Crizotinib in patients with tumors harboring ALK or ROS1 rearrangements in the NCI-MATCH trial.

The NCI-MATCH was designed to characterize the efficacy of targeted therapies in histology-agnostic driver mutation-positive malignancies. Sub-protocols F and G were developed to evaluate the role of crizotinib in rare tumors that harbored either ALK or ROS1 rearrangements. Patients with malignancies that progressed following at least one prior systemic therapy were accrued to the NCI-MATCH for molecular profiling, and those with actionable ALK or ROS1 rearrangements were offered participation in sub-protocols F or G, respectively. There were five patients who enrolled on Arm F (ALK) and four patients on Arm G (ROS1). Few grade 3 or 4 toxicities were noted, including liver test abnormalities, and acute kidney injury. For sub-protocol F (ALK), the response rate was 50% (90% CI 9.8-90.2%) with one complete response among the 4 eligible patients. The median PFS was 3.8 months, and median OS was 4.3 months. For sub-protocol G (ROS1) the response rate was 25% (90% CI 1.3-75.1%). The median PFS was 4.3 months, and median OS 6.2 months. Data from 3 commercial vendors showed that the prevalence of ALK and ROS1 rearrangements in histologies other than non-small cell lung cancer and lymphoma was rare (0.1% and 0.4% respectively). We observed responses to crizotinib which met the primary endpoint for ALK fusions, albeit in a small number of patients. Despite the limited accrual, some of the patients with these oncogenic fusions can respond to crizotinib which may have a therapeutic role in this setting.

Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project.

BACKGROUND: Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications. MATERIALS AND METHODS: Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values. RESULTS: Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples. CONCLUSIONS: Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

Ado-trastuzumab emtansine (T-DM1) in patients with HER2-amplified tumors excluding breast and gastric/gastroesophageal junction (GEJ) adenocarcinomas: results from the NCI-MATCH trial (EAY131) subprotocol Q.

BACKGROUND: The National Cancer Institute-Molecular Analysis for Therapy Choice (NCI-MATCH) is a national precision medicine study incorporating centralized genomic testing to direct refractory cancer patients to molecularly targeted treatment subprotocols. This treatment subprotocol was designed to screen for potential signals of efficacy of ado-trastuzumab emtansine (T-DM1) in HER2-amplified histologies other than breast and gastroesophageal tumors. METHODS: Eligible patients had HER2 amplification at a copy number (CN) >7 based on targeted next-generation sequencing (NGS) with a custom Oncomine AmpliSeq™ (ThermoFisher Scientific) panel. Patients with prior trastuzumab, pertuzumab or T-DM1 treatment were excluded. Patients received T-DM1 at 3.6 mg/kg i.v. every 3 weeks until toxicity or disease progression. Tumor assessments occurred every three cycles. The primary end point was centrally assessed objective response rate (ORR). Exploratory end points included correlating response with HER2 CN by NGS. The impact of co-occurring genomic alterations and PTEN loss by immunohistochemistry were also assessed. RESULTS: Thirty-eight patients were enrolled and 36 included in efficacy analysis. Median prior therapies in the metastatic setting was 3 (range 0-9; unknown in one patient). Median HER2 CN was 17 (range 7-139). Partial responses were observed in two (5.6%) patients: one mucoepidermoid carcinoma of parotid gland and one parotid gland squamous cell cancer. Seventeen patients (47%) had stable disease including 8/10 (80%) with ovarian and uterine carcinomas, with median duration of 4.6 months. The 6-month progression-free survival rate was 23.6% [90% confidence interval 14.2% to 39.2%]. Common toxicities included fatigue, anemia, fever and thrombocytopenia with no new safety signals. There was a trend for tumor shrinkage with higher levels of gene CN as determined by the NGS assay. CONCLUSION: T-DM1 was well tolerated. While this subprotocol did not meet the primary end point for ORR in this heavily pre-treated diverse patient population, clinical activity was seen in salivary gland tumors warranting further study in this tumor type in dedicated trials.

Glucagon receptor antagonist and GIP agonist combination for diet-induced obese mice.

