-rank, p=0.027). HR= for recurrence was 2.26, (95% CI 1.08-4.76, p=0.031). Conclusion: We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. Thus, patients with unfavorable prognosis, when accurately identified, could be ideal candidates for the application of more aggressive treatment modalities.

Project description:The study was designed to identify the molecular changes that occur in EGFR mutant NSCLCs that become resistant to TKI by transforming to SCLC. Tyrosine kinase inhibitors (TKIs) are effective treatments for non-small cell lung cancers (NSCLCs) with epidermal growth factor receptor (EGFR) mutations. However, they do not lead to cures, and, on average, relapse occurs after one year of continuous treatment. In a subset of patients, a fundamental histological transformation from NSCLC to small cell lung cancer (SCLC) is observed in the resistant cancers, but the molecular changes associated with this transformation remain unknown. Analysis of a cohort of tumor samples and cell lines derived from resistant EGFR mutant patients with SCLC transformation revealed that RB is lost in 100% of these cases, but rarely in those that remain NSCLC. Global changes in gene expression, including increased neuroendocrine marker expression and absence of EGFR expression, are observed in cancers that transformed to SCLC. Consistent with their genetic and epigenetic similarities to classical SCLC, cell lines derived from resistant EGFR mutant SCLC biopsies are substantially more sensitive to ABT-263 treatment compared to those derived from resistant EGFR mutant NSCLCs. Together, these findings suggest that despite developing initially as EGFR mutant adenocarcinomas, this subset of resistant cancers ultimately take on many of the molecular and phenotypic characteristics of classical SCLC. The patient-derived cell line models MGH119, MGH121, MGH125, MGH126, MGH131-1, MGH131-2, MGH134 and MGH156 were developed on collagen coated plates in ACL4 medium and transferred to RPMI. MGH157 was developed initially in RPMI. The cell line MGH141 was derived using the feeder system with irradiated fibroblasts (5000 rad) from normal patient tissue. When a tumor cell majority was observed it was passaged off of the feeder layer and later transferred to RPMI medium for experiments. The development of a model was considered complete when it was independent of the feeder system, free of stromal cells, and determined to maintain known patient tumor mutations. MGH119-R was derived in vitro from the treatment naive model, MGH119, through in vitro exposure to gefitinib, escalating from 10nM to a final concentration of 1Î¼M.

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Dynamics of sequence and structural cell-free DNA landscapes in small-cell lung cancer

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