Potential Immune Biomarker Candidates and Immune Subtypes of Lung Adenocarcinoma for Developing mRNA Vaccines

mRNA vaccines against cancer have advantages in safety, improved therapeutic efficacy, and large-scale production. Therefore, our purpose is to identify immune biomarkers and to analyze immune status for developing mRNA vaccines and selecting appropriate patients for vaccination. We downloaded clinical information and RNA-seq data of 494 LUAD patients from TCGA. LUAD mutational information was hierarchically clustered by NMF package (Version 0.23.0). DeconstructSigs package (Version 1.8.0) and NMF consistency clustering were used to identify mutation signatures. Maftools package (Version 2.6.05) was used to select LUAD-related immune biomarkers. TIMER was used to discuss the correlation between genetic mutations and cellular components. Unsupervised clustering Pam method was used to identify LUAD immune subtypes. Log-rank test and univariate/multivariate cox regression were used to predict the prognosis of immune subtypes. Dimensionality reduction analysis was dedicated to the description of LUAD immune landscape. LUAD patients are classified into four signatures: T >C, APOBEC mutation, age, and tobacco. Then, GPRIN1, MYRF, PLXNB2, SLC9A4, TRIM29, UBA6, and XDH are potential LUAD-related immune biomarker candidates to activate the immune response. Next, we clustered five LUAD-related immune subtypes (IS1–IS5) by prognostic prediction. IS3 showed prolonged survival. The reliability of our five immune subtypes was validated by Thorsson’s results. IS2 and IS4 patients had high tumor mutation burden and large number of somatic mutations. Besides, we identified that immune subtypes of cold immunity (patients with IS2 and IS4) are ideal mRNA vaccination recipients. Finally, LUAD immune landscape revealed immune cells and prognostic conditions, which provides important information to select patients for vaccination. GPRIN1, MYRF, PLXNB2, SLC9A4, TRIM29, UBA6, and XDH are potential LUAD-related immune biomarker candidates to activate the immune response. Patients with IS2 and IS4 might potentially be immunization-sensitive patients for vaccination.

Relationship between JAK2-V617F mutation and hematologic parameters in Philadelphia-negative chronic myeloproliferative neoplasms

ObjectivesWe aimed to investigate the prevalence of JAK2-V617F mutation and its association with hematologic parameters in polycythemia vera(PV), essential thrombocytosis(ET) and primary myelofibrosis(PMF) patients who have been tested for the mutation.MethodsWe retrospectively reviewed the records of 168 patients (82 males and 86 females) who were tested for JAK2-V617F mutation upon request of Hematology Clinic. JAK2-V617F mutation status, white blood cell (WBC) counts, platelet (PLT) counts, hemoglobin (Hb), hematocrit (Hct) levels and demographics of the patients were recorded.ResultsJAK2-V617F mutation was detected in 55.9% of the 168 patients. The mutation was observed in 58.2% of PV cases, in 54.4% of ET and in 54.5% of PMF cases. All patients were divided into two groups: mutation positive and negative. Age, WBC and PLT levels were significantly higher in mutation positive group (p<0.05). Age, WBC, Hb, Hct and PLT counts in PV cases with JAK2-V617F mutation, age and WBC counts in PMF cases with JAK2-V617F mutation were found to be significantly higher compared to mutation negative patients (p<0.05).ConclusionJAK2-V617F mutation is a very important parameter in diagnostic and prognostic evaluation. Thus, every patient suspected of having a myeloproliferative neoplasm should be screened for JAK2-V617F mutation.

What’s in a Number? Examining the Prognostic and Predictive Importance of Platelet Count in Patients With Essential Thrombocythemia

Essential thrombocythemia (ET) is a myeloproliferative neoplasm characterized by clonal overproduction of platelets and an increased risk of thrombohemorrhagic complications. Patients are risk stratified by driver mutation, age, and thrombotic history and treated to reduce the risk of thrombotic and hemorrhagic events. The significance of platelet number as a risk factor or treatment goal is unclear. Despite the preponderance of data failing to demonstrate an association, there exists a pervasive belief that higher platelet counts correlate with an increased thrombotic risk. In fact, the association between thrombocytosis and bleeding is more clearly supported. Variability in regional consensus guidelines contributes to the uncertainty. This article reviews the data that shed light on the importance of platelet count in patients with ET.

