A key constraint in genomic testing in oncology is that matched normal specimens are not commonly obtained in clinical practice. Thus, while well-characterized genomic alterations do not require ...normal tissue for interpretation, a significant number of alterations will be unknown in whether they are germline or somatic, in the absence of a matched normal control. We introduce SGZ (somatic-germline-zygosity), a computational method for predicting somatic vs. germline origin and homozygous vs. heterozygous or sub-clonal state of variants identified from deep massively parallel sequencing (MPS) of cancer specimens. The method does not require a patient matched normal control, enabling broad application in clinical research. SGZ predicts the somatic vs. germline status of each alteration identified by modeling the alteration's allele frequency (AF), taking into account the tumor content, tumor ploidy, and the local copy number. Accuracy of the prediction depends on the depth of sequencing and copy number model fit, which are achieved in our clinical assay by sequencing to high depth (>500x) using MPS, covering 394 cancer-related genes and over 3,500 genome-wide single nucleotide polymorphisms (SNPs). Calls are made using a statistic based on read depth and local variability of SNP AF. To validate the method, we first evaluated performance on samples from 30 lung and colon cancer patients, where we sequenced tumors and matched normal tissue. We examined predictions for 17 somatic hotspot mutations and 20 common germline SNPs in 20,182 clinical cancer specimens. To assess the impact of stromal admixture, we examined three cell lines, which were titrated with their matched normal to six levels (10-75%). Overall, predictions were made in 85% of cases, with 95-99% of variants predicted correctly, a significantly superior performance compared to a basic approach based on AF alone. We then applied the SGZ method to the COSMIC database of known somatic variants in cancer and found >50 that are in fact more likely to be germline.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cancer treatments have evolved from indiscriminate cytotoxic agents to selective genome- and immune-targeted drugs that have transformed the outcomes of some malignancies
. Tumor complexity and ...heterogeneity suggest that the 'precision medicine' paradigm of cancer therapy requires treatment to be personalized to the individual patient
. To date, precision oncology trials have been based on molecular matching with predetermined monotherapies
. Several of these trials have been hindered by very low matching rates, often in the 5-10% range
, and low response rates. Low matching rates may be due to the use of limited gene panels, restrictive molecular matching algorithms, lack of drug availability, or the deterioration and death of end-stage patients before therapy can be implemented. We hypothesized that personalized treatment with combination therapies would improve outcomes in patients with refractory malignancies. As a first test of this concept, we implemented a cross-institutional prospective study (I-PREDICT, NCT02534675 ) that used tumor DNA sequencing and timely recommendations for individualized treatment with combination therapies. We found that administration of customized multidrug regimens was feasible, with 49% of consented patients receiving personalized treatment. Targeting of a larger fraction of identified molecular alterations, yielding a higher 'matching score', was correlated with significantly improved disease control rates, as well as longer progression-free and overall survival rates, compared to targeting of fewer somatic alterations. Our findings suggest that the current clinical trial paradigm for precision oncology, which pairs one driver mutation with one drug, may be optimized by treating molecularly complex and heterogeneous cancers with combinations of customized agents.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Neuroblastoma is characterized by a relative paucity of recurrent somatic mutations at diagnosis. However, recent studies have shown that the mutational burden increases at relapse, likely as a ...result of clonal evolution of mutation-carrying cells during primary treatment. To inform the development of personalized therapies, we sought to further define the frequency of potentially actionable mutations in neuroblastoma, both at diagnosis and after chemotherapy. We performed a retrospective study to determine mutation frequency, the only inclusion criterion being availability of cancer gene panel sequencing data from Foundation Medicine. We analyzed 151 neuroblastoma tumor samples: 44 obtained at diagnosis, 42 at second look surgery or biopsy for stable disease after chemotherapy, and 59 at relapse (6 were obtained at unknown time points). Nine patients had multiple tumor biopsies. ALK was the most commonly mutated gene in this cohort, and we observed a higher frequency of suspected oncogenic ALK mutations in relapsed disease than at diagnosis. Patients with relapsed disease had, on average, a greater number of mutations reported to be recurrent in cancer, and a greater number of mutations in genes that are potentially targetable with available therapeutics. We also observed an enrichment of reported recurrent RAS/MAPK pathway mutations in tumors obtained after chemotherapy. Our data support recent evidence suggesting that neuroblastomas undergo substantial mutational evolution during therapy, and that relapsed disease is more likely to be driven by a targetable oncogenic pathway, highlighting that it is critical to base treatment decisions on the molecular profile of the tumor at the time of treatment. However, it will be necessary to conduct prospective clinical trials that match sequencing results to targeted therapeutic intervention to determine if cancer genomic profiling improves patient outcomes.
