Molecular profiling using the 92-gene assay for tumor classification of brain metastases.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e13583-e13583
Author(s):  
Andrew Jacob Brenner ◽  
Raul Collazo ◽  
Catherine A. Schnabel ◽  
F Anthony Greco
Keyword(s):  
Brain Metastases ◽  
Targeted Therapies ◽  
Primary Tumor ◽  
Tumor Type ◽  
Federal Drug Administration ◽  
Gene Assay ◽  
Clinical Series ◽  
The Us ◽  
Tumor Types

e13583 Background: Nearly 200,000 patients are diagnosed with brain metastases in the US annually. Advances in targeted therapies make definitive diagnosis of the primary tumor type important but can be challenging in many patients. The 92-gene assay is a validated gene expression classifier of 50 tumor types/subtypes for patients with uncertain diagnoses. Results from a clinical series of brain biopsies and potential impact on treatment were evaluated. Methods: An IRB-approved, de-identified database of clinical and molecular information from biopsies (N = 24,486) submitted for testing with the 92-gene assay (CancerTYPE ID, Biotheranostics, Inc.) as part of routine care were reviewed. Descriptive analysis included patient demographics and molecular diagnoses. Results: Analysis included 464 brain biopsies. A molecular diagnosis was provided in 433 (93.3%) tested ( < 5% assay failure rate) with 24 different tumor types. Six primary tumor types made up the majority (67.4%) with almost one-third of the molecular predictions being Lung (31.2%), followed by Neuroendocrine (NET) (9.9%), Sarcoma (7.9%), Skin (6.4%), Gastroesophageal (6.2%), and Urinary bladder (5.8%). All of these 6 tumor types, for which activity in the CNS has been documented, have immune checkpoint inhibitors or other targeted therapies approved in selected cases by the US Federal Drug Administration (FDA) (Table). Conclusions: Molecular classification of brain metastases can identify distinct tumor types for which there are FDA approved targeted medications. Improving diagnostic precision with the 92-gene assay helps identify a subset of therapy-responsive metastatic brain tumors, thus improving therapy and possibly providing better outcomes and survival. [Table: see text]

scholarly journals OTHR-16. MOLECULAR PROFILING USING THE 92-GENE ASSAY FOR TUMOR CLASSIFICATION OF BRAIN METASTASES

2019 ◽  
Vol 1 (Supplement_1) ◽  
pp. i21-i21
Author(s):  
Andrew Brenner ◽  
Raul Collazo ◽  
Catherine Schnabel ◽  
Anthony Greco
Keyword(s):  
Brain Metastases ◽  
Targeted Therapies ◽  
Primary Tumor ◽  
Tumor Type ◽  
Federal Drug Administration ◽  
Gene Assay ◽  
Clinical Series ◽  
The Us ◽  
Tumor Types

Abstract BACKGROUND: Nearly 200,000 patients are diagnosed with brain metastases in the US annually. Advances in targeted therapies make definitive diagnosis of the primary tumor type important but can be challenging in many patients. The 92-gene assay is a validated gene expression classifier of 50 tumor types for patients with uncertain tissue of origin diagnoses. Results from a clinical series of brain biopsies and potential impact on treatment were evaluated. METHODS: An IRB approved, de-identified database of clinical and molecular information from biopsies (N = 24,486) submitted for testing with the 92-gene assay (CancerTYPE ID, Biotheranostics, Inc.) as part of routine care were reviewed. Descriptive analysis included patient demographics and molecular diagnoses. RESULTS: Analysis included 464 brain biopsies. A molecular diagnosis was provided in 433 (93.3%) tested (&lt; 5% assay failure rate) with 24 different tumor types. Six primary tumor types made up the majority (67.4%) with almost one-third of the molecular predictions being Lung (31.2%), followed by Neuroendocrine (NET) (9.9%), Sarcoma (7.9%), Skin (6.4%), Gastroesophageal (6.2%), and Urinary bladder (5.8%). All of these 6 tumor types, for which activity in the CNS has been documented, have immune checkpoint inhibitors or other targeted therapies approved in selected cases by the US Federal Drug Administration (FDA). CONCLUSIONS: Molecular classification of brain metastases can identify distinct tumor types for which there are FDA approved targeted medications. Improving diagnostic precision with the 92-gene assay helps identify a subset of therapy-responsive metastatic brain tumors, thus improving therapy and possibly providing better outcomes and survival.

