BackgroundIpilimumab induces long-lasting clinical responses in a minority of patients with metastatic melanoma. To better understand the mechanism(s) of action and to identify novel biomarkers associated with the clinical benefit and toxicity of ipilimumab, baseline characteristics and changes in CD4+ and CD8+ T cells from melanoma patients receiving ipilimumab were characterized by gene profiling and flow cytometry.MethodsMicroarray analysis of flow-cytometry purified CD4+ and CD8+ T cells was employed to assess gene profiling changes induced by ipilimumab. Selected molecules were further investigated by flow cytometry on pre, 3-month and 6-month post-treatment specimens.ResultsIpilimumab up-regulated Ki67 and ICOS on CD4+ and CD8+ cells at both 3- and 6-month post ipilimumab (p ≤ 0.001), decreased CCR7 and CD25 on CD8+ at 3-month post ipilimumab (p ≤ 0.02), and increased Gata3 in CD4+ and CD8+ cells at 6-month post ipilimumab (p ≤ 0.001). Increased EOMES+CD8+, GranzymeB+EOMES+CD8+ and decreased Ki67+EOMES+CD4+ T cells at 6 months were significantly associated with relapse (all p ≤ 0.03). Decreased Ki67+CD8+ T cells were significantly associated with the development of irAE (p = 0.02). At baseline, low Ki67+EOMES+CD8+ T cells were associated with relapse (p ≤ 0.001), and low Ki67+EOMES+CD4+ T cells were associated with irAE (p ≤ 0.008).ConclusionsUp-regulation of proliferation and activation signals in CD4+ and CD8+ T cells were pharmacodynamic markers for ipilimumab. Ki67+EOMES+CD8+ and Ki67+EOMES+CD4+T cells at baseline merit further testing as biomarkers associated with outcome and irAEs, respectively.

Cancer-associated protein tyrosine kinase (PTK) mutations usually are gain-of-function (GOF) mutations that drive tumor growth and metastasis. We have found 50 JAK1 truncating mutations in 36 of 635 gynecologic tumors in the Total Cancer Care® (TCC®) tumor bank. Among cancer cell lines containing JAK1 truncating mutations in the Cancer Cell Line Encyclopedia databank, 68% are gynecologic cancer cells. Within JAK1 the K142, P430, and K860 frame-shift mutations were identified as hot spot mutation sites. Sanger sequencing of cancer cell lines, primary tumors, and matched normal tissues confirmed the JAK1 mutations and showed that these mutations are somatic. JAK1 mediates interferon (IFN)-γ-regulated tumor immune surveillance. Functional assays show that JAK1 deficient cancer cells are defective in IFN-γ-induced LMP2 and TAP1 expression, loss of which inhibits presentation of tumor antigens. These findings identify recurrent JAK1 truncating mutations that could contribute to tumor immune evasion in gynecologic cancers, especially in endometrial cancer.