KRAS mutation profile in Puerto Rican patients with colorectal cancer: Trends in expression of KRAS mutation in PR between April 2009 to January 2011.

e14102 Background: The prevalence of a mutated KRAS gene in colorectal cancer shows ethnic variation with a range between 30-48% among the Caucasian, Asian, and European populations. The purpose of this study was to define the profile of KRAS mutation in colorectal cancer patients in Puerto Rico. Methods: Between April 2009 and January 2011, we collected the expression of KRAS gene among colorectal cancer patients in Puerto Rico. The assay was performed by a central laboratory which began to offer the test in the island in April 2009 (GENOPTIX). Data for the presence and type of mutation, age, sex, cancer histology, site of tumor, and cancer stage were collected. The site of the mutation in codon 12 and 13 were identified by the real time polymerase chain reaction (PCR). The study was approved by IRB. A total of 501 cases were available for study. SPPS version 14 was used for statistical analysis. Results: A mutated KRAS was present in 39% (n=195) of the cohort, more commonly in the 51-69 age group (55.4%; p=0.004), in females (55.4%; p=0.095), in the proximal area of colon (43.8%; p=0.017), in the codon 12 (91.2%), and 8.8% in the codon 13. The majority of mutated genes were in codon 12 (91.2%) with 12 ASP (39.5%) and 12 VAL (25.4%) most often seen. Mucinous histology was associated with 46.7% mutated KRAS, poorly differentiated tumor with 40.0% of KRAS mutation. The mutant expression of KRAS in cases with rectum carcinoma was 39.5%, where the most common mutation was 12 VAL. Conclusions: The prevalence of KRAS mutation in Puerto Rican population is similar to other reported studies. A higher prevalence of 12 VAL mutation in rectal carcinoma and a trend towards a higher mutation rate in females are different in this cohort as compared with published studies. This study was supported by NIH grant numbers G12RR-03035 & 8U54MD007587-03.

Correlation of Clinical Features with the Mutational Status of GM-CSF Signaling Pathway-Related Genes in Children with Juvenile Myelomonocytic Leukemia

Juvenile myelomonocytic leukemia (JMML) is a rare clonal myeloproliferative disorder that affects young children. It is characterized by specific hypersensitivity to granulocyte-macrophage colony-stimulating factor (GM-CSF) in vitro. Mutations in RAS, NF1, or PTPN11 positioned in the GM-CSF signal pathway, are thought to be involved in the pathogenesis of JMML. However, no information is available on the relationship between these mutations and clinical features of JMML. The impacts of these mutations on clinical outcome also remain unclear. We tested 49 Japanese children with JMML for N-RAS, K-RAS, and PTPN11 mutations and evaluated their clinical significance. We also assessed correlations between mutational status and clinical and laboratory findings, including age at diagnosis, fetal hemoglobin (HbF), platelet count, and cytogenetic abnormality, all which have been proposed as prognostic factors for JMML. Of the 49 JMML patients, cytogenetic abnormalities were detected in 13, including 8 with monosomy 7. For 2 patients, a clinical diagnosis of neurofibromatosis type 1 (NF1) was confirmed. PTPN11 and N-/K-RAS mutations were found in 22 (45%) and 8 (16%) patients, respectively. Neither PTPN11 nor RAS mutations nor NF1 were present in 17 (35%) patients, and no simultaneous aberrations in these genes were found. In patients with the PTPN11 mutation, age at diagnosis was older (35 vs 11 months; P=0.001, or 12 months; P<0.01) and HbF level was higher (31 vs 10%; P=0.03, or 16%; P<0.01) than for patients with the RAS mutation or without any aberration, suggesting that the clinical outcome for patients with the PTPN11 mutation might be poorer, because a higher HbF level and older age have been reported to be poor prognostic factors. In fact, overall survival (OS) at 5 years was lower for patients with the PTPN11 mutation than for those without (20±9% vs 58±9%; P=0.02). In addition to PTPN11 mutation, age older than 24 months (P<0.01) and abnormal karyotype (P=0.02) were also associated with poor prognosis for OS. Of the 49 patients, 33 received stem cell transplantation (SCT). OS probabilities for patients with and without a mutation in PTPN11 at 5 years after SCT were 25±10% and 64±12%, respectively (P=0.04). More importantly, mutation in PTPN11 was the only unfavorable factor for relapse after SCT (P<0.01). Seven patients died owing to relapse and 12 from complications. All patients who died after relapse had a PTPN11 mutation. In summary, our results suggest that PTPN11-mutated JMML might be a distinct subgroup with specific clinical characteristics and a poor outcome.