Brain metastases in patients diagnosed with a solid primary cancer during childhood: experience from a single referral cancer center

2014 ◽  
Vol 14 (4) ◽  
pp. 372-385 ◽  
Author(s):  
Dima Suki ◽  
Rami Khoury Abdulla ◽  
Minming Ding ◽  
Soumen Khatua ◽  
Raymond Sawaya
Keyword(s):  
Brain Metastasis ◽  
Brain Metastases ◽  
Primary Tumor ◽  
Lung Metastases ◽  
Cancer Center ◽  
Leptomeningeal Disease ◽  
Tumor Type ◽  
Primary Cancer ◽  
Extracranial Metastases ◽  
The Brain

Object Metastasis to the brain is frequent in adult cancer patients but rare among children. Advances in primary tumor treatment and the associated prolonged survival are said to have increased the frequency of brain metastasis in children. The authors present a series of cases of brain metastases in children diagnosed with a solid primary cancer, evaluate brain metastasis trends, and describe tumor type, patterns of occurrence, and prognosis. Methods Patients with brain metastases whose primary cancer was diagnosed during childhood were identified in the 1990–2012 Tumor Registry at The University of Texas M.D. Anderson Cancer Center. A review of their hospital records provided demographic data, history, and clinical data, including primary cancer sites, number and location of brain metastases, sites of extracranial metastases, treatments, and outcomes. Results Fifty-four pediatric patients (1.4%) had a brain metastasis from a solid primary tumor. Sarcomas were the most common (54%), followed by melanoma (15%). The patients' median ages at diagnosis of the primary cancer and the brain metastasis were 11.37 years and 15.03 years, respectively. The primary cancer was localized at diagnosis in 48% of patients and disseminated regionally in only 14%. The primary tumor and brain metastasis presented synchronously in 15% of patients, and other extracranial metastases were present when the primary cancer was diagnosed. The remaining patients were diagnosed with brain metastasis after initiation of primary cancer treatment, with a median presentation interval of 17 months after primary cancer diagnosis (range 2–77 months). At the time of diagnosis, the brain metastasis was the first site of systemic metastasis in only 4 (8%) of the 51 patients for whom data were available. Up to 70% of patients had lung metastases when brain metastases were found. Symptoms led to the brain metastasis diagnosis in 65% of cases. Brain metastases were single in 60% of cases and multiple in 35%; 6% had only leptomeningeal disease. The median Kaplan-Meier estimates of survival after diagnoses of primary cancer and brain metastasis were 29 months (95% CI 24–34 months) and 9 months (95% CI 6–11 months), respectively. Untreated patients survived for a median of 0.9 months after brain metastasis diagnosis (95% CI 0.3–1.5 months). Those receiving treatment survived for a median of 8 months after initiation of therapy (95% CI 6–11 months). Conclusions The results of this study challenge the current notion of an increased incidence of brain metastases among children with a solid primary cancer. The earlier diagnosis of the primary cancer, prior to its dissemination to distant sites (especially the brain), and initiation of presumably more effective treatments may support such an observation. However, although the actual number of cases may not be increasing, the prognosis after the diagnosis of a brain metastasis remains poor regardless of the management strategy.

