Viswam S. Nair

The prognostic landscape of genes and infiltrating immune cells across human cancers

Molecular profiles of tumors and tumor-associated cells hold great promise as biomarkers of clinical outcomes. However, existing data sets are fragmented and difficult to analyze systematically. Here we present a pan-cancer resource and meta-analysis of expression signatures from ∼18,000 human tumors with overall survival outcomes across 39 malignancies. By using this resource, we identified a forkhead box MI (FOXM1) regulatory network as a major predictor of adverse outcomes, and we found that expression of favorably prognostic genes, including KLRB1 (encoding CD161), largely reflect tumor-associated leukocytes. By applying CIBERSORT, a computational approach for inferring leukocyte representation in bulk tumor transcriptomes, we identified complex associations between 22 distinct leukocyte subsets and cancer survival. For example, tumor-associated neutrophil and plasma cell signatures emerged as significant but opposite predictors of survival for diverse solid tumors, including breast and lung adenocarcinomas. This resource and associated analytical tools (http://precog.stanford.edu) may help delineate prognostic genes and leukocyte subsets within and across cancers, shed light on the impact of tumor heterogeneity on cancer outcomes, and facilitate the discovery of biomarkers and therapeutic targets.

Clinical Outcome Prediction by MicroRNAs in Human Cancer: A Systematic Review

BACKGROUND MicroRNA (miR) expression may have prognostic value for many types of cancers. However, the miR literature comprises many small studies. We systematically reviewed and synthesized the evidence. METHODS Using MEDLINE (last update December 2010), we identified English language studies that examined associations between miRs and cancer prognosis using tumor specimens for more than 10 patients during classifier development. We included studies that assessed a major clinical outcome (nodal disease, disease progression, response to therapy, metastasis, recurrence, or overall survival) in an agnostic fashion using either polymerase chain reaction or hybridized oligonucleotide microarrays. RESULTS Forty-six articles presenting results on 43 studies pertaining to 20 different types of malignancy were eligible for inclusion in this review. The median study size was 65 patients (interquartile range [IQR] = 34-129), the median number of miRs assayed was 328 (IQR = 250-470), and overall survival or recurrence were the most commonly measured outcomes (30 and 19 studies, respectively). External validation was performed in 21 studies, 20 of which reported at least one nominally statistically significant result for a miR classifier. The median hazard ratio for poor outcome in externally validated studies was 2.52 (IQR = 2.26-5.40). For all classifier miRs in studies that evaluated overall survival across diverse malignancies, the miRs most frequently associated with poor outcome after accounting for differences in miR assessment due to platform type were let-7 (decreased expression in patients with cancer) and miR 21 (increased expression). CONCLUSIONS MiR classifiers show promising prognostic associations with major cancer outcomes and specific miRs are consistently identified across diverse studies and platforms. These types of classifiers require careful external validation in large groups of cancer patients that have adequate protection from bias. -

Prognostic PET 18F-FDG Uptake Imaging Features Are Associated with Major Oncogenomic Alterations in Patients with Resected Non–Small Cell Lung Cancer

Although 2[18F]fluoro-2-deoxy-d-glucose (FDG) uptake during positron emission tomography (PET) predicts post-surgical outcome in patients with non-small cell lung cancer (NSCLC), the biologic basis for this observation is not fully understood. Here, we analyzed 25 tumors from patients with NSCLCs to identify tumor PET-FDG uptake features associated with gene expression signatures and survival. Fourteen quantitative PET imaging features describing FDG uptake were correlated with gene expression for single genes and coexpressed gene clusters (metagenes). For each FDG uptake feature, an associated metagene signature was derived, and a prognostic model was identified in an external cohort and then tested in a validation cohort of patients with NSCLC. Four of eight single genes associated with FDG uptake (LY6E, RNF149, MCM6, and FAP) were also associated with survival. The most prognostic metagene signature was associated with a multivariate FDG uptake feature [maximum standard uptake value (SUV(max)), SUV(variance), and SUV(PCA2)], each highly associated with survival in the external [HR, 5.87; confidence interval (CI), 2.49-13.8] and validation (HR, 6.12; CI, 1.08-34.8) cohorts, respectively. Cell-cycle, proliferation, death, and self-recognition pathways were altered in this radiogenomic profile. Together, our findings suggest that leveraging tumor genomics with an expanded collection of PET-FDG imaging features may enhance our understanding of FDG uptake as an imaging biomarker beyond its association with glycolysis.

PET scan 18F-fluorodeoxyglucose uptake and prognosis in patients with resected clinical stage IA non-small cell lung cancer.