Ablation of glucagon receptor signaling represents a potential treatment option for type 2 diabetes (T2DM). Additionally, activation of glucose-dependent insulinotropic polypeptide (GIP) receptor signaling also holds therapeutic promise for T2DM. Therefore, this study examined both independent and combined metabolic actions of desHis(1)Pro(4)Glu(9)(Lys(12)PAL)-glucagon (glucagon receptor antagonist) and d-Ala(2)GIP (GIP receptor agonist) in diet-induced obese mice. Glucagon receptor binding has been linked to alpha-helical structure and desHis(1)Pro(4)Glu(9)(Lys(12)PAL)-glucagon displayed enhanced alpha-helical content compared with native glucagon. In clonal pancreatic BRIN-BD11 beta-cells, desHis(1)Pro(4)Glu(9)(Lys(12)PAL)-glucagon was devoid of any insulinotropic or cAMP-generating actions, and did not impede d-Ala(2)GIP-mediated (P<0.01 to P<0.001) effects on insulin and cAMP production. Twice-daily injection of desHis(1)Pro(4)Glu(9)(Lys(12)PAL)-glucagon or d-Ala(2)GIP alone, and in combination, in high-fat-fed mice failed to affect body weight or energy intake. Circulating blood glucose levels were significantly (P<0.05 to P<0.01) decreased by all treatments regimens, with plasma and pancreatic insulin elevated (P<0.05 to P<0.001) in all mice receiving d-Ala(2)GIP. Interestingly, plasma glucagon concentrations were decreased (P<0.05) by sustained glucagon inhibition (day 28), but increased (P<0.05) by d-Ala(2)GIP therapy, with a combined treatment resulting in glucagon concentration similar to saline controls. All treatments improved (P<0.01) intraperitoneal and oral glucose tolerance, and peripheral insulin sensitivity. d-Ala(2)GIP-treated mice showed increased glucose-induced insulin secretion in response to intraperitoneal and oral glucose. Metabolic rate and ambulatory locomotor activity were increased (P<0.05 to P<0.001) in all desHis(1)Pro(4)Glu(9)(Lys(12)PAL)-glucagon-treated mice. These studies highlight the potential of glucagon receptor inhibition alone, and in combination with GIP receptor activation, for T2DM treatment.

Statistical controversies in clinical research: assessing pathologic complete response as a trial-level surrogate end point for early-stage breast cancer.

BACKGROUND: A trial-level surrogate end point for a randomized clinical trial may allow assessment of the relative benefits of the treatment to be performed at an earlier time point and potentially with a smaller sample size. However, determining whether an end point is a reliable trial-level surrogate based on results of previous trials is not straightforward. The question of trial-level surrogacy is easily confused with the question of individual-level surrogacy, and this confusion can lead to controversy. A recent example concerns the evaluation of pathologic complete response (pCR) as a surrogate for event-free survival (EFS) and overall survival (OS) in early-stage breast cancer. MATERIALS AND METHODS: The differences between individual-level surrogacy (i.e. for patients receiving a specific treatment, the surrogate end point predicts the definitive end point) and trial-level surrogacy (the results of the trial for the surrogate end point predict the results of the trial for the definitive end point) are discussed. Trial-level data used in two previous meta-analyses evaluating pCR as a trial-level surrogate for EFS and OS were re-analyzed using methods that appropriately account for the variability in pCR rates as well as the variability in the hazard ratios for EFS and OS. RESULTS: There is no evidence that pCR is a trial-level surrogate for EFS or OS, nor is there evidence that pCR could be used reliably to screen out nonpromising agents from further drug development. CONCLUSIONS: At present, neoadjuvant RCTs should continue to follow patients to observe EFS and OS to assess clinical benefit, and they should be designed with sufficient sample size to reliably assess EFS. However, one cannot rule out the possibility that future meta-analyses involving more trials and in which the patient population or class of treatments is restricted could suggest the validity of pCR as a trial-level surrogate for EFS or OS in some focused settings.

Circulating levels of immune and inflammatory markers and long versus short survival in early-stage lung cancer.