A retrospective survival analysis of whole brain radiotherapy (WBRT) for brain metastases at Mount Vernon Cancer Centre (MVCC)

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 2068-2068
Author(s):  
P. J. Mulholland ◽  
M. Assoku ◽  
P. Sasieni
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Factor ◽  
Brain Metastases ◽  
Whole Brain Radiotherapy ◽  
Skin Tumor ◽  
Unknown Primary ◽  
Tumor Type ◽  
Rank Analysis ◽  
Brain Radiotherapy ◽  
Tumor Types

2068 Background: The primary purpose of this retrospective study was to determine the survival of patients with brain metastases following WBRT with regards to the influence of tumor type, age < 65 versus ≥ 65 (RPA RTOG prognostic factor) and recency of treatment date. Methods: From treatment records we identified 1,926 patients with brain metastases from solid tumors who were treated with WBRT at MVCC between February 1992 and March 2008. Dates of death were sourced from records at MVCC, the Cancer Registry and GP practices. Results: We obtained dates of death for patients with lung (n=804), breast (n=457), colorectal (n=129), skin (n=119), kidney (n=82), and unknown primary (n=124) cancers. 42 patients were excluded from analysis as their tumor types were unspecified. A heterogeneous group of 169 patients with a variety of other primary tumor types were also excluded from our primary analyses. 22% of the patients died within the first month following WBRT and only 2.4% remained alive at 2 years. Log-rank analysis of age < 65 versus ≥ 65 demonstrated improved survival for the former for the colorectal, lung, and skin tumor types (p = 0.0048, 0.0001, and 0.0456 respectively). This relationship did not reach significance for the breast, unknown primary, and renal cancer groups (p = 0.14, 0.13, and 0.06 respectively). With the exception of colorectal cancer, the analysis of the effect of treatment date on survival did not reveal recent improvements in survival for patients with brain metastases. An improvement in survival was experienced by the colorectal subgroup treated after March 2006 (HR= 0.51 95% CI 0.27- 0.96). Conclusions: Our data validate age as an important prognostic factor for many tumor types with notable exceptions for as yet undetermined reasons. Metastasis to the brain is a late stage feature of colorectal malignancy. The survival of the majority of patients undergoing WBRT for brain metastases is poor and with the possible exception of colorectal cancer, has not improved over the last decade. [Table: see text] [Table: see text]

scholarly journals Deep Learning Based Tumor Type Classification Using Gene Expression Data

2018 ◽  
Author(s):  
Boyu Lyu ◽  
Anamul Haque
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Tumor Type ◽  
Differential Analysis ◽  
Rna Seq ◽  
Heat Map ◽  
Standard Practices ◽  
Tumor Types ◽  
Pan Cancer

ABSTRACTDifferential analysis occupies the most significant portion of the standard practices of RNA-Seq analysis. However, the conventional method is matching the tumor samples to the normal samples, which are both from the same tumor type. The output using such method would fail in differentiating tumor types because it lacks the knowledge from other tumor types. Pan-Cancer Atlas provides us with abundant information on 33 prevalent tumor types which could be used as prior knowledge to generate tumor-specific biomarkers. In this paper, we embedded the high dimensional RNA-Seq data into 2-D images and used a convolutional neural network to make classification of the 33 tumor types. The final accuracy we got was 95.59%, higher than another paper applying GA/KNN method on the same dataset. Based on the idea of Guided Grad Cam, as to each class, we generated significance heat-map for all the genes. By doing functional analysis on the genes with high intensities in the heat-maps, we validated that these top genes are related to tumor-specific pathways, and some of them have already been used as biomarkers, which proved the effectiveness of our method. As far as we know, we are the first to apply convolutional neural network on Pan-Cancer Atlas for classification, and we are also the first to match the significance of classification with the importance of genes. Our experiment results show that our method has a good performance and could also apply in other genomics data.

Analysis of the MOSAIC correlative cancer database integrating molecular cancer classification and tumor profiling to identify targeted treatment options for metastatic cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3121-3121
Author(s):  
Li Ma ◽  
Kai Treuner ◽  
Jenna Wong ◽  
David R. Spigel ◽  
Catherine A. Schnabel ◽  
...  
Keyword(s):  
Metastatic Cancer ◽  
Genetic Alterations ◽  
Targeted Treatment ◽  
Unknown Primary ◽  
Molecular Testing ◽  
Tumor Type ◽  
Gene Assay ◽  
Biomarker Analysis ◽  
Biomarker Testing ◽  
Tumor Types