OBJECTIVE Our objective was to examine the association between (18)F-fluorodeoxyglucose (FDG) uptake on PET scan and prognosis in patients with surgically treated, clinical stage IA non-small cell lung cancer (NSCLC). METHODS We reviewed data collection forms and Veterans Affairs administrative records of 75 patients with surgically treated, stage IA NSCLC who were enrolled in a prospective study of PET imaging from 1999 to 2001. We used Cox proportional hazards analysis to examine the association between FDG uptake and survival 4 years following enrollment. RESULTS Most patients were men (97%), and the mean age was 68 +/- 9 years. Almost half of the patients (44%) had adenocarcinoma, and 35% underwent a sublobar resection. The mean maximum standardized uptake value (SUVmax) was 4.9 +/- 2.5 in survivors and 7.1 +/- 3.9 in nonsurvivors (P = .045). Before and after adjustment for age, tumor size, histology, and type of resection, the hazard of death was significantly higher in patients with squamous cell histology (adjusted hazard ratio [HR], 4.54; 95% CI, 1.09-18.9) and those with higher degrees of FDG uptake (adjusted HR, 1.21 per 1 unit increment; 95% CI, 1.01-1.45). At a threshold value of 5 for SUVmax, 34 of 39 patients (87%) with low FDG uptake survived, compared with only 24 of 36 patients (67%) with high FDG uptake (P = .04). Visual assessment of FDG uptake was not associated with an increased hazard of death (HR 0.66; 95% CI, 0.19-2.29). CONCLUSIONS High FDG uptake as measured by SUVmax identifies individuals with clinical stage IA NSCLC who are at increased risk of death following surgery. Such high-risk patients may be good candidates for participation in future trials of adjuvant therapy.

Positron Emission Tomography 18F-Fluorodeoxyglucose Uptake and Prognosis in Patients with Surgically Treated, Stage I Non-small Cell Lung Cancer: A Systematic Review

Background: 18F-fluorodeoxyglucose (FDG) uptake holds potential as a noninvasive biomarker in patients with non-small cell lung cancer (NSCLC). We aimed to investigate the association between tumor FDG uptake and survival in patients with surgically resected, stage I NSCLC. Methods: We used systematic methods to identify studies for inclusion, assess methodological quality, and abstract relevant data about study design and results. Results: Our literature search identified 1578 citations, of which nine retrospective, cross-sectional studies met eligibility criteria. In all studies, higher degrees of FDG uptake in the primary tumor were associated with worse overall or disease free survival after 2 to 5 years of follow-up, but these differences were statistically significant in only five studies. Across studies, the median overall or disease free survival was 70% for patients with higher FDG uptake compared with 88% for patients with lower FDG uptake. In three studies that performed multivariable analysis, the adjusted hazard of death or recurrence was 1.9 to 8.6 times greater in patients with higher FDG uptake. Conclusion: Current evidence suggests that increasing tumor FDG uptake is associated with worse survival in patients with stage I NSCLC. FDG uptake has the potential to be used as a biomarker for identifying stage I patients who are at increased risk of death or recurrence and therefore could identify candidates for participation in future trials of adjuvant therapy.

Design and Analysis for Studying microRNAs in Human Disease: A Primer on -Omic Technologies

microRNAs (miRNAs) are fundamental to cellular biology. Although only approximately 22 bases long, miRNAs regulate complex processes in health and disease, including human cancer. Because miRNAs are highly stable in circulation when compared with several other classes of nucleic acids, they have generated intense interest as clinical biomarkers in diverse epidemiologic studies. As with other molecular biomarker fields, however, miRNA research has become beleaguered by pitfalls related to terminology and classification; procedural, assay, and study cohort heterogeneity; and methodological inconsistencies. Together, these issues have led to both false-positive and potentially false-negative miRNA associations. In this review, we summarize the biological rationale for studying miRNAs in human disease with a specific focus on circulating miRNAs, which highlight some of the most challenging topics in the field to date. Examples from lung cancer are used to illustrate the potential utility and some of the pitfalls in contemporary miRNA research. Although the field is in its infancy, several important lessons have been learned relating to cohort development, sample preparation, and statistical analysis that should be considered for future studies. The goal of this primer is to equip epidemiologists and clinical researchers with sound principles of study design and analysis when using miRNAs.

NF-κB protein expression associates with 18F-FDG PET tumor uptake in non-small cell lung cancer: A radiogenomics validation study to understand tumor metabolism

INTRODUCTION We previously demonstrated that NF-κB may be associated with (18)F-FDG PET uptake and patient prognosis using radiogenomics in patients with non-small cell lung cancer (NSCLC). To validate these results, we assessed NF-κB protein expression in an extended cohort of NSCLC patients. METHODS We examined NF-κBp65 by immunohistochemistry (IHC) using a Tissue Microarray. Staining intensity was assessed by qualitative ordinal scoring and compared to tumor FDG uptake (SUVmax and SUVmean), lactate dehydrogenase A (LDHA) expression (as a positive control) and outcome using ANOVA, Kaplan Meier (KM), and Cox-proportional hazards (CPH) analysis. RESULTS 365 tumors from 355 patients with long-term follow-up were analyzed. The average age for patients was 67±11 years, 46% were male and 67% were ever smokers. Stage I and II patients comprised 83% of the cohort and the majority had adenocarcinoma (73%). From 88 FDG PET scans available, average SUVmax and SUVmean were 8.3±6.6, and 3.7±2.4 respectively. Increasing NF-κBp65 expression, but not LDHA expression, was associated with higher SUVmax and SUVmean (p=0.03 and 0.02 respectively). Both NF-κBp65 and positive FDG uptake were significantly associated with more advanced stage, tumor histology and invasion. Higher NF-κBp65 expression was associated with death by KM analysis (p=0.06) while LDHA was strongly associated with recurrence (p=0.04). Increased levels of combined NF-κBp65 and LDHA expression were synergistic and associated with both recurrence (p=0.04) and death (p=0.03). CONCLUSIONS NF-κB IHC was a modest biomarker of prognosis that associated with tumor glucose metabolism on FDG PET when compared to existing molecular correlates like LDHA, which was synergistic with NF-κB for outcome. These findings recapitulate radiogenomics profiles previously reported by our group and provide a methodology for studying tumor biology using computational approaches.

