Quantifying the Expanding Landscape of Clinical Actionability for Patients with Cancer

There is a continuing debate about the proportion of cancer patients that benefit from precision oncology, attributable in part to conflicting views as to which molecular alterations are clinically actionable. To quantify the expansion of clinical actionability since 2017, we annotated 47,271 solid tumors sequenced with the MSK-IMPACT clinical assay using two temporally distinct versions of the OncoKB knowledge base deployed 5 years apart. Between 2017 and 2022, we observed an increase from 8.9% to 31.6% in the fraction of tumors harboring a standard care (level 1 or 2) predictive biomarker of therapy response and an almost halving of tumors carrying nonactionable drivers (44.2% to 22.8%). In tumors with limited or no clinical actionability, TP53 (43.2%), KRAS (19.2%), and CDKN2A (12.2%) were the most frequently altered genes.

SIGNIFICANCE

Although clear progress has been made in expanding the availability of precision oncology-based treatment paradigms, our results suggest a continued unmet need for innovative therapeutic strategies, particularly for cancers with currently undruggable oncogenic drivers. See related commentary by Horak and Fröhling, p. 18. This article is featured in Selected Articles from This Issue, p. 5.

Interpreting and integrating genomic tests results in clinical cancer care: Overview and practical guidance

The last decade has seen rapid progress in the use of genomic tests, including gene panels, whole-exome sequencing, and whole-genome sequencing, in research and clinical cancer care. These advances have created expansive opportunities to characterize the molecular attributes of cancer, revealing a subset of cancer-associated aberrations called driver mutations. The identification of these driver mutations can unearth vulnerabilities of cancer cells to targeted therapeutics, which has led to the development and approval of novel diagnostics and personalized interventions in various malignancies. The applications of this modern approach, often referred to as precision oncology or precision cancer medicine, are already becoming a staple in cancer care and will expand exponentially over the coming years. Although genomic tests can lead to better outcomes by informing cancer risk, prognosis, and therapeutic selection, they remain underutilized in routine cancer care. A contributing factor is a lack of understanding of their clinical utility and the difficulty of results interpretation by the broad oncology community. Practical guidelines on how to interpret and integrate genomic information in the clinical setting, addressed to clinicians without expertise in cancer genomics, are currently limited. Building upon the genomic foundations of cancer and the concept of precision oncology, the authors have developed practical guidance to aid the interpretation of genomic test results that help inform clinical decision making for patients with cancer. They also discuss the challenges that prevent the wider implementation of precision oncology.

Precision Oncology: 2023 in Review

SUMMARY

This article presents a review of recent major advances in precision oncology and the future implications of these advances, specifying the iterative progress achieved from the end of 2022 through 2023. We discuss the different classes of precision oncology drugs and associated biomarkers as well as the improvements in clinical trial design that have enabled the efficient testing of these drugs.

Tumor sequencing of African ancestry reveals differences in clinically relevant alterations across common cancers

Cancer genomes from patients with African (AFR) ancestry have been poorly studied in clinical research. We leverage two large genomic cohorts to investigate the relationship between genomic alterations and AFR ancestry in six common cancers. Cross-cancer type associations, such as an enrichment of MYC amplification with AFR ancestry in lung, breast, and prostate cancers, and depletion of BRAF alterations are observed in colorectal and pancreatic cancers. There are differences in actionable alterations, such as depletion of KRAS G12C and EGFR L858R, and enrichment of ROS1 fusion with AFR ancestry in lung cancers. Interestingly, in lung cancer, KRAS mutations are less common in both smokers and non-smokers with AFR ancestry, whereas the association of TP53 mutations with AFR ancestry is only seen in smokers, suggesting an ancestry-environment interaction that modifies driver rates. Our study highlights the need to increase representation of patients with AFR ancestry in drug development and biomarker discovery.

Molecular Characterization of Endometrial Carcinomas in Black and White Patients Reveals Disparate Drivers with Therapeutic Implications

Although the incidence of endometrial carcinoma (EC) is similar in Black and White women, racial disparities are stark, with the highest mortality rates observed among Black patients. Here, analysis of 1,882 prospectively sequenced ECs using a clinical FDA-authorized tumor-normal panel revealed a significantly higher prevalence of high-risk histologic and molecular EC subtypes in self-identified Black (n = 259) compared with White (n = 1,623) patients. Clinically actionable alterations, including high tumor mutational burden/microsatellite instability, which confer benefit from immunotherapy, were less frequent in ECs from Black than from White patients. Ultramutated POLE molecular subtype ECs associated with favorable outcomes were rare in Black patients. Results were confirmed by genetic ancestry analysis. CCNE1 gene amplification, which is associated with aggressive clinical behavior, was more prevalent in carcinosarcomas occurring in Black than in White patients. ECs from Black and White patients display important differences in their histologic types, molecular subtypes, driver genetic alterations, and therapeutic targets.

SIGNIFICANCE

Our comprehensive analysis of prospectively clinically sequenced ECs revealed significant differences in their histologic and molecular composition and in the presence of therapeutic targets in Black versus White patients. These findings emphasize the importance of incorporating diverse populations into molecular studies and clinical trials to address EC disparities. This article is featured in Selected Articles from This Issue, p. 2293.

Enhanced clinical assessment of hematologic malignancies through routine paired tumor and normal sequencing

Genomic profiling of hematologic malignancies has augmented our understanding of variants that contribute to disease pathogenesis and supported development of prognostic models that inform disease management in the clinic. Tumor only sequencing assays are limited in their ability to identify definitive somatic variants, which can lead to ambiguity in clinical reporting and patient management. Here, we describe the MSK-IMPACT Heme cohort, a comprehensive data set of somatic alterations from paired tumor and normal DNA using a hybridization capture-based next generation sequencing platform. We highlight patterns of mutations, copy number alterations, and mutation signatures in a broad set of myeloid and lymphoid neoplasms. We also demonstrate the power of appropriate matching to make definitive somatic calls, including in patients who have undergone allogeneic stem cell transplant. We expect that this resource will further spur research into the pathobiology and clinical utility of clinical sequencing for patients with hematologic neoplasms.

Abstract 6585: OncoKB, MSK’s precision oncology knowledge base

OncoKB, Memorial Sloan Kettering Cancer Center’s (MSK) precision oncology knowledge base (www.oncokb.org), is an FDA-recognized* somatic variant database that contains information about the oncogenic effect and clinical implications of genomic alterations in cancer. Since its 2016 public release, OncoKB has grown to include annotation for >5,770 alterations in ~700 cancer-associated genes. OncoKB data is integrated into the cBioPortal for Cancer Genomics and used to annotate >12,000 MSK patient sequencing reports annually, encompassing both solid tumor and hematological malignancies. Users in academic, commercial and hospital settings outside MSK can programmatically access OncoKB data via its web API with an OncoKB license, which is free for academic research. To date, users from ~ 1400 institutions across >70 countries have licensed access to OncoKB annotations. The OncoKB Therapeutic (Tx) Levels of Evidence assign tumor-type specific clinical actionability to individual mutational events based on data supporting whether an alteration is predictive of response to matched targeted therapies. To date, OncoKB includes 44 Level 1 genes (included in the FDA drug label), 23 Level 2 genes (included in professional guidelines), 33 Level 3A genes (predictive of drug response in well-powered clinical studies), 27 Level 4 genes (predictive of drug response based on compelling biological evidence), and 11 R1/R2 resistance genes. In 2022, several major content additions were made to OncoKB based on key shifts in the precision oncology landscape. For example, OncoKB included 2 new tumor-agnostic FDA drug approvals, dabrafenib + trametinib and selpercatinib for BRAF V600E and RET fusion-positive solid tumors respectively (Level 1), capturing 5 tumor-agnostic FDA drug approvals to date. OncoKB promoted ERBB2 oncogenic mutations and FGFR1 fusions to Level 1 following their inclusion as patient eligibility criteria in FDA drug labels for trastuzumab deruxtecan (NSCLC) and pemigatinib (myeloid/lymphoid neoplasms) respectively. NCCN guidelines for uterine sarcoma and pancreatic cancer listed PARP-inhibition for BRCA-mutant disease, making them Level 2 in these indications. Lastly, previously considered undruggable targets, TP53 Y220C and KRAS G12D, were included in OncoKB based on compelling evidence demonstrating response to allele-targeting drugs, PC14586 and RMC-6263, respectively. In sum, 7 novel clinically actionable biomarkers (Levels 1-4) and 11 follow-on precision oncology therapies for existing leveled biomarkers were added to OncoKB in 2022. Current OncoKB efforts are focused on prioritized high-volume cancer gene curation for annotation of whole exome/genome data, annotation of germline alterations and development of a clinical trials matching system. *FDA recognition of OncoKB is partial and limited to the information clearly marked on www.oncokb.org.

Citation Format: Sarah P. Suehnholz, Moriah Nissan, Hongxin Zhang, Ritika Kundra, Calvin Lu, Amanda Dhaneshwar, Nicole Fernandez, Stephanie Carrero, Maria E. Arcila, Marc Ladanyi, Michael F. Berger, Aijazuddin Syed, Rose Brannon, Ross Levine, Ahmet Dogan, Ezra Rosen, Alexander Drilon, David B. Solit, Nikolaus Schultz, Debyani Chakravarty. OncoKB, MSK’s precision oncology knowledge base. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6585.