3121 Background: Unless tumor type and genetic alterations can be identified, metastatic cancer patients with unknown or uncertain diagnoses may be limited to empiric chemotherapy. The 92-gene assay (CancerTYPE ID) is a validated gene expression classifier of 50 tumor types and subtypes for patients with cancer of unknown primary (CUP) or ambiguous diagnoses. Multimodal molecular biomarker testing by next-generation sequencing (NGS), tumor mutational burden (TMB), fluorescent in situ hybridization (FISH), microsatellite instability (MSI), and immunohistochemistry (IHC) can identify genetic targets. A database integrating tumor typing with biomarker analysis in metastatic cases was utilized to identify the most prevalent genetic alterations by tumor type. Methods: MOSAIC (Molecular Synergy to Advance Individualized Cancer Care) is an IRB-approved database of cases with CancerTYPE ID testing plus multimodal biomarker testing. The current study determined molecular tumor type followed by molecular profiling by NGS for up to 323 genes, (NeoTYPE profiles, Neogenomics). Results: Tumor type was determined in 1992 of 2151 cases (92.7%), comprised of 27 different tumor types. 72% of cases were comprised of the 7 tumor types shown in the table,which also shows the frequency of the 10 most commonly mutated genes by tumor type. Bolded are genes with actionable genetic mutations for which FDA-approved therapies are not currently indicated in the identified tumor type. Conclusions: Precise targeted treatment for many patients with CUP or ambiguous diagnoses requires accurate diagnosis of the cancer origin combined with multimodal molecular testing to identify actionable genetic alterations in the appropriate cellular context. Future studies will evaluate additional biomarker profiles, including TMB, FISH, MSI, and IHC for cases in the MOSAIC database.[Table: see text]

Racial and Gender Disparities and the Role of Primary Tumor Type on Inpatient Outcomes Following Craniotomy for Brain Metastases

2012 ◽  
Vol 19 (8) ◽  
pp. 2657-2663 ◽  
Author(s):  
Miriam Nuño ◽  
Debraj Mukherjee ◽  
Adam Elramsisy ◽  
Kristin Nosova ◽  
Shivanand P. Lad ◽  
...  
Keyword(s):  
Brain Metastases ◽  
Primary Tumor ◽  
Gender Disparities ◽  
Tumor Type ◽  
Inpatient Outcomes ◽  
And Gender ◽  
Primary Tumor Type

Use of next-generation sequencing (NGS) to identify actionable genomic alterations (GA) in diverse solid tumor types: The Foundation Medicine (FMI) experience with 2,200+ clinical samples.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 11020-11020 ◽  
Author(s):  
Vincent A. Miller ◽  
Jeffrey S. Ross ◽  
Kai Wang ◽  
Siraj M. Ali ◽  
Geoff Otto ◽  
...  
Keyword(s):  
Targeted Therapies ◽  
Drug Targets ◽  
Treatment Options ◽  
Additional Treatment ◽  
Clinical Samples ◽  
Tumor Type ◽  
Kinase Gene ◽  
Hybridization Capture ◽  
Small Indels ◽  
Tumor Types

11020 Background: ST oncology has been transformed by the linkage of GA with targeted therapeutics. Unfortunately, most STs still have no target detected by clinically available assays. More comprehensive testing platforms are needed to determine GA in ST and thus broaden treatment options. We developed a ST NGS diagnostic assay, optimized for routine clinical FFPE specimens including core and fine needle biopsies and malignant effusions, and analyzed > 2,200 patients’ tumors in a CLIA-certified lab (Foundation Medicine). Methods: Hybridization capture of 3,320 exons from 182 cancer-related genes and 37 introns of 14 genes commonly rearranged in cancer was applied to ≥ 50ng of DNA extracted from 2,200+ consecutive FFPE tumor specimens and sequenced to high unique coverage. GA (base substitutions, small indels, rearrangements, copy number alterations) were categorized as “actionable” if directly linked to a clinically available targeted treatment option or a mechanism-driven clinical trial. Results: 2,112/2,221 (95%) of specimens (most common 1° sites: lung 18%, breast 14%, colon 7%, other 34%) were successfully profiled (mean coverage 1134X). Alterations were reported in 155/182 (85%) of genes. Seventy-six percent of cases harbored ≥1 actionable GA, mean 1.6 (range 0-16); sixty-two percent harbored at least one actionable GA not assayed by available tumor-type specific tests or hotspot panels. This approach has led to novel insights into advanced cancer including: 13 novel, potentially druggable kinase gene fusions; alterations in known drug targets (e.g. ALK, EGFR, ERRB2, KIT, MET, PDGFR α and β, RAF1 and RET) in novel tumor types and new mechanisms of resistance to approved targeted therapies. Several patients demonstrated dramatic responses to treatment with targeted therapies directed against these alterations. Conclusions: Comprehensive NGS genomic profiling was successful in profiling >2,200 unselected clinical cases, identified actionable alterations in 76% of cases and provided additional treatment options for 62% of patients targeting alterations in genes not assayed by available hotspot panels.