BACKGROUND: Some patients diagnosed with early-stage lung cancer and treated according to standard care survive for only a short period of time, while others survive for years for reasons that are not well understood. Associations between markers of inflammation and survival from lung cancer have been observed. MATERIALS AND METHODS: Here, we investigate whether circulating levels of 77 inflammatory markers are associated with long versus short survival in stage I and II lung cancer. Patients who had survived either <79 weeks (~1.5 years) (short survivors, SS) or >156 weeks (3 years) (long survivors, LS) were selected from a retrospective population-based study. Logistic regression was used to calculate adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs). The false discovery rate was calculated to adjust for multiple testing. RESULTS: A total of 157 LS and 84 SS were included in this analysis. Thirteen markers had adjusted OR on the order of 2- to 5-fold when comparing the upper and lower quartiles with regard to the odds of short survival versus long. Chemokine CCL15 [chemokine (C-C motif) ligand 15] was the most significant marker associated with increased odds of short survival (ORs = 4.93; 95% CI 1.90-12.8; q-value: 0.042). Smoking and chronic obstructive pulmonary disease were not associated with marker levels. CONCLUSIONS: Our results provide some evidence that deregulation of inflammatory responses may play a role in the survival of early-stage lung cancer. These findings will require confirmation in future studies.

Epstein-Barr virus microRNAs and lung cancer.

BACKGROUND: We conducted the first analysis of viral microRNAs (miRNAs) in lung cancer, with a focus on Epstein-Barr virus (EBV). METHODS: We evaluated viral miRs with a two-channel oligo-array targeting mature, anti-sense miRNAs in 290 cases. In 48 cases, we compared microarray and real-time quantitative PCR (qPCR) expression for three EBV miRNAs. We tested for EBV DNA, RNA, and protein in tumour tissue from six cases with and six cases without strong qPCR-based evidence of EBV miRNAs. RESULTS: The EBV miRNAs strongly differentiated between adenocarcinoma and squamous cell carcinoma using the microarray (P<0.01 for 9 out of 16 EBV miRNAs). However, microarray and qPCR measurements of BART1, BART2, and BHRF1-3 expression were not significantly correlated (P=0.53, 0.94, and 0.47, respectively). Although qPCR provided substantial evidence of EBV miRNAs in 7 out of 48 cases, only 1 of these 7 cases had detectable EBV DNA in tumour tissue. None had detectable EBV RNA or protein by histochemical stains. CONCLUSION: In a comprehensive evaluation of EBV miRNA, DNA, RNA, and protein in lung cancer, we found little evidence of EBV in lung tumour tissue. Discrepancies between microarray- and qPCR-based strategies highlight the difficulty of validating molecular markers of disease. Our results do not support a role of EBV in lung cancer.

Inherited polymorphisms in the RNA-mediated interference machinery affect microRNA expression and lung cancer survival.

BACKGROUND: MicroRNAs (miRs) have an important role in lung carcinogenesis and progression. Single-nucleotide polymorphisms (SNPs) in genes involved in miR biogenesis may affect miR expression in lung tissue and be associated with lung carcinogenesis and progression. METHODS: we analysed 12 SNPs in POLR2A, RNASEN and DICER1 genes in 1984 cases and 2073 controls from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We investigated miR expression profiles in 165 lung adenocarcinoma (AD) and 125 squamous cell carcinoma tissue samples from the same population. We used logistic and Cox regression models to examine the association of individual genotypes and haplotypes with lung cancer risk and with lung cancer-specific survival, respectively. SNPs-miR expression associations in cases were assessed using two-sample t-tests and global permutation tests. RESULTS: a haplotype in RNASEN (Drosha) was significantly associated with shorter lung cancer survival (hazard ratio=1.86, 95% CI=1.19-2.92, P=0.007). In AD cases, a SNP within the same haplotype was associated with reduced RNASEN mRNA expression (P=0.013) and with miR expression changes (global P=0.007) of miRs known to be associated with cancer (e.g., let-7 family, miR-21, miR-25, miR-126 and miR15a). CONCLUSION: inherited variation in the miR-processing machinery can affect miR expression levels and lung cancer-specific survival.

Questioning the utility of pooling samples in microarray experiments with cell lines.