Comprehensive Molecular Characterization of Gallbladder Carcinoma and Potential Targets for Intervention

PURPOSE

Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications.

EXPERIMENTAL DESIGN

GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes). Variants with therapeutic implications were identified using OncoKB database. The associations between recurrent genetic alterations and clinicopathologic characteristics (Fisher exact tests) or overall survival (univariate Cox regression) were evaluated. P values were adjusted for multiple testing.

RESULTS

Overall, 244 samples (57% primary tumors and 43% metastases) from 233 patients were studied (85% adenocarcinomas, 10% carcinomas with squamous differentiation, and 5% neuroendocrine carcinomas). The most common oncogenic molecular alterations appeared in the cell cycle (TP53 63% and CDKN2A 21%) and RTK_RAS pathways (ERBB2 15% and KRAS 11%). No recurrent structural variants were identified. There were no differences in the molecular landscape of primary and metastasis samples. Variants in SMAD4 and STK11 independently associated with reduced survival in patients with metastatic disease. Alterations considered clinically actionable in GBC or other solid tumor types (e.g., NTRK1 fusions or oncogenic variants in ERBB2, PIK3CA, or BRCA1/2) were identified in 35% of patients; 18% of patients with metastatic disease were treated off-label or enrolled in a clinical trial based on molecular findings.

CONCLUSIONS

GBC is a genetically diverse malignancy. This large-scale genomic analysis revealed alterations with potential prognostic and therapeutic implications and provides guidance for the development of targeted therapies.

Precision Oncology: 2022 in Review

This article presents a review of the major advances and future implications in precision oncology accomplished in 2022 and centers on three primary pillars: advances in (i) rational drug design, (ii) study design, and (iii) novel biomarkers.

Genomic analysis of early-stage lung cancer reveals a role for TP53 mutations in distant metastasis

Patients with non-small cell lung cancer (NSCLC) who have distant metastases have a poor prognosis. To determine which genomic factors of the primary tumor are associated with metastasis, we analyzed data from 759 patients originally diagnosed with stage I-III NSCLC as part of the AACR Project GENIE Biopharma Collaborative consortium. We found that TP53 mutations were significantly associated with the development of new distant metastases. TP53 mutations were also more prevalent in patients with a history of smoking, suggesting that these patients may be at increased risk for distant metastasis. Our results suggest that additional investigation of the optimal management of patients with early-stage NSCLC harboring TP53 mutations at diagnosis is warranted in light of their higher likelihood of developing new distant metastases.

Genetic Ancestry Correlates with Somatic Differences in a Real-World Clinical Cancer Sequencing Cohort

Accurate ancestry inference is critical for identifying genetic contributors of cancer disparities among populations. Although methods to infer genetic ancestry have historically relied upon genome-wide markers, the adaptation to targeted clinical sequencing panels presents an opportunity to incorporate ancestry inference into routine diagnostic workflows. We show that global ancestral contributions and admixture of continental populations can be quantitatively inferred using markers captured by the MSK-IMPACT clinical panel. In a pan-cancer cohort of 45,157 patients, we observed differences by ancestry in the frequency of somatic alterations, recapitulating known associations and revealing novel associations. Despite the comparable overall prevalence of driver alterations by ancestry group, the proportion of patients with clinically actionable alterations was lower for African (30%) compared with European (33%) ancestry. Although this result is largely explained by population-specific cancer subtype differences, it reveals an inequity in the degree to which different populations are served by existing precision oncology interventions.

SIGNIFICANCE

We performed a comprehensive analysis of ancestral associations with somatic mutations in a real-world pan-cancer cohort, including >5,000 non-European individuals. Using an FDA-authorized tumor sequencing panel and an FDA-recognized oncology knowledge base, we detected differences in the prevalence of clinically actionable alterations, potentially contributing to health care disparities affecting underrepresented populations. This article is highlighted in the In This Issue feature, p. 2483.

Overall survival with circulating tumor DNA-guided therapy in advanced non-small-cell lung cancer

Circulating tumor DNA (ctDNA) sequencing guides therapy decisions but has been studied mostly in small cohorts without sufficient follow-up to determine its influence on overall survival. We prospectively followed an international cohort of 1,127 patients with non-small-cell lung cancer and ctDNA-guided therapy. ctDNA detection was associated with shorter survival (hazard ratio (HR), 2.05; 95% confidence interval (CI), 1.74-2.42; P < 0.001) independently of clinicopathologic features and metabolic tumor volume. Among the 722 (64%) patients with detectable ctDNA, 255 (23%) matched to targeted therapy by ctDNA sequencing had longer survival than those not treated with targeted therapy (HR, 0.63; 95% CI, 0.52-0.76; P < 0.001). Genomic alterations in ctDNA not detected by time-matched tissue sequencing were found in 25% of the patients. These ctDNA-only alterations disproportionately featured subclonal drivers of resistance, including RICTOR and PIK3CA alterations, and were associated with short survival. Minimally invasive ctDNA profiling can identify heterogeneous drivers not captured in tissue sequencing and expand community access to life-prolonging therapy.

Abstract 1189: OncoKB, MSK’s precision oncology knowledge base

OncoKB, Memorial Sloan Kettering Cancer Center’s (MSK) precision oncology knowledge base (www.oncokb.org), is a comprehensive database that annotates the oncogenic effects and clinical actionability of somatic alterations in cancer. OncoKB supports variant interpretation by the cBioPortal for Cancer Genomics and is used to annotate &gt;12,000 MSK patient sequencing reports annually. Since its introduction in 2016, OncoKB has expanded to include 5685 alterations in 682 genes, and in October 2021, it became the first somatic knowledge base to be partially recognized by the FDA. The scope of the OncoKB FDA recognition includes clinically actionable variants that map to an FDA level of evidence, the processes of variant curation, and policies regarding database oversight, personnel training and transparency of data sources and operations. This recognition credentials OncoKB as providing accurate, reliable and clinically meaningful information to the medical and scientific communities.

The OncoKB Therapeutic (Tx) Levels of Evidence categorize variants based on their tumor type-specific predictive value of sensitivity or resistance to matched standard care or investigational targeted therapies. To date, OncoKB includes 43 Level 1 genes (included in the FDA drug label), 23 Level 2 genes (included in professional guidelines), 25 Level 3A genes (predictive of drug response in well-powered clinical studies), 23 Level 4 genes (predictive of drug response based on compelling biological evidence), and 11 R1 or R2 resistance genes. Initially focused on solid tumors, OncoKB was expanded to include hematologic disease annotation in 2019 and introduced Diagnostic (Dx) and Prognostic (Px) levels of evidence. All three level of evidence systems (Tx, Dx and Px) are consistent with the guidelines for evidence-based categorization of somatic variants published as a joint consensus recommendation by AMP/ASCO/CAP.

OncoKB is governed by a Clinical Genomics Annotation Committee, composed of MSK physicians and scientists who ensure that the information captured is accurate and current, and an external advisory board composed of leaders in the clinical oncology and genomics communities who oversee OncoKB updates and progress. OncoKB curation rules and processes are transparent and documented in the OncoKB Curation Standard Operating Procedure, which is publicly available via the website. User feedback to OncoKB content is encouraged via the website and through cBioPortal. Queries or suggestions by OncoKB users are addressed by the OncoKB team within 72 hours.

OncoKB offers licenses for academic, commercial and hospital use, with which users can programmatically access the web API. Future work includes coverage of additional cancer-associated genes, annotation of germline alterations that are predictive of drug response and/or associated with increased heritable cancer risk and the development of a clinical trial matching system.

Citation Format: Sarah P. Suehnholz, Moriah Nissan, Hongxin Zhang, Ritika Kundra, Calvin Lu, Benjamin Xu, Maria E. Arcila, Marc Ladanyi, Michael F. Berger, Ahmet Zehir, Aijaz Syed, Julia E. Rudolph, Ross L. Levine, Ahmet Dogan, Jianjiong Gao, David B. Solit, Nikolaus Schultz, Debyani Chakravarty. OncoKB, MSK’s precision oncology knowledge base [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1189.

Abstract 3628: Comprehensive identification of lineage associated cancer genes in 122 histologies

Although the majority of cancer genes show a high degree of specificity for certain lineages, genomic profiling of cancer patients routinely identify alterations in genes that are atypical to the presented cancer type but are canonical drivers in a different lineage. It is often unclear if these atypical drivers arose early in tumorigenesis or were acquired during progression. A complete understanding of lineage associated genes (LAGs) will enable better interpretation of the molecular etiology of each diagnosed tumor.

Here, we used a cohort of 38,912 patients across 122 cancer histologies (each with 50 or more patients) profiled for somatic alterations (mutations, copy number alterations and gene fusions) using the MSK-IMPACT assay. Tumors with TMB &gt; 15 were already excluded. All alterations were classified as drivers using OncoKB. Allele-specific copy number calls were assessed using FACETS.