Evaluation of invasion patterns and their correlation with integrin alphavbeta expression in brain metastases of solid cancers.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 2059-2059
Author(s):  
Anna Sophie Berghoff ◽  
Orsolya Rajky ◽  
Frank Winkler ◽  
Michael Weller ◽  
Christoph Zielinski ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Brain Metastases ◽  
Primary Tumor ◽  
Brain Parenchyma ◽  
T Test ◽  
Integrin Expression ◽  
Tumor Type ◽  
Diffuse Infiltration ◽  
Invasion Pattern ◽  
Invasion Patterns

2059 Background: Understanding the pathobiology of brain metastases (BM) could guide the establishment of new targeted therapies. Methods: We collected 57 autopsy specimens of BM (primary tumor: 27 lung cancer, 6 breast cancer, 8 melanoma, 1 kidney cancer, 2 colorectal cancer, 13 other) and histologically evaluated the patterns of invasion into the surrounding brain parenchyma. Expression of the following integrins was evaluated using immunohistochemistry: with novel antibodies for αv subunit, αvβ3, αvβ5, αvβ6 and αvβ8 integrin. Results: We observed three main invasion patterns: well-demarcated (29/57, 51%), vascular co-option (10/57, 18%) and diffuse infiltration (18/57, 32%). There was no association of invasion pattern with primary tumor type, although vascular co-option was most common in melanomas (4/10, 40%). αv subunit expression was lowest in the vascular co-option group (p = 0.05, t-test). αvβ6 levels were higher in the well-demarcated group than in the vascular co-option group (p = 0.025; t-test) and were higher in lung cancer BM than in melanoma BM (0.01, t-test). αvβ3 and αvβ5 were frequently expressed in tumoral (αvβ3: 30/57, 53%; αvβ5: 55/57, 97%) and peritumoral (αvβ3: 29/57, 51%, αvβ5: 54/57 (95%) vascular structures and 27/57 (47%) specimens showed avb5 and 6/57 (11%) αvβ3 expression on tumor cells. Prior radio- or chemotherapy did not correlate with invasion pattern or integrin expression. Conclusions: We delineate three distinct invasion patterns of BM into the brain parenchyma: well-demarcated growth, vascular co-option and diffuse infiltration. Integrin expression is frequent on tumor and vascular cells in BM and associated with distinct invasion patterns. Anti-integrin therapy could be a valid treatment option in patients with BM.

Patterns of treatment (tx) with bone-modifying agents (BMA) in patients with bone metastases (mets).

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e20690-e20690
Author(s):  
Jane M Quigley ◽  
Rohini Khorana Hernandez ◽  
Karynsa Cetin ◽  
Melissa A. Pirolli ◽  
David Quach ◽  
...  
Keyword(s):  
Medical Records ◽  
Descriptive Analysis ◽  
Cord Compression ◽  
Tumor Type ◽  
The Us ◽  
Skeletal Related Events ◽  
Tumor Types ◽  
To Receive ◽  
Intravenous Bisphosphonates

