The inclusion of high-dimensional omics data in prediction models has become a well-studied topic in the last decades. Although most of these methods do not account for possibly different types of ...variables in the set of covariates available in the same dataset, there are many such scenarios where the variables can be structured in blocks of different types, e.g., clinical, transcriptomic, and methylation data. To date, there exist a few computationally intensive approaches that make use of block structures of this kind.
In this paper we present priority-Lasso, an intuitive and practical analysis strategy for building prediction models based on Lasso that takes such block structures into account. It requires the definition of a priority order of blocks of data. Lasso models are calculated successively for every block and the fitted values of every step are included as an offset in the fit of the next step. We apply priority-Lasso in different settings on an acute myeloid leukemia (AML) dataset consisting of clinical variables, cytogenetics, gene mutations and expression variables, and compare its performance on an independent validation dataset to the performance of standard Lasso models.
The results show that priority-Lasso is able to keep pace with Lasso in terms of prediction accuracy. Variables of blocks with higher priorities are favored over variables of blocks with lower priority, which results in easily usable and transportable models for clinical practice.
Purpose
Treatment of metastatic germ cell cancer (GCC) is based on the International Germ Cell Cancer Collaborative Group (IGCCCG) prognostic classification published in 1997. 5-year survival rates ...were reported to be 91%, 79%, and 48% for patients with good, intermediate and poor prognosis, respectively. However, treatment results may have improved over time due to cumulative experience, improved supportive care and modern-type chemotherapy.
Methods
Patients with metastatic GCC who received cisplatin-based chemotherapy at two institutions in Munich between 2000 and 2013 were retrospectively studied. Clinical characteristics, treatment and outcomes were analyzed with respect to the IGCCG prognostic classification.
Results
Of 225 patients (median age 35 years), 72 (32%) had seminoma (S) and 153 (68%) nonseminoma. 175 (78%), 30 (13%) and 20 patients (9%) had good, intermediate and poor prognosis according to the IGCCCG classification. The 2-year-progression free survival of patients with good, intermediate and poor prognosis was 91%, 83% and 37%, and the 5-year-overall survival (OS) was 98%, 96%, and 66%, respectively. There was no significant difference in the OS between patients in the good and intermediate prognosis group.
Conclusion
Compared to data from the original IGCCCG classification system, the outcome of patients with metastatic GCC has considerably improved over time. While the prognosis of intermediate-risk patients is excellent, treatment in the poor-prognosis group remains to be improved.
Follicular lymphoma (FL) is a clinically and molecularly heterogeneous disease. Posttreatment surrogate end points, such as progression of disease within 24 months (POD24) are promising predictors ...for overall survival (OS) but are of limited clinical value, primarily because they cannot guide up-front treatment decisions. We used the clinical and molecular data from 2 independent cohorts of symptomatic patients in need of first-line immunochemotherapy (151 patients from a German Low-Grade Lymphoma Study Group GLSG trial and 107 patients from a population-based registry of the British Columbia Cancer Agency BCCA) to validate the predictive utility of POD24, and to evaluate the ability of pretreatment risk models to predict early treatment failure. POD24 occurred in 17% and 23% of evaluable GLSG and BCCA patients, with 5-year OS rates of 41% (vs 91% for those without POD24, P < .0001) and 26% (vs 86%, P < .0001), respectively. The m7–FL International Prognostic Index (m7-FLIPI), a prospective clinicogenetic risk model for failure-free survival, had the highest accuracy to predict POD24 (76% and 77%, respectively) with an odds ratio of 5.82 in GLSG (P = .00031) and 4.76 in BCCA patients (P = .0052). A clinicogenetic risk model specifically designed to predict POD24, the POD24-PI, had the highest sensitivity to predict POD24, but at the expense of a lower specificity. In conclusion, the m7-FLIPI prospectively identifies the smallest subgroup of patients (28% and 22%, respectively) at highest risk of early failure of first-line immunochemotherapy and death, including patients not fulfilling the POD24 criteria, and should be evaluated in prospective trials of precision medicine approaches in FL.