Overall, 95% of patients harbored at least one oncogenic alteration, with a median of 4 drivers per tumor. We observed widespread prevalence of drivers across lineages with each gene mutated in a median of 36 different lineages. Conversely, a median of 103 genes were mutated at least once in each lineage. Hypothesizing that cancer genes are influenced by cell of origin, we sought to identify lineages harboring significantly higher rates of drivers in a given gene compared to its pancancer driver rate. We identified 1781 significant (adjusted P &lt; 0.05) gene and lineage associations, and an additional 109 involving genes mutated at &gt;10% in the respective lineages but which did not reach significance were also included. Lineage-agnostic genes such as TP53 and CDKN2A were associated with a broad spectrum of lineages (90 and 55, respectively). However, overall, each gene we profiled was found to be associated with a median of 3 distinct lineages. For example, while BRAF drivers are found in nearly all histologies (n=91), it is enriched for drivers in only 8 lineages: melanoma (acral and cutaneous), thyroid (poorly differentiated, anaplastic and papillary) and bowel (mucinous adenocarc. of colon/rectum, colon adenocarc. and neuroendocrine carc. of colon/rectum). In all, nearly a third of all drivers were observed in non-associated lineages.

We next compared the somatic properties of drivers among genes in associated lineages vs. the same genes in non-associated lineages. We observed that mutations in LAGs were more often clonal (83% vs. 73%, associated vs. non-associated, P = 0) and showed enrichment for mutant allele imbalance in oncogenes (40% vs. 23%, P = 2e-111) and biallelic inactivation in tumor suppressor LAGs (71% vs. 58%, P = 4e-130). Furthermore, 93% of all OncoKB Level 1/2/3A actionable alterations, which are classified based on their histology, were in LAGs. In conclusion, our findings enable classification of drivers that are relevant for lineage-specific malignant transformation and advance our understanding of tumor biology.

Citation Format: Chaitanya Bandlamudi, Walid K. Chatila, Shaleigh A. Smith, Subhiksha Nandakumar, Craig Bielski, Bastien Nguyen, Henry S. Walch, Christoph K. Kreitzer, Kanika S. Arora, Tran Thinh Ngoc, Miika Mehine, Irina Ostrovnaya, Ino de Bruijn, Hyung Jun Woo, Ritika Kundra, Christopher J. Fong, Satshil Rana, Gaofei Zhao, Mingxuan Zhang, Mark R. Zucker, Hongxin Zhang, Ryan Ptashkin, Rose Brannon, Eduard Reznik, JianJiong Gao, Maria E. Arcila, Ryma Benayed, Debyani Chakravarty, David Solit, Mark T. Donoghue, Marc Ladanyi, Nikolaus D. Schultz, Michael F. Berger, Ahmet Zehir. Comprehensive identification of lineage associated cancer genes in 122 histologies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3628.

Abstract 3634: Integrative analysis of the contribution of genomic and clinical factors to worse clinical outcomes in non-Hispanic Black patients with colorectal cancer

Non-Hispanic Black (NHB) patients have higher incidence and higher mortality from colorectal cancer (CRC) than non-Hispanic white (NHW) patients. The extent to which this aggressive behavior in NHB patients is driven by differences in cancer genomics is presently unknown.

We analyzed clinical and genomic data from 3,963 CRC patients treated at Memorial Sloan Kettering, including 336 (8%) NHB and 3,627 (92%) NHW patients. Tumors were sequenced using the clinical MSK-IMPACT test, a targeted next-generation DNA sequencing assay that identifies mutations, copy number changes and structural rearrangements in 341-505 genes using solid tissue and matched blood.

No significant differences by race were observed for stage at diagnosis or sex. While the difference in median age at diagnosis was small (53.4 for NHB vs. 55 years for NHW patients, p=0.012), significantly fewer NHB patients were diagnosed after 65 years of age (17% vs. 27%, p=0.001). Right-sided colon tumors were more common among NHB patients (37% vs. 25%, p=0.02); the proportion of rectal tumors was similar in both racial groups (31% in NHB vs. 34% in NHW patients, n.s.). Hypermutated tumors, including tumors with microsatellite instability (MSI) and POLE hypermutants, were more frequent among NHW patients (12% vs. 8%, p=0.02). Right-sided tumors were more frequently MSI/hypermutated in the NHW patients (27% vs. 13%, p=0.008), whereas no differences by race were observed for left-sided colon (5% vs. 1%, n.s.) or rectal primaries (4% vs. 5%, n.s.).

Genomic analysis of the non-hypermutated tumors revealed no significant differences in tumor mutational burden or fraction of genome altered between racial groups. Tumors in NHB patients were enriched in KRAS mutations (60% vs. 45%, p&lt;0.001), but G12C mutations accounted only for 3% of all driver KRAS mutations in NHB patients vs. 8% of all driver mutations in NHW patients (p=0.01). BRAF mutations were more frequent in non-hypermutated NHW patients (7% vs. 3%, p=0.006), but the overall frequency of RTK/RAS pathway alterations was higher in the NHB group (74% vs. 66%, p=0.004).

Even though all patients were treated at the same single institution during the study, NHB patients had shorter overall survival (OS) from the time of sequencing (median 28 months [95% CI 25-38] vs. 50 months [95% CI 47-53], p&lt;0.001). NHB patients also had worse OS [HR 1.64, CI 1.3 - 2.1, p&lt;0.001] in a multivariate analysis using Cox Proportional-Hazards and accounting for age at diagnosis, stage at diagnosis, body mass index, primary tumor location, MSI status and oncogenic alterations in APC, TP53, KRAS, SMAD4, and BRAF.

Our data confirms that NHB patients with CRC have worse clinical outcomes than NHW patients. Clinically relevant differences in the frequency of alterations in cancer driver genes are observed based on racial origin, but they do not fully explain the difference in survival.

Citation Format: Henry Walch, Anisha Luthra, Walid K. Chatila, Fan Wu, Debyani Chakravarty, Chin-Tung Chen, Rupa Sood, Dana M. Omer, Jesse J. Smith, Nikolaus Schultz, Karuna Ganesh, Julio Garcia-Aguilar, Rona Yaeger, Francisco Sanchez-Vega. Integrative analysis of the contribution of genomic and clinical factors to worse clinical outcomes in non-Hispanic Black patients with colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3634.

Abstract 2182: Ancestry inference and population-specific disparities in a real-world clinical sequencing cohort

Accurate ancestry inference is crucial for identifying genetic determinants of cancer disparities among specific populations. While methods to infer genetic ancestry and admixture have historically relied upon genome-wide markers from broad-scale next-generation sequencing (NGS), the adaptation to targeted NGS panels presents an opportunity to prospectively incorporate ancestry inference as part of routine clinical diagnosis. Here we show that global ancestral contributions and admixture of African (AFR), European (EUR), East Asian (EAS), Native American (NAM) and South Asian (SAS) populations can be reliably inferred using markers from genomic regions covered by the FDA-authorized clinical NGS panel, MSK-IMPACT. We also show that individuals with Ashkenazi Jewish (ASJ) ancestry can be inferred with 97% accuracy using a set of ASJ ancestry-informative markers. We apply these methods to infer genetic ancestry for over 45,000 patients from the AACR GENIE v10.0-public cohort who were profiled using MSK-IMPACT. We observed 98% concordance between self-reported race and genetic ancestry for non-admixed individuals and were able to quantitatively infer ancestral contributions for individuals from recently admixed populations such as African American and Latin American. Of the discordant cases, manual review of clinical and family histories revealed the vast majority to represent clinical encoding errors where the inferred ancestry was confirmed correct. As self-reported race is not available for 17% of patients in the GENIE cohort, the ability to accurately infer genetic ancestry enables broader analysis of population-specific genomic and clinical features. We systematically evaluated the frequency of somatic and germline alterations in up to 468 genes for each cancer type and recapitulated known differences among ancestral populations. For example, we observed significantly higher frequency of EGFR somatic alterations in EAS (65%) and SAS (66%) compared to non-ASJ EUR (21%) with lung adenocarcinoma, a difference that remained significant even when limiting to never-smokers. Additionally, we found that the frequency of harboring at least one known BRCA founder mutation (BRCA1 68_69delAG, BRCA1 5266dupC, or BRCA2 5946delT) was 26x higher in genetically determined ASJ (5.1%) compared to non-ASJ (0.2%). Strikingly, while the overall rate of driver alterations in solid tumors was similar across different populations, we found that the proportion of patients with clinically actionable somatic alterations (OncoKB Level 1, 2, 3A, or 3B) was lowest in AFR (47%) patients compared to EUR, EAS and SAS (50% each). While this result is partially explained by different cancer type and subtype distributions in different populations in this real-world cohort, it highlights the urgency for greater equity in drug development programs to target alterations represented across all diverse populations.

Citation Format: Kanika Arora, Thinh N. Tran, Yelena M. Kemel, Miika Mehine, Ying Liu, Shaleigh A. Smith, Subhiksha Nandakumar, Irina Ostrovnaya, Thomas C. Reynolds, Kenneth Offit, David Solit, Marc Ladanyi, Nikolaus Schultz, Ahmet Zehir, Carol L. Brown, Debyani Chakravarty, Zsofia K. Stadler, Chaitanya Bandlamudi, Michael F. Berger. Ancestry inference and population-specific disparities in a real-world clinical sequencing cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2182.