e20690 Background: Bone mets can lead to serious and debilitating skeletal-related events (SREs: fracture, spinal cord compression, and surgery or radiation to bone). Three BMAs are approved in the US for prevention of SREs in cancer patients (pts) with bone mets: 2 intravenous bisphosphonates (IV BP) with recommended dosing every 3-4 weeks (pamidronate [PAM] and zoledronic acid [ZA]), and 1 RANK ligand inhibitor with subcutaneous injection every 4 weeks (denosumab). Monitoring real-world tx trends is important, particularly as low persistence has been linked to higher rates of SREs (Hatoum et al 2008). Methods: A retrospective cohort was defined from the Oncology Services Comprehensive Electronic Records (OSCER) database, which includes medical records from >500K pts treated at 76 US oncology practices. Adult solid tumor pts with bone mets who initiated tx with a BMA between Jan 2011 and Oct 2011 were included and followed for 12 mos after tx initiation. Pts were either naïve (no BMA in previous 6 mos) or transition (different BMA received in previous 6 mos). Results: The cohort was composed of 1445 denosumab pts (62% naïve) and 1807 IV BP pts (99% naïve). Pt characteristics were similar, although denosumab pts were somewhat more likely to have prostate cancer than IV BP pts (30% vs 25%). Denosumab pts were more likely to receive regular tx during follow-up and less likely to switch tx than IV BP pts (Table). Trends were consistent across tumor types and for naïve vs transition pts. Conclusions: This descriptive analysis reports on tx patterns for pts with bone mets since the availability of denosumab in Dec 2010. Denosumab represented almost half (44%) of pts initiating a BMA and one-third of pts naïve to tx. Uninterrupted tx was more common for denosumab pts than IV BP pts, regardless of tumor type. Trends, including reasons for and consequences of tx interruption, should be monitored as the pt experience develops. [Table: see text]

Prioritizing targeted therapies in an evidence-based manner, integrating biological context and functional precision medicine.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14065-e14065
Author(s):  
Simina Boca ◽  
Krithika Bhuvaneshwar ◽  
Virneliz Fernandez-Vega ◽  
Jayaram Kancherla ◽  
Shruti Rao ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Targeted Therapies ◽  
Evidence Based ◽  
Tumor Type ◽  
Molecular Alterations ◽  
Her2 Breast Cancer ◽  
Evidence Level ◽  
Molecular Profiles ◽  
Tumor Types ◽  
Biological Context

e14065 Background: It is becoming increasingly common for cancer patients to undergo molecular profiling of their tumors in order to see whether there are any actionable DNA, gene expression, or protein expression signatures. For example, individuals with ER+ or HER2+ breast cancer or KRAS wild type (non-mutated) colorectal cancer are prescribed specific targeted therapies. When an individual’s molecular alterations do not match any currently-approved recommendations for their tumor type, their clinician may consider prescribing a therapy approved in a different tumor type. Unfortunately, tumors often eventually become resistant to the therapies they are exposed to, leading to a narrowing of options after each therapy line. Methods: We previously developed CDGnet, an evidence-based approach and web-based tool for prioritizing targeted therapies based on tumor molecular profiles based on known pathways which provide biological context. CDGnet considers approved therapies with biomarkers among the alterations for the individual’s tumor type and other tumor types as the first and second evidence level categories respectively. These are followed by therapies that target or have as biomarkers genes or proteins downstream of altered oncogenes, considering curated pathways for the individual’s tumor type and other tumor types as the third and fourth evidence level categories respectively. We are currently expanding CDGnet in order to include data from high-throughput screening (HTS) experiments of NCI oncologic drugs performed on patient-derived organoids. The concept of “functional precision medicine” consists of using functional drug efficacy determination directly on individual patients, in this case by considering drugs with low half maximal effective concentrations (EC50) which are tested on tissues derived from the actual patients. Results: We will present extensions to CDGnet that allow users to upload both the molecular profiles and the HTS data to see whether any drugs are predicted by both approaches or whether specific combinations appear promising for further testing. Preliminary results on a set of glioblastoma samples will be presented. Conclusions: We hope that extending CDGnet to also include HTS data will eventually allow a truly multi-factorial personalized oncology approach, whereby both molecular alterations at the DNA, RNA, and protein levels and patient-derived organoids will be considered in deciding on treatment plans for individuals.

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