Background The incidence and outcomes for patients with colorectal cancer (CRC) varies by age. Younger patients tend to have sporadic cancers not detected by screening and worse survival. To understand if genetic differences exist between age cohorts we sought to characterize unique genetic alterations in patients with CRC. Methods We identified 283 patients with sporadic CRC between 1998 and 2010 and divided them by age into two cohorts: ≤45 years old (younger) or ≥65 years old (older) and performed targeted exome sequencing. Fisher’s Exact test was used to detect differences in mutation frequencies between the two groups. Whole exome sequencing was performed on 21 additional younger patient samples for validation. Findings were confirmed in The Cancer Genome Atlas CRC dataset. Results 246 samples were included for final analysis (195 older, 51 younger). Mutations in FBXW7 were more common in the younger cohort (27.5% vs. 9.7%, p=0.0022) as were mutations in the proofreading domain of POLE (9.8% vs. 1.0%, p= 0.0048). There were similar mutation rates between cohorts with regards to TP53 (64.7% vs. 61.5%), KRAS (43.1% vs. 46.2%), and APC (60.8% vs 73.8%). BRAF mutations were numerically more common in the older cohort, though not statistically significant (2.0% vs 9.7%, p=0.082). Conclusions In this retrospective study, we identified a unique genetic profile for younger CRC patients as compared to patients diagnosed at an older age. These findings should be validated in a larger study and could have an impact on future screening and treatment modalities for younger CRC patients.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal cancers world-wide, partly because methods are lacking to detect disease at an early, operable stage. Noninvasive PDAC precursors called intraductal papillary mucinous neoplasms (IPMNs) exist, and strategies are needed to aid in their proper diagnosis and management. Data support the importance of mi(cro)RNAs in the progression of IPMNs to malignancy, and we hypothesized that miRNAs may be shed from IPMN tissues and detected in blood. Our primary goals were to measure the abundance of miRNAs in archived pre-operative plasma from individuals with pathologically-confirmed IPMNs and healthy controls and discover plasma miRNAs that distinguish between IPMN patients and controls and between ‘malignant’ and ‘benign’ IPMNs. Using novel nCounter technology™ to evaluate 800 miRNAs, we showed that a 30-miRNA signature distinguished 42 IPMN cases from 24 controls (area underneath the curve (AUC)= 74.4 (95% CI:62.3-86.5, p=0.002). The signature contained novel miRNAs and miRNAs previously implicated in pancreatic carcinogenesis that had 2-4 fold higher expression in cases than controls. We also generated a 5-miRNA signature that discriminated between 21 malignant (high-grade dysplasia and invasive carcinoma) and 21 benign (low- and moderate-grade dysplasia) IPMNs (AUC=73.2 (95% CI: 57.6-73.2, p=0.005)), and showed that paired plasma and tissue samples from patients with IPMNs can have distinct miRNA expression profiles. This study suggests feasibility of using new cost-effective technology to develop a miRNA-based blood test to aid in pre-operative identification of malignant IPMNs that warrant resection while sparing individuals with benign IPMNs the morbidity associated with overtreatment.

BackgroundObservations of recurrent somatic mutations in tumors have led to identification and definition of signaling and other pathways that are important for cancer progression and therapeutic targeting. As tumor cells contain both an individual’s inherited genetic variants and somatic mutations, challenges arise in distinguishing these events in massively parallel sequencing datasets. Typically, both a tumor sample and a “normal” sample from the same individual are sequenced and compared; variants observed only in the tumor are considered to be somatic mutations. However, this approach requires two samples for each individual.ResultsWe evaluate a method of detecting somatic mutations in tumor samples for which only a subset of normal samples are available. We describe tuning of the method for detection of mutations in tumors, filtering to remove inherited variants, and comparison of detected mutations to several matched tumor/normal analysis methods. Filtering steps include the use of population variation datasets to remove inherited variants as well a subset of normal samples to remove technical artifacts. We then directly compare mutation detection with tumor-only and tumor-normal approaches using the same sets of samples. Comparisons are performed using an internal targeted gene sequencing dataset (n = 3380) as well as whole exome sequencing data from The Cancer Genome Atlas project (n = 250). Tumor-only mutation detection shows similar recall (43–60%) but lesser precision (20–21%) to current matched tumor/normal approaches (recall 43–73%, precision 30–82%) when compared to a “gold-standard” tumor/normal approach. The inclusion of a small pool of normal samples improves precision, although many variants are still uniquely detected in the tumor-only analysis.ConclusionsA detailed method for somatic mutation detection without matched normal samples enables study of larger numbers of tumor samples, as well as tumor samples for which a matched normal is not available. As sensitivity/recall is similar to tumor/normal mutation detection but precision is lower, tumor-only detection is more appropriate for classification of samples based on known mutations. Although matched tumor-normal analysis is preferred due to higher precision, we demonstrate that mutation detection without matched normal samples is possible for certain applications.Electronic supplementary materialThe online version of this article (10.1186/s40246-017-0118-2) contains supplementary material, which is available to authorized users.