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High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 ...blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types.
In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types.
We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB.
These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The management of non-small cell lung carcinoma (NSCLC) has been transformed by the observation that lung adenocarcinomas harboring mutations in epidermal growth factor receptor (EGFR) are uniquely ...sensitive to EGFR tyrosine kinase inhibitors (TKI). In these patients, acquired resistance to EGFR-TKI develops after a median of 10 to 14 months, at which time the current standard practice is to switch to conventional cytotoxic chemotherapy. Several possible mechanisms for acquired resistance have been identified, the most common being the development of an EGFR T790M gatekeeper mutation in more than 50% of cases. In this review, we discuss recent advances in the understanding of acquired TKI resistance in EGFR-mutant lung cancer and review therapeutic progress with second generation TKIs and combinations of targeted therapies.
BRAF mutations occur in non-small-cell lung cancer. Therapies targeting BRAF mutant tumors have recently been identified. We undertook this study to determine the clinical characteristics of patients ...with lung adenocarcinomas harboring BRAF mutations.
We reviewed data from consecutive patients with lung adenocarcinoma whose tumors underwent BRAF, EGFR, and KRAS mutation testing as well as fluorescence in situ hybridization for ALK rearrangements. Patient characteristics including age, sex, race, performance status, smoking history, stage, treatment history, and overall survival were collected.
Among 697 patients with lung adenocarcinoma, BRAF mutations were present in 18 patients (3%; 95% CI, 2% to 4%). The BRAF mutations identified were V600E (50%), G469A (39%), and D594G (11%). Mutations in EGFR were present in 24%, KRAS in 25%, and ALK translocations in 6%. In contrast to patients with EGFR mutations and ALK rearrangements who were mostly never smokers, all patients with BRAF mutations were current or former smokers (P < .001). The median overall survival of advanced-stage patients with BRAF mutations was not reached. In comparison, the median overall survival of patients with EGFR mutations was 37 months (P = .73), with KRAS mutations was 18 months (P = .12), and with ALK rearrangements was not reached (P = .64).
BRAF mutations occur in 3% of patients with lung adenocarcinoma and occur more commonly in current and former smokers. The incidence of BRAF mutations other than V600E is significantly higher in lung cancer than in melanoma.
The third-generation EGFR inhibitor, osimertinib, is the first mutant-selective inhibitor that has received regulatory approval for the treatment of patients with
-mutant lung cancer. Despite the ...development of highly selective third-generation inhibitors, acquired resistance remains a significant clinical challenge. Recently, we and others have identified a novel osimertinib resistance mutation, G724S, which was not predicted in
screens. Here, we investigate how G724S confers resistance to osimertinib.
We combine structure-based predictive modeling of G724S in combination with the 2 most common EGFR-activating mutations, exon 19 deletion (Ex19Del) and L858R, with
drug-response models and patient genomic profiling.
Our simulations suggest that the G724S mutation selectively reduces osimertinib-binding affinity in the context of Ex19Del. Consistent with our simulations, cell lines transduced with Ex19Del/G724S demonstrate resistance to osimertinib, whereas cells transduced with L858R/G724S are sensitive to osimertinib. Subsequent clinical genomic profiling data further suggest G724S occurs with Ex19Del but not L858R. Furthermore, we demonstrate that Ex19Del/G724S retains sensitivity to afatinib, but not to erlotinib, suggesting a possible therapy for patients at the time of disease relapse.
Altogether, these data suggest that G724S is an allele-specific resistance mutation emerging in the context of Ex19Del but not L858R. Our results fundamentally reframe the problem of targeted therapy resistance from one focused on the "drug-resistance mutation" pair to one focused on the "activating mutation-drug-resistance mutation" trio. This has broad implications across clinical oncology.