Clinicopathologic characterization of ERK2 E322K mutation in solid tumors: Implications for treatment and drug development

3135

Background: MAPK1 encodes ERK2, a kinase component of the mitogen activated signaling (MAPK) pathway. ERK2 E322K is a known activating mutation that leads to increased phosphorylation and ERK signaling. In vitro studies found this mutation to be associated with resistance to dabrafenib, trametinib, but potential sensitivity to ERK inhibitors. Despite its potential as a drug target, little is known about the clinicopathologic characteristics of this hotspot mutation across solid tumors. Methods: Patients with solid tumors underwent tumor next-generation sequencing at Memorial Sloan Kettering Cancer Center between Jan 2015 and Sep 2020 using the MSK-IMPACT assay. Using the cBioPortal database and clinical charts, we analyzed tumors harboring MAPK1/ERK2 E322K mutations, assessed their clinicopathologic characteristics, co-mutational status and overall survival (OS). OS was measured from time of tumor sequencing to date of death or last follow-up. Results: A total of 37 tumor samples from 35 patients were identified in 59,822 tumors sequenced (0.06%) to harbor an ERK2 E322K mutation. The distribution across tumor types was as follows: head and neck squamous cell carcinoma (29%), bladder cancer (20%), lymphomas (9%), colorectal cancers (9%), gastric cancers (9%), cholangiocarcinoma (6%), cervical cancers (6%), lung cancers (6%), germ cell tumor (3%), Merkel cell carcinoma (3%), and breast cancers (3%). The OS in patients with metastatic disease and ERK2 E322K was 22.29 months (95%CI: 7.56-NA) months. Other mutations in RAS pathway frequently co-occurred with ERK2 E322K mutation (17/37, 46%). Concurrent mutations are also involved in pathways of cell cycle (71%), PI3K (71%), TP53 (66%), NOTCH (57%), RTK (51%), HIPPO (29%), TGF-beta (29%), WNT (26%), NRF2 (20%), MYC (14%). The median TMB score of samples from solid malignancies was 12.3 (range:0-101, quartiles: 6.9-33.0) mutation/Mb. Two patients (2/35, 6%) had microsatellite-instability high (MSI-H) tumors. The most frequent concurrent activating mutations include ARID1A (29%), FBXW7 (26%), PI3KCA (22%), PI3KR1/2/3 (20%), CDKN2A (11%), PTEN (8%), BRCA1/2(8%), FGFR3 (8%), BRAF (6%), Only one of these 35 patients received treatment targeting BRAF/MEK/ERK pathway and achieved partial response. One patient with NSCLC harboring a concurrent EGFR L858R mutation did not respond to erlotinib. One patient with PI3KCA mutated head and neck cancer did not respond to PI3K inhibitor. Two patients had TMB score of 100.9 and 12.9 mutation/Mb had partial response to pembrolizumab. Conclusions: ERK2 E322K mutation is a rare oncogenic mutation across diverse solid tumor types, associated with a high co-occurrence of other activating mutations and a high TMB. The lack of response to other targeted therapies suggests ERK2 E322K is a potential driver mutation. These findings may inform treatment and further development of ERK inhibitors.

Computational methods and translational applications for targeted next-generation sequencing platforms

During the past decade, next-generation sequencing (NGS) technologies have become widely adopted in cancer research and clinical care. Common applications within the clinical setting include patient stratification into relevant molecular subtypes, identification of biomarkers of response and resistance to targeted and systemic therapies, assessment of heritable cancer risk based on known pathogenic variants, and longitudinal monitoring of treatment response. The need for efficient downstream processing and reliable interpretation of sequencing data has led to the development of novel algorithms and computational pipelines, as well as structured knowledge bases that link genomic alterations to currently available drugs and ongoing clinical trials. Cancer centers around the world use different types of targeted solid-tissue and blood based NGS assays to analyze the genomic and transcriptomic profile of patients as part of their routine clinical care. Recently, cross-institutional collaborations have led to the creation of large pooled datasets that can offer valuable insights into the genomics of rare cancers.

Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants

Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity 'sensors' that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 editor-sgRNA combinations, we provide a comprehensive resource of sgRNAs for introducing and interrogating cancer-associated single nucleotide variants in multiple model systems. We demonstrate that sensor-validated tools streamline production of in vivo cancer models and that integrating sensor modules in pooled sgRNA libraries can aid interpretation of high-throughput base editing screens. Using this approach, we identify several previously uncharacterized mutant TP53 alleles as drivers of cancer cell proliferation and in vivo tumor development. We anticipate that the framework described here will facilitate the functional interrogation of cancer variants in cell and animal models.

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC)

PURPOSE

Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care. Therefore, it is essential to address this unmet need.

METHODS

Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group and ClinGen Germline/Somatic Variant Subcommittee, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium used a consensus approach to develop a standard operating procedure (SOP) for the classification of oncogenicity of somatic variants.

RESULTS

This comprehensive SOP has been developed to improve consistency in somatic variant classification and has been validated on 94 somatic variants in 10 common cancer-related genes.

CONCLUSION

The comprehensive SOP is now available for classification of oncogenicity of somatic variants.

AKT mutant allele-specific activation dictates pharmacologic sensitivities

AKT- a key molecular regulator of PI-3K signaling pathway, is somatically mutated in diverse solid cancer types, and aberrant AKT activation promotes altered cancer cell growth, survival, and metabolism1-8. The most common of AKT mutations (AKT1 E17K) sensitizes affected solid tumors to AKT inhibitor therapy7,8. However, the pathway dependence and inhibitor sensitivity of the long tail of potentially activating mutations in AKT is poorly understood, limiting our ability to act clinically in prospectively characterized cancer patients. Here we show, through population-scale driver mutation discovery combined with functional, biological, and therapeutic studies that some but not all missense mutations activate downstream AKT effector pathways in a growth factor-independent manner and sensitize tumor cells to diverse AKT inhibitors. A distinct class of small in-frame duplications paralogous across AKT isoforms induce structural changes different than those of activating missense mutations, leading to a greater degree of membrane affinity, AKT activation, and cell proliferation as well as pathway dependence and hyper-sensitivity to ATP-competitive, but not allosteric AKT inhibitors. Assessing these mutations clinically, we conducted a phase II clinical trial testing the AKT inhibitor capivasertib (AZD5363) in patients with solid tumors harboring AKT alterations (NCT03310541). Twelve patients were enrolled, out of which six harbored AKT1-3 non-E17K mutations. The median progression free survival (PFS) of capivasertib therapy was 84 days (95% CI 50-not reached) with an objective response rate of 25% (n = 3 of 12) and clinical benefit rate of 42% (n = 5 of 12). Collectively, our data indicate that the degree and mechanism of activation of oncogenic AKT mutants vary, thereby dictating allele-specific pharmacological sensitivities to AKT inhibition.

Somatic Genomic Testing in Patients With Metastatic or Advanced Cancer: ASCO Provisional Clinical Opinion

PURPOSE

An ASCO provisional clinical opinion offers timely clinical direction to ASCO's membership following publication or presentation of potentially practice-changing data from major studies. This provisional clinical opinion addresses the appropriate use of tumor genomic testing in patients with metastatic or advanced solid tumors.

CLINICAL CONTEXT

An increasing number of therapies are approved to treat cancers harboring specific genomic biomarkers. However, there is a lack of clarity as to when tumor genomic sequencing should be ordered, what type of assays should be performed, and how to interpret the results for treatment selection.

PROVISIONAL CLINICAL OPINION

Patients with metastatic or advanced cancer should undergo genomic sequencing in a certified laboratory if the presence of one or more specific genomic alterations has regulatory approval as biomarkers to guide the use of or exclusion from certain treatments for their disease. Multigene panel-based assays should be used if more than one biomarker-linked therapy is approved for the patient's disease. Site-agnostic approvals for any cancer with a high tumor mutation burden, mismatch repair deficiency, or neurotrophic tyrosine receptor kinase (NTRK) fusions provide a rationale for genomic testing for all solid tumors. Multigene testing may also assist in treatment selection by identifying additional targets when there are few or no genotype-based therapy approvals for the patient's disease. For treatment planning, the clinician should consider the functional impact of the targeted alteration and expected efficacy of genomic biomarker-linked options relative to other approved or investigational treatments.Additional information is available at www.asco.org/assays-and-predictive-markers-guidelines.

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients

Metastatic progression is the main cause of death in cancer patients, whereas the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we assembled MSK-MET, a pan-cancer cohort of over 25,000 patients with metastatic diseases. By analyzing genomic and clinical data from this cohort, we identified associations between genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma, and HR+/HER2+ breast ductal carcinoma, but not in others, including colorectal cancer and high-grade serous ovarian cancer, where copy-number alteration patterns may be established early in tumor development. We also identified somatic alterations associated with metastatic burden and specific target organs. Our data offer a valuable resource for the investigation of the biological basis for metastatic spread and highlight the complex role of chromosomal instability in cancer progression.

GA4GH: International policies and standards for data sharing across genomic research and healthcare

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Therapeutic Implications of Germline Testing in Patients With Advanced Cancers

PURPOSE

Tumor mutational profiling is increasingly performed in patients with advanced cancer. We determined the extent to which germline mutation profiling guides therapy selection in patients with advanced cancer.

