Philadelphia chromosome (Ph)-like acute lymphoblastic leukemia (ALL) is a high-risk subtype of ALL in children. There are conflicting data on the incidence and prognosis of Ph-like ALL in adults. ...Patients with newly diagnosed B-cell ALL (B-ALL) who received frontline chemotherapy at MD Anderson Cancer Center underwent gene expression profiling of leukemic cells. Of 148 patients, 33.1% had Ph-like, 31.1% had Ph+, and 35.8% had other B-ALL subtypes (B-other). Within the Ph-like ALL cohort, 61% had cytokine receptor-like factor 2 (CRLF2) overexpression. Patients with Ph-like ALL had significantly worse overall survival (OS), and event-free survival compared with B-other with a 5-year survival of 23% (vs 59% for B-other, P = .006). Sixty-eight percent of patients with Ph-like ALL were of Hispanic ethnicity. The following were associated with inferior OS on multivariable analysis: age (hazard ratio HR, 3.299; P < .001), white blood cell count (HR, 1.910; P = .017), platelet count (HR, 7.437; P = .005), and Ph-like ALL (HR, 1.818; P = .03). Next-generation sequencing of the CRLF2+ group identified mutations in the JAK-STAT and Ras pathway in 85% of patients, and 20% had a CRLF2 mutation. Within the CRLF2+ group, JAK2 mutation was associated with inferior outcomes. Our findings show high frequency of Ph-like ALL in adults, an increased frequency of Ph-like ALL in adults of Hispanic ethnicity, significantly inferior outcomes of adult patients with Ph-like ALL, and significantly worse outcomes in the CRLF2+ subset of Ph-like ALL. Novel strategies are needed to improve the outcome of these patients.
•Approximately 20% to 25% of adults with B-ALL have Ph-like ALL with increased frequency of Ph-like ALL in adults with Hispanic ethnicity.•Adult patients with CRLF2+ ALL have poor long-term outcomes; novel strategies are needed to improve the outcomes.
Targeting TRK family proteins in cancer Khotskaya, Yekaterina B; Holla, Vijaykumar R; Farago, Anna F ...
Pharmacology & therapeutics (Oxford)
173
Journal Article
Recenzirano
The tropomyosin receptor kinase (TRK) family includes TRKA, TRKB, and TRKC proteins, which are encoded by NTRK1, NTRK2 and NTRK3 genes, respectively. Binding of neurotrophins to TRK proteins induces ...receptor dimerization, phosphorylation, and activation of the downstream signaling cascades via PI3K, RAS/MAPK/ERK, and PLC-gamma. TRK pathway aberrations, including gene fusions, protein overexpression, and single nucleotide alterations, have been implicated in the pathogenesis of many cancer types, with NTRK gene fusions being the most well validated oncogenic events to date. Although the NTRK gene fusions are infrequent in most cancer types, certain rare tumor types are predominately driven by these events. Conversely, in more common histologies, such as lung and colorectal cancers, prevalence of the NTRK fusions is well below 5%. Selective inhibition of TRK signaling may therefore be beneficial among patients whose tumors vary in histologies, but share underlying oncogenic NTRK gene alterations. Currently, several TRK-targeting compounds are in clinical development. The ongoing Phase 2 trials with entrectinib and LOXO-101, two of the leading TRK inhibitors, are designed as 'basket trials', inclusive of patients whose tumors harbor NTRK gene fusions, independent of histology. Additional Phase 1 studies of other TRK inhibitors, including MGCD516, PLX7486, DS-6051b, and TSR-011, are underway. Interim data examining NTRK-rearranged tumors treated with entrectinib or LOXO-101 demonstrate encouraging activity, with patients achieving rapid and durable responses. Consequently, both drugs have achieved orphan designation from regulatory agencies, and efforts are underway to further expedite their development.
Determine the characteristics of percutaneous core biopsies that are adequate for a next generation sequencing (NGS) genomic panel.