We describe a microarray experiment using the MCF-7 breast cancer cell line in two different experimental conditions for which the same number of independent pools as the number of individual samples was hybridized on Affymetrix GeneChips. Unexpectedly, when using individual samples, the number of probe sets found to be differentially expressed between treated and untreated cells was about three times greater than that found using pools. These findings indicate that pooling samples in microarray experiments where the biological variability is expected to be small might not be helpful and could even decrease one's ability to identify differentially expressed genes.

Reporting recommendations for tumor marker prognostic studies (remark).

Despite years of research and hundreds of reports on tumor markers in oncology, the number of markers that have emerged as clinically useful is pitifully small. Often, initially reported studies of a marker show great promise, but subsequent studies on the same or related markers yield inconsistent conclusions or stand in direct contradiction to the promising results. It is imperative that we attempt to understand the reasons that multiple studies of the same marker lead to differing conclusions. A variety of methodologic problems have been cited to explain these discrepancies. Unfortunately, many tumor marker studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalizability of study results. The development of guidelines for the reporting of tumor marker studies was a major recommendation of the National Cancer Institute - European Organisation for Research and Treatment of Cancer (NCI - EORTC) First International Meeting on Cancer Diagnostics in 2000. As for the successful CONSORT initiative for randomized trials and for the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, preplanned hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, the guidelines suggest helpful presentations of data and important elements to include in discussions. The goal of these guidelines is to encourage transparent and complete reporting so that the relevant information will be available to others to help them to judge the usefulness of the data and understand the context in which the conclusions apply.

REporting recommendations for tumour MARKer prognostic studies (REMARK).

Despite years of research and hundreds of reports on tumour markers in oncology, the number of markers that have emerged as clinically useful is pitifully small. Often initially reported studies of a marker show great promise, but subsequent studies on the same or related markers yield inconsistent conclusions or stand in direct contradiction to the promising results. It is imperative that we attempt to understand the reasons that multiple studies of the same marker lead to differing conclusions. A variety of methodological problems have been cited to explain these discrepancies. Unfortunately, many tumour marker studies have not been reported in a rigorous fashion, and published articles often lack sufficient information to allow adequate assessment of the quality of the study or the generalisability of the study results. The development of guidelines for the reporting of tumour marker studies was a major recommendation of the US National Cancer Institute and the European Organisation for Research and Treatment of Cancer (NCI-EORTC) First International Meeting on Cancer Diagnostics in 2000. Similar to the successful CONSORT initiative for randomised trials and the STARD statement for diagnostic studies, we suggest guidelines to provide relevant information about the study design, preplanned hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, the guidelines suggest helpful presentations of data and important elements to include in discussions. The goal of these guidelines is to encourage transparent and complete reporting so that the relevant information will be available to others to help them to judge the usefulness of the data and understand the context in which the conclusions apply.

Identifying pre-post chemotherapy differences in gene expression in breast tumours: a statistical method appropriate for this aim.

Although widely used for the analysis of gene expression microarray data, cluster analysis may not be the most appropriate statistical technique for some study aims. We demonstrate this by considering a previous analysis of microarray data obtained on breast tumour specimens, many of which were paired specimens from the same patient before and after chemotherapy. Reanalysing the data using statistical methods that appropriately utilise the paired differences for identification of differentially expressed genes, we find 17 genes that we can confidently identify as more expressed after chemotherapy than before. These findings were not reported by the original investigators who analysed the data using cluster analysis techniques.

Latent class modeling approaches for assessing diagnostic error without a gold standard: with applications to p53 immunohistochemical assays in bladder tumors.

Improved characterization of tumors for purposes of guiding treatment decisions for cancer patients will require that accurate and reproducible assays be developed for a variety of tumor markers. No gold standards exist for most tumor marker assays. Therefore, estimates of assay sensitivity and specificity cannot be obtained unless a latent class model-based approach is used. Our goal in this article is to estimate sensitivity and specificity for p53 immunohistochemical assays of bladder tumors using data from a reproducibility study conducted by the National Cancer Institute Bladder Tumor Marker Network. We review latent class modeling approaches proposed by previous authors, and we find that many of these approaches impose assumptions about specimen heterogeneity that are not consistent with the biology of bladder tumors. We present flexible mixture model alternatives that are biologically plausible for our example, and we use them to estimate sensitivity and specificity for our p53 assay example. These mixture models are shown to offer an improvement over other methods in a variety of settings, but we caution that, in general, care must be taken in applying latent class models.