•The posttreatment end point progression of FL within 24 months (POD24) is strongly associated with OS.•A pretreatment clinicogenetic risk model (m7-FLIPI) predicts POD24 and OS and identifies the smallest subgroup with highest unmet need.
Mg
regulates many physiological processes and signalling pathways. However, little is known about the mechanisms underlying the organismal balance of Mg
. Capitalizing on a set of newly generated ...mouse models, we provide an integrated mechanistic model of the regulation of organismal Mg
balance during prenatal development and in adult mice by the ion channel TRPM6. We show that TRPM6 activity in the placenta and yolk sac is essential for embryonic development. In adult mice, TRPM6 is required in the intestine to maintain organismal Mg
balance, but is dispensable in the kidney.
inactivation in adult mice leads to a shortened lifespan, growth deficit and metabolic alterations indicative of impaired energy balance. Dietary Mg
supplementation not only rescues all phenotypes displayed by
-deficient adult mice, but also may extend the lifespan of wildtype mice. Hence, maintenance of organismal Mg
balance by TRPM6 is crucial for prenatal development and survival to adulthood.
Abstract
High-throughput sequencing describes multiple alterations in individual tumors, but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are ...required for functional validation and to identify therapeutic targets of high significance for each patient. Here, we establish a Cre-ER
T2
-loxP (causes recombination, estrogen receptor mutant T2, locus of X-over P1) based inducible RNAi- (ribonucleic acid interference) mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition is initiated in mice harboring orthotopic tumors. In fluorochrome guided, competitive in vivo trials, silencing of the apoptosis regulator
MCL1
(myeloid cell leukemia sequence 1) correlates to pharmacological
MCL1
inhibition in patients´ tumors, demonstrating the ability of the method to detect therapeutic vulnerabilities. The technique identifies a major tumor-maintaining potency of the
MLL-AF4
(mixed lineage leukemia, ALL1-fused gene from chromosome 4) fusion, restricted to samples carrying the translocation.
DUX4
(double homeobox 4) plays an essential role in patients’ leukemias carrying the recently described
DUX4-IGH
(immunoglobulin heavy chain) translocation, while the downstream mediator
DDIT4L
(DNA-damage-inducible transcript 4 like) is identified as therapeutic vulnerability. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.
Philadelphia-like B-cell precursor acute lymphoblastic leukemia (Ph-like ALL) is characterized by distinct genetic alterations and inferior prognosis in children and younger adults. The purpose of ...this study was a genetic and clinical characterization of Ph-like ALL in adults. Twenty-six (13%) of 207 adult patients (median age: 42 years) with B-cell precursor ALL (BCP-ALL) were classified as having Ph-like ALL using gene expression profiling. The frequency of Ph-like ALL was 27% among 95 BCP-ALL patients negative for BCR-ABL1 and KMT2A-rearrangements. IGH-CRLF2 rearrangements (6/16; P=0.002) and mutations in JAK2 (7/16; P<0.001) were found exclusively in the Ph-like ALL subgroup. Clinical and outcome analyses were restricted to patients treated in German Multicenter Study Group for Adult ALL (GMALL) trials 06/99 and 07/03 (n=107). The complete remission rate was 100% among both Ph-like ALL patients (n=19) and the "remaining BCP-ALL" cases (n=40), i.e. patients negative for BCR-ABL1 and KMT2A-rearrangements and the Ph-like subtype. Significantly fewer Ph-like ALL patients reached molecular complete remission (33% versus 79%; P=0.02) and had a lower probability of continuous complete remission (26% versus 60%; P=0.03) and overall survival (22% versus 64%; P=0.006) at 5 years compared to the remaining BCP-ALL patients. The profile of genetic lesions in adults with Ph-like ALL, including older adults, resembles that of pediatric Ph-like ALL and differs from the profile in the remaining BCP-ALL. Our study is the first to demonstrate that Ph-like ALL is associated with inferior outcomes in intensively treated older adult patients. Ph-like adult ALL should be recognized as a distinct, high-risk entity and further research on improved diagnostic and therapeutic approaches is needed. (NCT00199056, NCT00198991).