All patients undergoing percutaneous core biopsies in ...interventional radiology (IR) with samples evaluated for a 46-gene NGS panel during 1-year were included in this retrospective study. Patient and procedure variables were collected. An imaging-based likelihood of adequacy score incorporating targeting and sampling factors was assigned to each biopsied lesion. Univariate and multivariate logistic regression was performed.
153 patients were included (58.2% female, average age 59.5 years). The most common malignancy was lung cancer (40.5%), most common biopsied site was lung (36%), and average size of biopsied lesions was 3.8 cm (+/- 2.7). Adequacy for NGS was 69.9%. Univariate analysis showed higher likelihood of adequacy score (p = 0.004), primary malignancy type (p = 0.03), and absence of prior systemic therapy (p = 0.018) were associated with adequacy for NGS. Multivariate analysis showed higher adequacy for lesions with likelihood of adequacy scored 3 (high) versus lesions scored 1 (low) (OR, 7.82; p = 0.002). Melanoma lesions had higher adequacy for NGS versus breast cancer lesions (OR 9.5; p = 0.01). Absence of prior systemic therapy (OR, 6.1; p = 0.02) and systemic therapy </ = 3 months (OR 3.24; p = 0.01) compared to systemic therapy >3 months before biopsy yielded greater adequacy for NGS. Lesions <3 cm had greater adequacy for NGS than larger lesions (OR 2.72, p = 0.02).
As targeted therapy becomes standard for more cancers, percutaneous biopsy specimens adequate for NGS genomic testing will be needed. An imaging-based likelihood of adequacy score assigned by IR physicians and other pre-procedure variables can help predict the likelihood of biopsy adequacy for NGS.
Physicians are expected to assess prognosis both for patient counseling and for determining suitability for clinical trials. Increasingly, cell-free circulating tumor DNA (cfDNA) sequencing is being ...performed for clinical decision making. We sought to determine whether variant allele frequency (VAF) in cfDNA is associated with prognosis.
We performed a retrospective analysis of 298 patients with metastatic disease who underwent clinical comprehensive cfDNA analysis and assessed association between VAF and overall survival.
cfDNA mutations were detected in 240 patients (80.5%). Median overall survival (OS) was 11.5 months. cfDNA mutation detection and number of nonsynonymous mutations (NSM) significantly differed between tumor types, being lowest in appendiceal cancer and highest in colon cancer. Having more than one NSM detected was associated with significantly worse OS (HR = 2.3;
< 0.0001). VAF was classified by quartiles, Q1 lowest, Q4 highest VAF. Higher VAF levels were associated with a significantly worse overall survival (VAF Q3 HR 2.3,
= 0.0069; VAF Q4 HR = 3.8,
< 0.0001) on univariate analysis. On multivariate analysis, VAF Q4, male sex, albumin level <3.5 g/dL, number of nonvisceral metastatic sites >0 and number of prior therapies >4 were independent predictors of worse OS.
Higher levels of cfDNA VAF and a higher number of NSMs were associated with worse OS in patients with metastatic disease. Further study is needed to determine optimal VAF thresholds for clinical decision making and the utility of cfDNA VAF as a prognostic marker in different tumor types.
The tools of next-generation sequencing (NGS) technology, such as targeted sequencing of candidate cancer genes and whole-exome and -genome sequencing, coupled with encouraging clinical results based ...on the use of targeted therapeutics and biomarker-guided clinical trials, are fueling further technological advancements of NGS technology. However, NGS data interpretation is associated with challenges that must be overcome to promote the techniques' effective integration into clinical oncology practice. Specifically, sequencing of a patient's tumor often yields 30-65 somatic variants, but most of these variants are "passenger" mutations that are phenotypically neutral and thus not targetable. Therefore, NGS data must be interpreted by multidisciplinary decision-support teams to determine mutation actionability and identify potential "drivers," so that the treating physician can prioritize what clinical decisions can be pursued in order to provide cancer therapy that is personalized to the patient and his or her unique genome.