METHODS

Patients with cancer undergoing tumor genomic profiling were prospectively consented for germline cancer predisposition gene analysis (2015-2019). In patients harboring germline likely pathogenic or pathogenic (LP/P) alterations, therapeutic actionability was classified using a precision oncology knowledge base. Patients with metastatic or recurrent cancer receiving germline genotype-directed therapy were determined.

RESULTS

Among 11,947 patients across > 50 malignancies, 17% (n = 2,037) harbored a germline LP/P variant. By oncology knowledge base classification, 9% (n = 1042) had an LP/P variant in a gene with therapeutic implications (4% level 1; 4% level 3B; < 1% level 4). BRCA1/2 variants accounted for 42% of therapeutically actionable findings, followed by CHEK2 (13%), ATM (12%), mismatch repair genes (11%), and PALB2 (5%). When limited to the 9,079 patients with metastatic or recurrent cancer, 8% (n = 710) harbored level 1 or 3B genetic findings and 3.2% (n = 289) received germline genotype-directed therapy. Germline genotype-directed therapy was received by 61% and 18% of metastatic cancer patients with level 1 and level 3B findings, respectively, and by 54% of BRCA1/2, 75% of mismatch repair, 43% of PALB2, 35% of RAD51C/D, 24% of BRIP1, and 19% of ATM carriers. Of BRCA1/2 patients receiving a poly(ADP-ribose) polymerase inhibitor, 45% (84 of 188) had tumors other than breast or ovarian cancer, wherein the drug, at time of delivery, was delivered in an investigational setting.

CONCLUSION

In a pan-cancer analysis, 8% of patients with advanced cancer harbored a germline variant with therapeutic actionability with 40% of these patients receiving germline genotype-directed treatment. Germline sequence analysis is additive to tumor sequence analysis for therapy selection and should be considered for all patients with advanced cancer.

Pancreas cancer and BRCA: A critical subset of patients with improving therapeutic outcomes

BACKGROUND

Patients with germline/somatic BRCA1/BRCA2 mutations (g/sBRCA1/2) comprise a distinct biologic subgroup of pancreas ductal adenocarcinoma (PDAC).

METHODS

Institutional databases were queried to identify patients who had PDAC with g/sBRCA1/2. Demographics, clinicopathologic details, genomic data (annotation sBRCA1/2 according to a precision oncology knowledge base for somatic mutations), zygosity, and outcomes were abstracted. Overall survival (OS) was estimated using the Kaplan-Meier method.

RESULTS

In total, 136 patients with g/sBRCA1/2 were identified between January 2011 and June 2020. Germline BRCA1/2 (gBRCA1/2) mutation was identified in 116 patients (85%). Oncogenic somatic BRCA1/2 (sBRCA1/2) mutation was present in 20 patients (15%). Seventy-seven patients had biallelic BRCA1/2 mutations (83%), and 16 (17%) had heterozygous mutations. Sixty-five patients with stage IV disease received frontline platinum therapy, and 52 (80%) had a partial response. The median OS for entire cohort was 27.6 months (95% CI, 24.9-34.5 months), and the median OS for patients who had stage IV disease was 23 months (95% CI, 19-26 months). Seventy-one patients received a poly(adenosine diphosphate ribose) polymerase (PARP) inhibitor (PARPi), and 52 received PARPi monotherapy. For maintenance PARPi, 10 patients (36%) had a partial response, 12 (43%) had stable disease, and 6 (21%) had progression of disease as their best response. Six patients (21%) received maintenance PARPi for >2 years. For those with stage IV disease who received frontline platinum, the median OS was 26 months (95% CI, 20-52 months) for biallelic patients (n = 39) and 8.66 months (95% CI, 6.2 months to not reached) for heterozygous patients (n = 4). The median OS for those who received PARPi therapy was 26.5 months (95% CI, 24-53 months) for biallelic patients (n = 25) and 8.66 months (95% CI, 7.23 months to not reached) for heterozygous patients (n = 2).

CONCLUSIONS

g/sBRCA1/2 mutations did not appear to have different actionable utility. Platinum and PARPi therapies offer therapeutic benefit, and very durable outcomes are observed in a subset of patients who have g/sBRCA1/2 mutations with biallelic status.

The efficacy of intravenous tranexamic acid administration at induction in definitive hip fracture surgery: Is there a role?

Tranexamic acid (TXA) is a cheap and powerful drug that has several uses in surgery and is well established in elective orthopaedic surgery. At present, limited small studies have looked into its role in the acute hip fracture. Transfusion in the geriatric population presents risks and increased costs to healthcare systems around the world. Our retrospective study looks at the role of TXA administration at induction for both intracapsular fracture requiring hemiarthroplasty and our preferred method of fixation of extracapsular fracture by intramedullary nail (IM nail). We show a statistically significant reduction in the number of patients requiring transfusion as well as mean haemoglobin (Hb) drop in those undergoing hemiarthroplasty. This was not replicated in those undergoing IM nail fixation. Both groups showed no increase in 1-year mortality or thromboembolic events following TXA administration. These results support the use of TXA for hemiarthroplasty for intracapsular hip fractures over the age of 60.

OBJECTIVES

The aim of this pre and post interventional study looks at the effects of intravenous administration of tranexamic acid on induction for elderly patients undergoing hemiarthroplasty or intramedullary nail fixation for hip fractures.

DESIGN

Pre and post interventional, randomised observational study SETTING: Large hip fracture unit, Level 2 Trauma Centre, single centre PATIENTS: Two arms of the study looking at those aged above the age of 60 undergoing hemiarthroplasty and intramedullary nail fixation without and with tranexamic acid on induction.

RESULTS

12.1% of hemiarthroplasties required post-operative transfusion without tranexamic acid compared to 2.6% of those with tranexamic acid (n=15 vs n=3 respectively, p=0.006). Equally, the mean Hb drop in g/L is reduced in those with tranexamic acid compared to those without (mean Hb = 14.6 vs 17.7 respectively, p=0.034). This was not replicated in the IM nail group between those without and those with tranexamic acid (n=31 vs n=20 respectively, p= 0.16). The mean Hb drop in g/L was not statistically significant in the tranexamic acid arm compared to without (mean Hb = 19.2 vs mean Hb = 21.9, p=0.11). Gross reporting of thromboembolic events did not demonstrate an increase in the number of those with DVT, PE, MI or stroke. 1-year mortality was not statistically significant in either hemiarthroplasty or IM nail fixation following tranexamic acid administration.

CONCLUSIONS

Tranexamic acid both statistically significantly reduces the number of patients requiring transfusion post hemiarthroplasty and also the value of mean Hb drop without appearing to increase in thromboembolic events or 1 year mortality rates. This does not appear to be emulated in the IM nail fixation although both thrombotic events and 1-year mortality rates are also not affected by administration of TXA. We propose that TXA has a role in hemiarthroplasty surgery in reducing post-operative transfusions.

LEVEL OF EVIDENCE

Level 3 - retrospective cohort study.

Clinical cancer genomic profiling

Technological innovation and rapid reduction in sequencing costs have enabled the genomic profiling of hundreds of cancer-associated genes as a component of routine cancer care. Tumour genomic profiling can refine cancer subtype classification, identify which patients are most likely to benefit from systemic therapies and screen for germline variants that influence heritable cancer risk. Here, we discuss ongoing efforts to enhance the clinical utility of tumour genomic profiling by integrating tumour and germline analyses, characterizing allelic context and identifying mutational signatures that influence therapy response. We also discuss the potential clinical utility of more comprehensive whole-genome and whole-transcriptome sequencing and ultra-sensitive cell-free DNA profiling platforms, which allow for minimally invasive, serial analyses of tumour-derived DNA in blood.

Abstract 99: Evolution of OncoKB, a precision oncology knowledgebase

Genomic sequencing of tumors is a routine part of cancer patient care. To address the need for a comprehensive resource that annotates the oncogenic effects and clinical actionability of somatic alterations in cancer, we developed OncoKB, a precision oncology knowledgebase. Since its introduction in 2016, OncoKB has grown to include annotations for &gt;500 alterations in 682 genes. This includes 42 Level 1 genes (included in the FDA drug label), 12 Level 2 genes (included in the NCCN guidelines), and 29 Level 3A genes (predictive of drug response in well-powered clinical studies).

We evaluated changes in the clinical actionability landscape and evolution of the OncoKB annotation rules and processes by comparing the AACR Project GENIE cohort (v8.1) annotated with the OncoKB version from February 2018 to that from November 2020. Even within a short window of time, this comparison reveals a significant shift of the proportion of samples that harbor a standard care alteration (Level 1 and 2), increasing from ~9% in 2018 to ~24% in 2020, and a Level 3A alteration, decreasing from ~11% to ~5%. This shift is partially attributable to the FDA approval of a PI3K inhibitor in PIK3CA-mutant ER+/HER2- breast cancer, approval of RAF inhibitors in BRAF V600E mutant anaplastic thyroid cancer and colorectal cancer, approval of NTRK-inhibitors in NTRK fusion-positive solid tumors, FGFR-inhibitor approval in FGFR2 fusion-positive bladder cancer and cholangiocarcinoma, RET-inhibitor approval in RET fusion-positive thyroid cancer and non-small cell lung cancer and expansion of indications for PARP inhibitors to include prostate cancer. The tumor agnostic approval of the checkpoint blockade inhibitor, pembrolizumab, in TMB-H solid tumors additionally gave rise to a ~4% increase in Level 1 samples.