Circulating Tumor Microemboli Diagnostics for Patients with Non–Small-Cell Lung Cancer

Introduction: Circulating tumor microemboli (CTM) are potentially important cancer biomarkers, but using them for cancer detection in early-stage disease has been assay limited. We examined CTM test performance using a sensitive detection platform to identify stage I non–small-cell lung cancer (NSCLC) patients undergoing imaging evaluation. Methods: First, we prospectively enrolled patients during 18F-FDG PET-CT imaging evaluation for lung cancer that underwent routine phlebotomy where CTM and circulating tumor cells (CTCs) were identified in blood using nuclear (DAPI), cytokeratin (CK), and CD45 immune-fluorescent antibodies followed by morphologic identification. Second, CTM and CTC data were integrated with patient (age, gender, smoking, and cancer history) and imaging (tumor diameter, location in lung, and maximum standard uptake value [SUVmax]) data to develop and test multiple logistic regression models using a case-control design in a training and test cohort followed by cross-validation in the entire group. Results: We examined 104 patients with NSCLC, and the subgroup of 80 with stage I disease, and compared them to 25 patients with benign disease. Clinical and imaging data alone were moderately discriminating for all comers (Area under the Curve [AUC] = 0.77) and by stage I disease only (AUC = 0.77). However, the presence of CTM combined with clinical and imaging data was significantly discriminating for diagnostic accuracy in all NSCLC patients (AUC = 0.88, p value = 0.001) and for stage I patients alone (AUC = 0.87, p value = 0.002). Conclusion: CTM may add utility for lung cancer diagnosis during imaging evaluation using a sensitive detection platform.

An Observational Study of Circulating Tumor Cells and 18F-FDG PET Uptake in Patients with Treatment-Naive Non-Small Cell Lung Cancer

Introduction We investigated the relationship of circulating tumor cells (CTCs) in non-small cell lung cancer (NSCLC) with tumor glucose metabolism as defined by 18F-fluorodeoxyglucose (FDG) uptake since both have been associated with patient prognosis. Materials & Methods We performed a retrospective screen of patients at four medical centers who underwent FDG PET-CT imaging and phlebotomy prior to a therapeutic intervention for NSCLC. We used an Epithelial Cell Adhesion Molecule (EpCAM) independent fluid biopsy based on cell morphology for CTC detection and enumeration (defined here as High Definition CTCs or “HD-CTCs”). We then correlated HD-CTCs with quantitative FDG uptake image data calibrated across centers in a cross-sectional analysis. Results We assessed seventy-one NSCLC patients whose median tumor size was 2.8 cm (interquartile range, IQR, 2.0–3.6) and median maximum standardized uptake value (SUVmax) was 7.2 (IQR 3.7–15.5). More than 2 HD-CTCs were detected in 63% of patients, whether across all stages (45 of 71) or in stage I disease (27 of 43). HD-CTCs were weakly correlated with partial volume corrected tumor SUVmax (r = 0.27, p-value = 0.03) and not correlated with tumor diameter (r = 0.07; p-value = 0.60). For a given partial volume corrected SUVmax or tumor diameter there was a wide range of detected HD-CTCs in circulation for both early and late stage disease. Conclusions CTCs are detected frequently in early-stage NSCLC using a non-EpCAM mediated approach with a wide range noted for a given level of FDG uptake or tumor size. Integrating potentially complementary biomarkers like these with traditional patient data may eventually enhance our understanding of clinical, in vivo tumor biology in the early stages of this deadly disease.

Molecular profiling of single circulating tumor cells from lung cancer patients

Significance There exists an urgent need for minimally invasive molecular analysis tools for cancer assessment and management, particularly in advanced-stage lung cancer, when tissue procurement is challenging and gene mutation profiling is crucial to identify molecularly targeted agents for treatment. High-throughput compartmentalization and multigene profiling of individual circulating tumor cells (CTCs) from whole-blood samples using modular gene panels may facilitate highly sensitive, yet minimally invasive characterization of lung cancer for therapy prediction and monitoring. We envision this nanoplatform as a compelling research tool to investigate the dynamics of cancer disease processes, as well as a viable clinical platform for minimally invasive yet comprehensive cancer assessment. Circulating tumor cells (CTCs) are established cancer biomarkers for the “liquid biopsy” of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non–small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.