A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep ...neural networks for prediction of drug response and assessed their performance on multiple clinical cohorts. We demonstrate that deep neural networks outperform the current state in machine learning frameworks. We provide a proof of concept for the use of deep neural network-based frameworks to aid precision oncology strategies.
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•A machine learning (ML) workflow is designed to predict drug response in cancer patients•Deep neural networks (DNNs) surpass current ML algorithms in drug response prediction•DNNs predict drug response and survival in various large clinical cohorts•DNNs capture intricate biological interactions linked to specific drug response pathways
Sakellaropoulos et al. designed a machine learning workflow to predict drug response and survival of cancer patients. All pipelines are trained on a large panel of cancer cell lines and tested in clinical cohorts. DNN outperforms other machine learning algorithms by capturing pathways that link gene expression with drug response.
Since the discovery that DNA alterations initiate tumorigenesis, scientists and clinicians have been exploring ways to counter these changes with targeted therapeutics. The sequencing of tumor DNA ...was initially limited to highly actionable hot spots-areas of the genome that are frequently altered and have an approved matched therapy in a specific tumor type. Large-scale genome sequencing programs quickly developed technological improvements that enabled the deployment of whole-exome and whole-genome sequencing technologies at scale for pristine sample materials in research environments. However, the turning point for precision medicine in oncology was the innovations in clinical laboratories that improved turnaround time, depth of coverage, and the ability to reliably sequence archived, clinically available samples. Today, tumor genome sequencing no longer suffers from significant technical or financial hurdles, and the next opportunity for improvement lies in the optimal utilization of the technologies and data for many different tumor types.
National educational organizations have called upon scientists to become involved in K-12 education reform. From sporadic interaction with students to more sustained partnerships with teachers, the ...engagement of scientists takes many forms. In this case, scientists from the American Society of Human Genetics (ASHG), the Genetics Society of America (GSA), and the National Society of Genetic Counselors (NSGC) have partnered to organize an essay contest for high school students as part of the activities surrounding National DNA Day. We describe a systematic analysis of 500 of 2443 total essays submitted in response to this contest over 2 years. Our analysis reveals the nature of student misconceptions in genetics, the possible sources of these misconceptions, and potential ways to galvanize genetics education.
Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined. The relationships between patterns of mutations and epigenetic phenotypes are not yet clear.
We ...analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis.
AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes. Of these, an average of 5 are in genes that are recurrently mutated in AML. A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples. Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcription-factor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumor-suppressor genes (16%), DNA-methylation-related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%). Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories.
We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients. The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification. (Funded by the National Institutes of Health.).
Malignant gliomas are a group of intracranial cancers associated with disproportionately high mortality and morbidity. Here, we report ultradeep targeted sequencing of a prospective cohort of 237 ...tumors from 234 patients consisting of both glioblastoma (GBM) and lower-grade glioma (LGG) using our customized gene panels. We identified 2,485 somatic mutations, including single-nucleotide substitutions and small indels, using a validated in-house protocol. Sixty-one percent of the mutations were contributed by 12 hypermutators. The hypermutators were enriched for recurrent tumors and had comparable outcome, and most were associated with temozolomide exposure.
was the most frequently mutated gene in our cohort, followed by
and
We detected at least one
mutation in 23% of LGGs, which was significantly higher than 6% seen in The Cancer Genome Atlas, a pattern that can be partially explained by the different patient composition and sequencing depth.
hotspot mutations were found with higher frequencies in LGG (83%) and secondary GBM (77%) than primary GBM (9%). Multivariate analyses controlling for age, histology, and tumor grade confirm the prognostic value of
mutation. We predicted 1p/19q status using the panel sequencing data and received only modest performance by benchmarking the prediction to FISH results of 50 tumors. Targeted therapy based on the sequencing data resulted in three responders out of 14 participants. In conclusion, our study suggests ultradeep targeted sequencing can recapitulate previous findings and can be a useful approach in the clinical setting.
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