Analysis of the AACR Project GENIE cohort also revealed significant changes to the OncoKB process, including those reflected in the updated OncoKB Levels of Evidence v2.0. The refined levels system deprioritized the significance of standard care biomarkers when present in indications outside of the FDA-approved/NCCN listed indication. This change was based on clinical data demonstrating that patients with investigational predictive biomarkers for a specific tumor type based on compelling clinical evidence from phase 3 trials (currently Level 3A) are more likely to experience clinical benefit compared to patients with predictive biomarkers that are considered standard care in a different tumor type (previously Level 2B, currently Level 3B), and is consistent with guidelines published by ASCO/AMP/CAP and ESMO.

Knowledgebases such as OncoKB have emerged as key informational resources that the clinical oncology and scientific communities have used to rapidly connect sequencing results to clinical actionability. Their utility depends on their ability to stay abreast of clinical data and seamlessly adapt their rules and processes to the evolving field of precision medicine.

Citation Format: Sarah P. Suehnholz, Ritika Kundra, Hongxin Zhang, Shaleigh Smith, Moriah Nissan, Yifu Yao, Lindsay LaFave, Kinisha Gala, Linde Miles, Maria E. Arcila, Marc Ladanyi, Michael F. Berger, Ahmet Zehir, Aijaz Syed, Julia Rudolph, Paul Sabbatini, Ross Levine, Ahmet Dogan, Jianjiong Gao, David Solit, Nikolaus Schultz, Debyani Chakravarty. Evolution of OncoKB, a precision oncology knowledgebase [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 99.

Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients

BACKGROUND

Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth.

METHODS

Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES).

RESULTS

cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score<5), 29 had sufficient material to be re-analyzed using a less comprehensive but more sensitive assay, MSK-ACCESS, which revealed somatic mutations in 14/29 (48%). Conversely, 5 patients without alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches.

CONCLUSIONS

cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.

OncoTree: A Cancer Classification System for Precision Oncology

PURPOSE

Cancer classification is foundational for patient care and oncology research. Systems such as International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), and National Cancer Institute Thesaurus (NCIt) provide large sets of cancer classification terminologies but they lack a dynamic modernized cancer classification platform that addresses the fast-evolving needs in clinical reporting of genomic sequencing results and associated oncology research.

METHODS

To meet these needs, we have developed OncoTree, an open-source cancer classification system. It is maintained by a cross-institutional committee of oncologists, pathologists, scientists, and engineers, accessible via an open-source Web user interface and an application programming interface.

RESULTS

OncoTree currently includes 868 tumor types across 32 organ sites. OncoTree has been adopted as the tumor classification system for American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), a large genomic and clinical data-sharing consortium, and for clinical molecular testing efforts at Memorial Sloan Kettering Cancer Center and Dana-Farber Cancer Institute. It is also used by precision oncology tools such as OncoKB and cBioPortal for Cancer Genomics.

CONCLUSION

OncoTree is a dynamic and flexible community-driven cancer classification platform encompassing rare and common cancers that provides clinically relevant and appropriately granular cancer classification for clinical decision support systems and oncology research.

Abstract 3208: OncoKB, a precision oncology knowledgebase

OncoKB is a precision oncology knowledge base that annotates the oncogenic effects and clinical actionability of somatic alterations in cancer. Initially focused on solid tumors, OncoKB was introduced in 2016 with &gt;200 genes and almost 3000 somatic alterations via a public website (oncokb.org) and through the cBioPortal for Cancer Genomics. OncoKB now contains annotations for &gt5000 alterations in 642 genes. This includes 30 Level 1 alterations (included in the FDA drug label; a growth of 114% since 2016), 15 Level 2 alterations (included in the NCCN guidelines; 50% growth), and 38 Level 3A alterations (predictive of drug response in well-powered clinical studies; 65% growth). OncoKB now also supports hematologic malignancies with two new levels of evidence systems that encompass diagnostic and prognostic implications (in addition to therapeutic implications) and 288 heme-specific alterations in 156 newly curated cancer-associated genes. At MSK, OncoKB is used for the annotation of 1000 molecular patient reports per month. To assess the clinical utility of OncoKB and changes in the frequency of actionable alterations, we performed a comparison between the AACR Project GENIE cohort from 2017 and the most recent one (Table 1). With an increased number of tumor types and greater inclusion of hematologic malignancies, the overall potential actionability rate increased by 3.6 percentage points. A shift in access to targeted cancer therapies is also observed, where Level 1 or 2 alterations increased over 5 percentage points and Level 3 alterations decreased by ~3 percentage points, perhaps reaping the benefits of recent successful phase III trials.

August 2017 (v1.1)December 2019 (v7.2)AACR Project GENIE cohort size18,80480,248Tumor types with &gt;100 samples3151Hematologic malignancies included29Level 1 or 2 annotation7.3%12.9%Level 3A annotation6.4%4.7%Level 3B annotation17.8%17.5%Total potential actionability31.5%35.1%

While only a subset of patients with targetable alterations will benefit from treatments, there is ample evidence that targeted cancer therapies can have profound and durable clinical activity. Knowledgebases such as OncoKB have become a key component to support clinical decision making, and there is a continued need to expand their capabilities while maintaining a nuanced approach to annotation.

Citation Format: Sarah Suehnholz, Hongxin Zhang, Moriah Nissan, Ritika Kundra, Jing Su, Lindsay LaFave, Kinisha Gala, Chad Vanderbilt, Maria Arcila, Marc Ladanyi, Michael Berger, Ahmet Zehir, Julia E. Rudolph, Paul Sabbatini, Ross Levine, Ahmet Dogan, Jianjiong Gao, David B. Solit, Nikolaus Schultz, Debyani Chakravarty. OncoKB, a precision oncology knowledgebase [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3208.

Abstract 3222: The Virtual Molecular Tumor Board of the Variant Interpretation for Cancer Consortium: A systematic gateway connecting cancer genome interpretation and progress in genomic knowledgebases in cancer

Comprehensive interpretation of a patient's cancer genome is a cross-disciplinary process requiring the expertise of oncologists, molecular pathologists, genetic counselors, genomic scientists, and bioinformaticians. The Variant Interpretation for Cancer Consortium (VICC) has created a non-clinical forum for the variant interpretation process by connecting experts from multiple academic institutions and industry to create a Virtual Molecular Tumor Board (VMTB). During VICC-VMTB sessions, experts retrospectively discuss de-identified, challenging patient cases in the context of genomic interpretation guidelines to evaluate a patient's profile across several distinct components: genomic variants; disease context; therapeutic history; family history; demographic information; genomic assay information; and variant allele frequency. These components are processed through the prism of publically available knowledge and expertise of VMTB members, resulting in a broad spectrum of clinically relevant assertions about the patient's disease that may be of prognostic, diagnostic, or predictive relevance. Through these evaluations, the VICC-VMTB primarily works as a means of illuminating challenges in genomic interpretation and advancing the objectives of domain-specific VICC working groups. Examples of challenges that have been highlighted by the VICC-VMTB forum include: 1) inconsistent disease and therapy ontologies across resources are being addressed by Disease Harmonization & Drug Harmonization working groups, respectively; 2) use of machine-learning and natural language processing into clinical-grade variant interpretation are being addressed by the AI-Assisted Curation working group; 3) aggregation and harmonization of knowledgebase data into a centralized resource is being addressed by the Data Licensing and Variant Harmonization working groups; 4) inefficiencies in knowledgebase search functions are being addressed by the Search working group; 5) determination of accurate prediction of biological consequences of rare variants is being addressed by the In Silico Interpretation working group; and 6) standardization of genomic variant curation is being addressed by the Knowledge Curation and Interpretation Standards working group. These VICC working groups provide dedicated expert assemblies intended to specifically tackle these challenges, further increasing the breadth for which genomic information can be made useful in cancer variant interpretation. The VICC-VMTB has been a pertinent link between cancer genomes and clinical interpretation. We are confident VICC-VMTB will continue to be a gateway of acceleration and progress needed in the field of cancer interpretation to provide accurate and efficient answers for our patients in the future.

Citation Format: Beth A. Pitel, Shruti Rao, Catherine Del Vecchio Fitz, Subha Madhavan, Rodrigo Dientsmann, Peter Horak, Ian King, Susan M. Mockus, Gordana Raca, Damian T. Rieke, Peter Rogan, Dmitriy Sonkin, David Tamborero, Ioannis S. Vlachos, Brian Walsh, Jeremy L. Warner, Malachi Griffith, Obi L. Griffith, Debyani Chakravarty, Alex H. Wagner. The Virtual Molecular Tumor Board of the Variant Interpretation for Cancer Consortium: A systematic gateway connecting cancer genome interpretation and progress in genomic knowledgebases in cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3222.

Abstract 5707: A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations

Somatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/.

Citation Format: Peter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5707.