Previous studies demonstrated that splicing factor mutations are recurrent events in hematopoietic malignancies with both clinical and functional implications. However, their aberrant splicing ...patterns in acute myeloid leukemia remain largely unexplored. In this study, we characterized mutations in SRSF2, U2AF1, and SF3B1, the most commonly mutated splicing factors. In our clinical analysis of 2678 patients, splicing factor mutations showed inferior relapse-free and overall survival, however, these mutations did not represent independent prognostic markers. RNA-sequencing of 246 and independent validation in 177 patients revealed an isoform expression profile which is highly characteristic for each individual mutation, with several isoforms showing a strong dysregulation. By establishing a custom differential splice junction usage pipeline, we accurately detected aberrant splicing in splicing factor mutated samples. A large proportion of differentially used junctions were novel, including several junctions in leukemia-associated genes. In SRSF2(P95H) mutants, we further explored the possibility of a cascading effect through the dysregulation of the splicing pathway. Furthermore, we observed a validated impact on overall survival for two junctions overused in SRSF2(P95H) mutants. We conclude that splicing factor mutations do not represent independent prognostic markers. However, they do have genome-wide consequences on gene splicing leading to dysregulated isoform expression of several genes.
Primary therapy resistance is a major problem in acute myeloid leukemia treatment. We set out to develop a powerful and robust predictor for therapy resistance for intensively treated adult patients. ...We used two large gene expression data sets (n=856) to develop a predictor of therapy resistance, which was validated in an independent cohort analyzed by RNA sequencing (n=250). In addition to gene expression markers, standard clinical and laboratory variables as well as the mutation status of 68 genes were considered during construction of the model. The final predictor (PS29MRC) consisted of 29 gene expression markers and a cytogenetic risk classification. A continuous predictor is calculated as a weighted linear sum of the individual variables. In addition, a cut off was defined to divide patients into a high-risk and a low-risk group for resistant disease. PS29MRC was highly significant in the validation set, both as a continuous score (OR=2.39,
=8.63·10
, AUC=0.76) and as a dichotomous classifier (OR=8.03,
=4.29·10
); accuracy was 77%. In multivariable models, only
mutation, age and PS29MRC (continuous: OR=1.75,
=0.0011; dichotomous: OR=4.44,
=0.00021) were left as significant variables. PS29MRC dominated all models when compared with currently used predictors, and also predicted overall survival independently of established markers. When integrated into the European LeukemiaNet (ELN) 2017 genetic risk stratification, four groups (median survival of 8, 18, 41 months, and not reached) could be defined (
=4.01·10
). PS29MRC will make it possible to design trials which stratify induction treatment according to the probability of response, and refines the ELN 2017 classification.
To identify a robust prognostic gene expression signature as an independent predictor of survival of patients with acute myeloid leukemia (AML) and use it to improve established risk classification.
...Four independent sets totaling 499 patients with AML carrying various cytogenetic and molecular abnormalities were used as training sets. Two independent patient sets composed of 825 patients were used as validation sets. Notably, patients from different sets were treated with different protocols, and their gene expression profiles were derived using different microarray platforms. Cox regression and Kaplan-Meier methods were used for survival analyses.
A prognostic signature composed of 24 genes was derived from a meta-analysis of Cox regression values of each gene across the four training sets. In multivariable models, a higher sum value of the 24-gene signature was an independent predictor of shorter overall (OS) and event-free survival (EFS) in both training and validation sets (P < .01). Moreover, this signature could substantially improve the European LeukemiaNet (ELN) risk classification of AML, and patients in three new risk groups classified by the integrated risk classification showed significantly (P < .001) distinct OS and EFS.
Despite different treatment protocols applied to patients and use of different microarray platforms for expression profiling, a common prognostic gene signature was identified as an independent predictor of survival of patients with AML. The integrated risk classification incorporating this gene signature provides a better framework for risk stratification and outcome prediction than the ELN classification.
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