Covariate measurement error adjustment for matched case-control studies.

We propose a conditional scores procedure for obtaining bias-corrected estimates of log odds ratios from matched case-control data in which one or more covariates are subject to measurement error. The approach involves conditioning on sufficient statistics for the unobservable true covariates that are treated as fixed unknown parameters. For the case of Gaussian nondifferential measurement error, we derive a set of unbiased score equations that can then be solved to estimate the log odds ratio parameters of interest. The procedure successfully removes the bias in naive estimates, and standard error estimates are obtained by resampling methods. We present an example of the procedure applied to data from a matched case-control study of prostate cancer and serum hormone levels, and we compare its performance to that of regression calibration procedures.

Measuring cell proliferation in the rectal mucosa. comparing bromodeoxyuridine (BrdU) and proliferating cell nuclear antigen (PCNA) assays.

Cell proliferation in the human colorectum can be measured using bromodeoxyuridine (BrdU) or proliferating cell nuclear antigen (PCNA) assays. Using data from the National Cancer Institute's Polyp Prevention Trial, these two assays are compared using correlation coefficients and variance components analysis. Adjusting for fixed as well as for the random effects of between-biopsy and scoring variation, the estimated correlation is 0.46 for the log labeling index and 0.45 for log proliferative height. This is an estimate of the highest correlation that can be achieved by taking multiple biopsies scored by multiple scorers. For single biopsies, the estimated correlation is 0.16 and 0.10, respectively. There are significant differences between the variance components for the two assays. For example, for log labeling index, PCNA has a lower variation between biopsies than BrdU, but higher variation between scorings. When used in a clinical or epidemiological setting, it is important to take multiple biopsies at multiple time points.

Statistical issues in tumor marker studies.

CONTEXT: Inferences from tumor marker studies are complicated by a variety of statistical concerns, which can make proper interpretation of results difficult. This article focuses on important issues that should be addressed when designing, conducting, and analyzing tumor marker studies. OBJECTIVE: To highlight the importance of considering statistical significance, risk ratios, statistical power, reproducibility, multiple testing, confirmatory studies, and missing data in the design of marker studies used for prognosis. RESULTS: Suggestions are provided for more effectively conducting marker studies. These include more careful attention to adequacy of the number of subjects for a marker study and improved documentation and standardization of assay methods. The importance of complete reporting of study results and description of the statistical analysis methods used is also emphasized. CONCLUSION: Cooperation among clinicians, laboratory scientists, and statisticians will be required to conduct statistically sound tumor marker studies and to facilitate prioritizing markers for new and confirmatory studies in an environment of limited patient and specimen resources.

Reproducibility of p53 immunohistochemistry in bladder tumors. National Cancer Institute, Bladder Tumor Marker Network.

The National Cancer Institute Bladder Tumor Marker Network conducted a study to evaluate the reproducibility of immunohistochemistry for measuring p53 expression in bladder tumors. Fifty paraffin blocks (10 from each of the five network institutions) were chosen at random from among high-grade invasive primary bladder tumors. Two sections from each block were sent to each laboratory for staining and scoring, and then all sections were randomly redistributed among the laboratories for a second scoring. Intra- and interlaboratory reproducibility was assessed with regard to both staining and scoring. For overall assessments of p53 positivity, the results demonstrated that intralaboratory reproducibility was quite good. Concordance across the five participating laboratories was high for specimens exhibiting no or minimal nuclear immunostaining of tumor cells or high percentages of tumor cells with nuclear immunoreactivities. However, there was a reduced level of concordance on specimens with percentages of stained tumor cells in an intermediate range. The discordancies were due mainly to staining differences in one of the five laboratories and scoring differences in another laboratory. These results indicate that some caution must be used in comparing results across studies from different groups. Standardization of staining protocols and selection of a uniform threshold for binary interpretation of results may improve assay reproducibility between laboratories.