Abstract 1096: Harmonization standards from the Variant Interpretation for Cancer Consortium

The use of clinical gene sequencing is now commonplace, and genome analysts and molecular pathologists are often tasked with the labor-intensive process of interpreting the clinical significance of large numbers of tumor variants. Numerous independent knowledgebases have been constructed to alleviate this manual burden, however these knowledgebases are non-interoperable. As a result, the analyst is left with a difficult tradeoff: for each knowledgebase used the analyst must understand the nuances particular to that resource and integrate its evidence accordingly when generating the clinical report, but for each knowledgebase omitted there is increased potential for missed findings of clinical significance.The Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) was formed as a driver project of the Global Alliance for Genomics and Health (GA4GH; ga4gh.org) to address this concern. VICC members include representatives from several major somatic interpretation knowledgebases including CIViC, OncoKB, Jax-CKB, the Weill Cornell PMKB, the IRB-Barcelona Cancer Biomarkers Database, and others. Previously, the VICC built and reported on a harmonized meta-knowledgebase of 19,551 biomarker associations of harmonized variants, diseases, drugs, and evidence across the constituent resources.In that study, we analyzed the frequency with which the tumor samples from the AACR Project GENIE cohort would match to harmonized associations. Variant matches increased dramatically from 57% to 86% when broader matching to regions describing categorical variants were allowed. Unlike precise sequence variants with specified alternate alleles, categorical variants describe a collection of potential variants with a common feature, such as “V600” (non-valine alleles at the 600 residue), “Exon 20 mutations” (all non-silent mutations in exon 20), or “Gain-of-function” (hypermorphic alterations that activate or amplify gene activity). However, matching observed sequence variants to categorical variants is challenging, as the latter are typically only described as unstructured text. Here we describe the expressive and computational GA4GH Variation Representation specification (vr-spec.readthedocs.io), which we co-developed as members of the GA4GH Genomic Knowledge Standards work stream. This specification provides a schema for common, precise forms of variation (e.g. SNVs and Indels) and the method for computing identifiers from these objects. We highlight key aspects of the specification and our work to apply it to the characterization of categorical variation, showcasing the variant terminology and classification tools developed by the VICC to support this effort. These standards and tools are free, open-source, and extensible, overcoming barriers to standardized variant knowledge sharing and search.

Citation Format: Alex H. Wagner, Reece K. Hart, Larry Babb, Robert R. Freimuth, Adam Coffman, Yonghao Liang, Beth Pitel, Angshumoy Roy, Matthew Brush, Jennifer Lee, Anna Lu, Thomas Coard, Shruti Rao, Deborah Ritter, Brian Walsh, Susan Mockus, Peter Horak, Ian King, Dmitriy Sonkin, Subha Madhavan, Gordana Raca, Debyani Chakravarty, Malachi Griffith, Obi L. Griffith. Harmonization standards from the Variant Interpretation for Cancer Consortium [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1096.

RAS/MAPK Pathway Driver Alterations Are Significantly Associated With Oncogenic KIT Mutations in Germ-cell Tumors

OBJECTIVE

To report the mutational profile and clinical outcomes of a cohort of patients with KIT-mutant seminomas and nonseminomatous germ-cell tumors (SGCT/NSGCTs).

PATIENTS AND METHODS

Retrospective cohort study of all patients with KIT-mutant GCTs sequenced at Memorial Sloan Kettering between March 2014 and March 2020. Tumors were assessed with MSK-IMPACT, a DNA next-generation sequencing assay for targeted sequencing of up to 468 key cancer genes.

RESULTS

Among 568 patients with GCTs, 8.1% had somatic KIT mutations, including 28 seminomas and 18 mixed/NSGCTs. Exons 17 (67.3%), 11 (22.4%), and 13 (6.1%) were most commonly affected. KIT-mutant cases were enriched for oncogenic RAS/MAPK pathway alterations compared to KIT-wildtype cases (34.8% vs 19.2%, P = .02). Among KIT-mutant cases, concurrent mutations were noted in KRAS (21.7%), RRAS2 (11.8%), CBL (6.5%), NRAS (4.3%), MAP2K1 (2.2%), and RAC1 (2.2%). Mutations in KRAS, RRAS2, and NRAS were mutually exclusive. In all, 73.9% of patients developed metastases and 95.7% received chemotherapy. No patients received KIT-directed tyrosine kinase inhibitors (TKIs). Classification as a NSGCT rather than a SGCT was associated with an increased risk of death (hazard ratio 9.1, 95% confidence interval 1.1-78.4, P = .04) while the presence of a concurrent RAS/MAPK pathway alteration was not (hazard ratio 0.8, 95% confidence interval 0.1-4.3, P = .76).

CONCLUSION

Mitogenic driver alterations can co-occur with activating KIT mutations, which may explain the lack of efficacy of KIT-directed TKIs in prior trials. Novel KIT-directed TKIs that target exon 17 mutations may benefit chemotherapy-refractory patients with KIT-mutant GCTs without RAS/MAPK alterations. Dual MEK/KIT inhibitor therapy in KIT-mutant GCTs with concurrent RAS/MAPK alterations could also be a plausible therapeutic strategy.

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices

PURPOSE

The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning.

METHODS

In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards.

RESULTS

Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence.

CONCLUSION

Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.

The Evolutionary Origins of Recurrent Pancreatic Cancer

Surgery is the only curative option for stage I/II pancreatic cancer; nonetheless, most patients will experience a recurrence after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer, we performed whole-exome or targeted sequencing of 10 resected primary cancers and matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease after adjuvant or first-line platinum therapy corresponds to an increased mutational burden. Recurrent disease is enriched for genetic alterations predicted to activate MAPK/ERK and PI3K-AKT signaling and develops from a monophyletic or polyphyletic origin. Treatment-induced genetic bottlenecks lead to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In 1 patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings suggest routine post-treatment sampling may have value in the management of recurrent pancreatic cancer. SIGNIFICANCE: The biological features or clinical vulnerabilities of recurrent pancreatic cancer after pancreaticoduodenectomy are unknown. Using whole-exome sequencing we find that recurrent disease has a distinct genomic landscape, intermetastatic genetic heterogeneity, diverse clonal origins, and higher mutational burden than found for treatment-naïve disease.See related commentary by Bednar and Pasca di Magliano, p. 762.This article is highlighted in the In This Issue feature, p. 747.

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT)

Background

In order to facilitate implementation of precision medicine in clinical management of cancer, there is a need to harmonise and standardise the reporting and interpretation of clinically relevant genomics data.

Methods

The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group (TR and PM WG) launched a collaborative project to propose a classification system for molecular aberrations based on the evidence available supporting their value as clinical targets. A group of experts from several institutions was assembled to review available evidence, reach a consensus on grading criteria and present a classification system. This was then reviewed, amended and finally approved by the ESMO TR and PM WG and the ESMO leadership.

Results

This first version of the ESMO Scale of Clinical Actionability for molecular Targets (ESCAT) defines six levels of clinical evidence for molecular targets according to the implications for patient management: tier I, targets ready for implementation in routine clinical decisions; tier II, investigational targets that likely define a patient population that benefits from a targeted drug but additional data are needed; tier III, clinical benefit previously demonstrated in other tumour types or for similar molecular targets; tier IV, preclinical evidence of actionability; tier V, evidence supporting co-targeting approaches; and tier X, lack of evidence for actionability.

Conclusions

The ESCAT defines clinical evidence-based criteria to prioritise genomic alterations as markers to select patients for targeted therapies. This classification system aims to offer a common language for all the relevant stakeholders in cancer medicine and drug development.

Clinical Genomic Sequencing of Pediatric and Adult Osteosarcoma Reveals Distinct Molecular Subsets with Potentially Targetable Alterations

PURPOSE

Although multimodal chemotherapy has improved outcomes for patients with osteosarcoma, the prognosis for patients who present with metastatic and/or recurrent disease remains poor. In this study, we sought to define how often clinical genomic sequencing of osteosarcoma samples could identify potentially actionable alterations.Experimental Design: We analyzed genomic data from 71 osteosarcoma samples from 66 pediatric and adult patients sequenced using MSK-IMPACT, a hybridization capture-based large panel next-generation sequencing assay. Potentially actionable genetic events were categorized according to the OncoKB precision oncology knowledge base, of which levels 1 to 3 were considered clinically actionable.

RESULTS

We found at least one potentially actionable alteration in 14 of 66 patients (21%), including amplification of CDK4 (n = 9, 14%: level 2B) and/or MDM2 (n = 9, 14%: level 3B), and somatic truncating mutations/deletions in BRCA2 (n = 3, 5%: level 2B) and PTCH1 (n = 1, level 3B). In addition, we observed mutually exclusive patterns of alterations suggesting distinct biological subsets defined by gains at 4q12 and 6p12-21. Specifically, potentially targetable gene amplifications at 4q12 involving KIT, KDR, and PDGFRA were identified in 13 of 66 patients (20%), which showed strong PDGFRA expression by IHC. In another largely nonoverlapping subset of 14 patients (24%) with gains at 6p12-21, VEGFA amplification was identified.

CONCLUSIONS

We found potentially clinically actionable alterations in approximately 21% of patients with osteosarcoma. In addition, at least 40% of patients have tumors harboring PDGFRA or VEGFA amplification, representing candidate subsets for clinical evaluation of additional therapeutic options. We propose a new genomically based algorithm for directing patients with osteosarcoma to clinical trial options.