IMPORTANCE: Data sets linking comprehensive genomic profiling (CGP) to clinical outcomes may accelerate precision medicine. OBJECTIVE: To assess whether a database that combines EHR-derived clinical ...data with CGP can identify and extend associations in non–small cell lung cancer (NSCLC). DESIGN, SETTING, AND PARTICIPANTS: Clinical data from EHRs were linked with CGP results for 28 998 patients from 275 US oncology practices. Among 4064 patients with NSCLC, exploratory associations between tumor genomics and patient characteristics with clinical outcomes were conducted, with data obtained between January 1, 2011, and January 1, 2018. EXPOSURES: Tumor CGP, including presence of a driver alteration (a pathogenic or likely pathogenic alteration in a gene shown to drive tumor growth); tumor mutation burden (TMB), defined as the number of mutations per megabase; and clinical characteristics gathered from EHRs. MAIN OUTCOMES AND MEASURES: Overall survival (OS), time receiving therapy, maximal therapy response (as documented by the treating physician in the EHR), and clinical benefit rate (fraction of patients with stable disease, partial response, or complete response) to therapy. RESULTS: Among 4064 patients with NSCLC (median age, 66.0 years; 51.9% female), 3183 (78.3%) had a history of smoking, 3153 (77.6%) had nonsquamous cancer, and 871 (21.4%) had an alteration in EGFR, ALK, or ROS1 (701 17.2% with EGFR, 128 3.1% with ALK, and 42 1.0% with ROS1 alterations). There were 1946 deaths in 7 years. For patients with a driver alteration, improved OS was observed among those treated with (n = 575) vs not treated with (n = 560) targeted therapies (median, 18.6 months 95% CI, 15.2-21.7 vs 11.4 months 95% CI, 9.7-12.5 from advanced diagnosis; P < .001). TMB (in mutations/Mb) was significantly higher among smokers vs nonsmokers (8.7 IQR, 4.4-14.8 vs 2.6 IQR, 1.7-5.2; P < .001) and significantly lower among patients with vs without an alteration in EGFR (3.5 IQR, 1.76-6.1 vs 7.8 IQR, 3.5-13.9; P < .001), ALK (2.1 IQR, 0.9-4.0 vs 7.0 IQR, 3.5-13.0; P < .001), RET (4.6 IQR, 1.7-8.7 vs 7.0 IQR, 2.6-13.0; P = .004), or ROS1 (4.0 IQR, 1.2-9.6 vs 7.0 IQR, 2.6-13.0; P = .03). In patients treated with anti–PD-1/PD-L1 therapies (n = 1290, 31.7%), TMB of 20 or more was significantly associated with improved OS from therapy initiation (16.8 months 95% CI, 11.6-24.9 vs 8.5 months 95% CI, 7.6-9.7; P < .001), longer time receiving therapy (7.8 months 95% CI, 5.5-11.1 vs 3.3 months 95% CI, 2.8-3.7; P < .001), and increased clinical benefit rate (80.7% vs 56.7%; P < .001) vs TMB less than 20. CONCLUSIONS AND RELEVANCE: Among patients with NSCLC included in a longitudinal database of clinical data linked to CGP results from routine care, exploratory analyses replicated previously described associations between clinical and genomic characteristics, between driver mutations and response to targeted therapy, and between TMB and response to immunotherapy. These findings demonstrate the feasibility of creating a clinicogenomic database derived from routine clinical experience and provide support for further research and discovery evaluating this approach in oncology.
Although the BRAF V600E base substitution is an approved target for the BRAF inhibitors in melanoma, BRAF gene fusions have not been investigated as anticancer drug targets. In our study, a wide ...variety of tumors underwent comprehensive genomic profiling for hundreds of known cancer genes using the FoundationOne™ or FoundationOne Heme™ comprehensive genomic profiling assays. BRAF fusions involving the intact in‐frame BRAF kinase domain were observed in 55 (0.3%) of 20,573 tumors, across 12 distinct tumor types, including 20 novel BRAF fusions. These comprised 29 unique 5′ fusion partners, of which 31% (9) were known and 69% (20) were novel. BRAF fusions included 3% (14/531) of melanomas; 2% (15/701) of gliomas; 1.0% (3/294) of thyroid cancers; 0.3% (3/1,062) pancreatic carcinomas; 0.2% (8/4,013) nonsmall‐cell lung cancers and 0.2% (4/2,154) of colorectal cancers, and were enriched in pilocytic (30%) vs. nonpilocytic gliomas (1%; p < 0.0001), Spitzoid (75%) vs. nonSpitzoid melanomas (1%; p = 0.0001), acinar (67%) vs. nonacinar pancreatic cancers (<1%; p < 0.0001) and papillary (3%) vs. nonpapillary thyroid cancers (0%; p < 0.03). Clinical responses to trametinib and sorafenib are presented. In conclusion, BRAF fusions are rare driver alterations in a wide variety of malignant neoplasms, but enriched in Spitzoid melanoma, pilocytic astrocytomas, pancreatic acinar and papillary thyroid cancers.
What's new?
New results may help target a rare genetic alteration that promotes cancer. Activation of the BRAF gene is already known to spur tumor growth, and usually that activation results from a single amino acid substitution. BRAF‐inhibiting treatments, then, target that mutation. However, in some cases, BRAF gets revved up by a gene fusion. In our study, the authors tested 20,000 tumors and identified 55 BRAF gene fusions in 12 different tumor types. They found the gene fusions occurred more frequently in certain histologic subtypes, information which will help guide treatment strategies for patients with these tumor subtypes.
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