The Outcome in AML Is Predicted by Cytogenetics, NPM1/FLT3 Mutation, Age and Sex, but Not by Treatment Variables.

In order to test current risk factors in a prospective multicenter setting we evaluated the AMLCG 99 trial. Patients were randomly assigned to induction by TAD-HAM (HAM with araC 3 for age <60y and 1 for age ≥60y g/m2 × 6), or HAM-HAM, and also to TAD consolidation and maintenance or (age <60y) myeloablative chemotherapy and autologous SCT. Patients with histocompatible family donors preferentially underwent allogeneic SCT. Since any randomization was done up-front, informations from completely unselected patients were available. 2547 patients of 16–85 (median 61) y entered the trial. 1858 pts had de-novo and 689 pts secondary AML. The CR rate was 61%, 54% in older (60) and 69% in younger patients. The overall survival (OS) at 4 years was 27%, 15% in older and 41% in younger patients. The relapse risk (RR) was 65%, 80% in older and 50% in younger patients and the relapse-free survival (RFS) was 30%, 14% and 44%, respectively. In the entire patients complete outcome (CR, OS, RR, RFS) was predicted by favorable and unfavorable karyotype. Among patients with any abnormal karyotype complete outcome was predicted by unfavorable karyotype in the older and favorable karyotype in the younger age group. In both age groups with normal karyotype outcome for the complete parameters was predicted by the NPM1+/FLT3- ITD- mutation status. As a new finding in patients of <60 years with normal karyotype female sex turned out being an independent predictive factor for longer OS (HR 1.45;95%CI 1.04–2.03), longer RFS (HR1.64;95%CI 1.10–2.44), and lower RR (HR 0.59;95%CI 0.38–0.92). Female sex was the only predictive factor besides the NPM1/FLT3 mutation status in this group. The OS at 4 years in patients of <60y with normal karyotype is 52% in women and 40% in men (log-rank P=0.047), the RR is 37% and 52% (P=0.016), and the RFS is 55% in women and 42% in men (P=0.025). Furthermore, the favorable NPM1+/FLT3- mutation status was more frequent in women than in men (35% vs 26%; P=0.0075). Remarkably, the NPM1+/FLT3- mutation status was equally predictive in patients of ≥60y as in those of <60y with HR for OS of 2.51 (95% CI 1.75–3.61) and 3.27 (95%CI 2.11–5.05) and HR for RR of 0.33 (95% C 0.21–0.51) and 0.29 (95%CI 0.17–0.49). The difference in the OS at 4 years between patients with NPM1+/FLT3- mutation and those with other NPM1/FLT3 combinations was 42% vs 18% (P=<0.001) in the older, and 69% vs 34% (P<0.001) in the younger patients. The related differences in RR were 58% vs 84% (P<0.001) in the older, and 22% vs 59% (P<0.001) in the younger patients. Among the NPM1/FLT3 mutations the favorable +/− constellation accounted for 27% of older, and 35% of younger patients (P=0.0197). Besides karyotypes and mutations, also age, de-novo AML, blast clearance, LDH and WBC partly predicted outcomes. In contrast no prognostic impact was found by multi-and univariate analyses of treatment alternatives. Conclusion: As from a large multicenter prospective trial the outcome in AML is mainly determined by cytogenetics, NPM1/FLT3 mutation, age and sex, but not by the assigned treatment variables.