Real-World Outcomes of an Automated Physician Support System for Genome-Driven Oncology

PURPOSE

Matching patients to investigational therapies requires new tools to support physician decision making. We designed and implemented Precision Insight Support Engine (PRECISE), an automated, just-in-time, clinical-grade informatics platform to identify and dynamically track patients on the basis of molecular and clinical criteria. Real-world use of this tool was analyzed to determine whether PRECISE facilitated enrollment to early-phase, genome-driven trials.

MATERIALS AND METHODS

We analyzed patients who were enrolled in genome-driven, early-phase trials using PRECISE at Memorial Sloan Kettering Cancer Center between April 2014 and January 2018. Primary end point was the proportion of enrolled patients who were successfully identified using PRECISE before enrollment. Secondary end points included time from sequencing and PRECISE identification to enrollment. Reasons for a failure to identify genomically matched patients were also explored.

RESULTS

Data were analyzed from 41 therapeutic trials led by 19 principal investigators. In total, 755 patients were accrued to these studies during the period that PRECISE was used. PRECISE successfully identified 327 patients (43%) before enrollment. Patients were diagnosed with 29 tumor types and harbored alterations in 43 oncogenes, most commonly ERBB2 (21.3%), PIK3CA (14.1%), and BRAF (8.7%). Median time from sequencing to enrollment was 163 days (interquartile range, 66 to 357 days), and from PRECISE identification to enrollment 87 days (interquartile range, 37 to 180 days). Common reasons for failing to identify patients before enrollment included accrual on the basis of molecular alterations that did not match pre-established PRECISE genomic eligibility (140 [33%] of 428) and external sequencing not available for parsing (127 [30%] of 428).

CONCLUSION

PRECISE identified 43% of all patients accrued to a diverse cohort of early-phase, genome-matched studies. Purpose-built informatics platforms represent a novel and potentially effective method for matching patients to molecularly selected studies.

Clinical Genomic Sequencing of Pediatric and Adult Osteosarcoma Reveals Distinct Molecular Subsets with Potentially Targetable Alterations

PURPOSE

Although multimodal chemotherapy has improved outcomes for patients with osteosarcoma, the prognosis for patients who present with metastatic and/or recurrent disease remains poor. In this study, we sought to define how often clinical genomic sequencing of osteosarcoma samples could identify potentially actionable alterations.Experimental Design: We analyzed genomic data from 71 osteosarcoma samples from 66 pediatric and adult patients sequenced using MSK-IMPACT, a hybridization capture-based large panel next-generation sequencing assay. Potentially actionable genetic events were categorized according to the OncoKB precision oncology knowledge base, of which levels 1 to 3 were considered clinically actionable.

RESULTS

We found at least one potentially actionable alteration in 14 of 66 patients (21%), including amplification of CDK4 (n = 9, 14%: level 2B) and/or MDM2 (n = 9, 14%: level 3B), and somatic truncating mutations/deletions in BRCA2 (n = 3, 5%: level 2B) and PTCH1 (n = 1, level 3B). In addition, we observed mutually exclusive patterns of alterations suggesting distinct biological subsets defined by gains at 4q12 and 6p12-21. Specifically, potentially targetable gene amplifications at 4q12 involving KIT, KDR, and PDGFRA were identified in 13 of 66 patients (20%), which showed strong PDGFRA expression by IHC. In another largely nonoverlapping subset of 14 patients (24%) with gains at 6p12-21, VEGFA amplification was identified.

CONCLUSIONS

We found potentially clinically actionable alterations in approximately 21% of patients with osteosarcoma. In addition, at least 40% of patients have tumors harboring PDGFRA or VEGFA amplification, representing candidate subsets for clinical evaluation of additional therapeutic options. We propose a new genomically based algorithm for directing patients with osteosarcoma to clinical trial options.

Publisher Correction: The long tail of oncogenic drivers in prostate cancer

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comprehensive Genomic Analysis of Metastatic Non-Clear-Cell Renal Cell Carcinoma to Identify Therapeutic Targets

PURPOSE

Non-clear-cell renal cell carcinoma (nccRCC) encompasses approximately 20% of renal cell carcinomas and includes subtypes that vary in clinical and molecular biology. Compared with clear cell renal cell carcinoma, nccRCC demonstrates limited sensitivity to conventional vascular endothelial growth factor- and mammalian target of rapamycin-directed agents, indicating a need for better therapies. Characterizing the genomic landscape of metastatic nccRCC variants may help define novel therapeutic strategies.

PATIENTS AND METHODS

We retrospectively analyzed tumor tissue from patients with metastatic nccRCC who consented to genomic analysis of their tumor and germline DNA. A hybridization capture-based assay was used to identify single nucleotide variants and small insertions and deletions across more than 340 cancer-associated genes with germline comparison. Clinical actionability of somatic mutations was assessed using OncoKB levels of evidence. Microsatellite instability (MSI) in the tumor was investigated.

RESULTS

Of 116 patients included in the analysis, 57 (49%) presented with de novo metastatic disease, and 59 (51%) presented with localized disease that later metastasized. Subtype classifications included unclassified (n = 41; 35%), papillary (n = 26; 22%), chromophobe (n = 17; 15%), translocation associated (n = 13; 11%), and other (n = 19; 16%). Of all tumors, 15 (13%) had putative driver somatic alterations amenable to targeted therapies, including alterations in MET, TSC1/2, and an ALK translocation. Of 45 patients who had germline testing, 11 (24%) harbored mutations, seven of which could potentially guide therapy. Of 115 available tumors for analysis, two (1.7%) had high and six (5%) had intermediate MSI status.

CONCLUSION

The mutation profiles of metastatic nccRCC vary by subtype. Comprehensive analysis of somatic mutations, germline mutations, and MSI, interpreted via an annotated precision oncology knowledge base, identified potentially targetable alterations in 22% of patients, which merits additional investigation.

Integrating somatic variant data and biomarkers for germline variant classification in cancer predisposition genes

In its landmark paper about Standards and Guidelines for the Interpretation of Sequence Variants, the American College of Medical Genetics and Genomics (ACMG), and Association for Molecular Pathology (AMP) did not address how to use tumor data when assessing the pathogenicity of germline variants. The Clinical Genome Resource (ClinGen) established a multidisciplinary working group, the Germline/Somatic Variant Subcommittee (GSVS) with this focus. The GSVS implemented a survey to determine current practices of integrating somatic data when classifying germline variants in cancer predisposition genes. The GSVS then reviewed and analyzed available resources of relevant somatic data, and performed integrative germline variant curation exercises. The committee determined that somatic hotspots could be systematically integrated into moderate evidence of pathogenicity (PM1). Tumor RNA sequencing data showing altered splicing may be considered as strong evidence in support of germline pathogenicity (PVS1) and tumor phenotypic features such as mutational signatures be considered supporting evidence of pathogenicity (PP4). However, at present, somatic data such as focal loss of heterozygosity and mutations occurring on the alternative allele are not recommended to be systematically integrated, instead, incorporation of this type of data should take place under the advisement of multidisciplinary cancer center tumor-normal sequencing boards.

Multicenter phase II study of temozolomide and myeloablative chemotherapy with autologous stem cell transplant for newly diagnosed anaplastic oligodendroglioma

Background

Anaplastic oligodendroglioma (AO) and anaplastic oligoastrocytoma (AOA) are chemotherapy-sensitive tumors with prolonged survival after radiochemotherapy. We report a prospective trial using induction temozolomide (TMZ) followed by myeloablative high-dose chemotherapy (HDC) with autologous stem-cell transplant (ASCT) as a potential strategy to defer radiotherapy.

Methods

Patients with AO/AOA received 6 cycles of TMZ (200 mg/m2 × 5/28 day). Responding patients were eligible for HDC (thiotepa 250 mg/m2/day × 3 days, then busulfan 3.2 mg/kg/day × 3 days), followed by ASCT. Genomic characterization was performed using next-generation sequencing.

Results

Forty-one patients were enrolled; 85% had 1p/19q codeleted tumors. After induction, 26 patients were eligible for HDC-ASCT and 21 agreed to proceed. There were no unexpected adverse events or toxic deaths. After median follow-up of 66 months, 2-year progression-free survival (PFS) for transplanted patients was 86%, 5-year PFS 60%, and no patient has died. Among all 1p/19q codeleted patients (N = 33), 5-year PFS was 50% and 5-year overall survival (OS) 93%, with median time to radiotherapy not reached. Next-generation sequencing disclosed typical oligodendroglioma-related mutations, including IDH1, TERT, CIC, and FUBP1 mutations in 1p/19q codeleted patients, and glioblastoma-like signatures in 1p/19q intact patients. Aside from IDH1, potentially oncogenic/actionable mutations were variable, depicting wide molecular heterogeneity within oligodendroglial tumors.

Conclusions

TMZ followed by HDC-ASCT can be safely administered to patients with newly diagnosed 1p/19q codeleted AO. This strategy was associated with promising PFS and OS, suggesting that a chemotherapy-based approach may delay the need for radiotherapy and radiation-related toxicities. Raw data for further genomic and meta-analyses are publicly available at http://cbioportal.org/study?id=odg_msk_2017, accessed 6 January 2017.

Clinicaltrials.gov registry

NCT00588523.