Ataxia-Telangiectasia Mutated Loss-of-Function Displays Variant and Tissue-Specific Differences across Tumor Types.

PURPOSE: Mutations in the ATM gene are common in multiple cancers, but clinical studies of therapies targeting ATM-aberrant cancers have yielded mixed results. Refinement of ATM loss of function (LOF) as a predictive biomarker of response is urgently needed. EXPERIMENTAL DESIGN: We present the first disclosure and preclinical development of a novel, selective ATR inhibitor, ART0380, and test its antitumor activity in multiple preclinical cancer models. To refine ATM LOF as a predictive biomarker, we performed a comprehensive pan-cancer analysis of ATM variants in patient tumors and then assessed the ATM variant-to-protein relationship. Finally, we assessed a novel ATM LOF biomarker approach in retrospective clinical data sets of patients treated with platinum-based chemotherapy or ATR inhibition. RESULTS: ART0380 had potent, selective antitumor activity in a range of preclinical cancer models with differing degrees of ATM LOF. Pan-cancer analysis identified 10,609 ATM variants in 8,587 patient tumors. Cancer lineage-specific differences were seen in the prevalence of deleterious (Tier 1) versus unknown/benign (Tier 2) variants, selective pressure for loss of heterozygosity, and concordance between a deleterious variant and ATM loss of protein (LOP). A novel ATM LOF biomarker approach that accounts for variant classification, relationship to ATM LOP, and tissue-specific penetrance significantly enriched for patients who benefited from platinum-based chemotherapy or ATR inhibition. CONCLUSIONS: These data help to better define ATM LOF across tumor types in order to optimize patient selection and improve molecularly targeted therapeutic approaches for patients with ATM LOF cancers.

Clinico-Genomic Profiling of Conventional and Dedifferentiated Chondrosarcomas Reveals TP53 Mutation to Be Associated with Worse Outcomes.

PURPOSE: Chondrosarcomas are the most common primary bone tumor in adults. Isocitrate dehydrogenase 1 (IDH1) and IDH2 mutations are prevalent. We aimed to assess the clinico-genomic properties of IDH mutant versus IDH wild-type (WT) chondrosarcomas as well as alterations in other genes. EXPERIMENTAL DESIGN: We included 93 patients with conventional and dedifferentiated chondrosarcoma for which there were available clinical next-generation sequencing data. Clinical and genomic data were extracted and compared between IDH mutant and IDH WT chondrosarcomas and between TP53 mutant and TP53 WT chondrosarcomas. RESULTS: IDH1 and IDH2 mutations are prevalent in chondrosarcoma (50.5%), more common in chondrosarcomas arising in the extremities, associated with higher age at diagnosis, and more common in dedifferentiated chondrosarcomas compared with grades 1-3 conventional chondrosarcoma. There was no difference in survival based on IDH mutation in univariate and multivariate analyses. TP53 mutation was the next most prevalent (41.9%) and is associated with worse overall survival and metastasis-free survival in both univariate and multivariate analyses. TP53 mutation was also associated with higher risk of recurrence following curative-intent surgery and worse survival among patients that presented with de novo metastatic disease. CONCLUSIONS: IDH mutations are prevalent in chondrosarcoma though were not associated with survival outcomes in this cohort. TP53 mutations were the next most common alteration and were associated with worse outcomes.

Actionability classification of variants of unknown significance correlates with functional effect.

Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either "Unknown" or "Potentially" actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable (N = 204) were more likely to be oncogenic than those categorized as Unknown (N = 230) (37% vs 13%, p = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy.

Clinical implications of tumor-based next-generation sequencing in high-grade epithelial ovarian cancer.

BACKGROUND: Tumor-based next-generation sequencing is used inconsistently as a tool to tailor treatment of ovarian cancer, yet beyond detection of somatic BRCA1 and BRCA2 mutations, the clinical benefit is not well established. This study aimed to assess the clinical relevance of tumor-based next-generation sequencing (tbNGS) in patients with ovarian cancer. METHODS: This retrospective study included patients with high-grade epithelial ovarian carcinoma. tbNGS results were identified in the electronic medical record using optical character recognition and natural language processing. Genetic, clinical, and demographic information was collected. Progression-free survival (PFS) and overall survival were calculated and compared using log-rank tests. Multivariate Cox regression and clustering analyses were used to identify patterns of genetic alterations associated with survival. RESULTS: Of 1092 patients in the described population, 409 (37.5%) had tbNGS results. Nearly all (96.1% [393/409]) had one or more genetic alterations. In 25.9% (106/409) of patients, an alteration that aligned with a targeted treatment was identified, and in an additional 48.7% (199/409), tbNGS results suggested eligibility for an investigational agent or clinical trial. The most frequent alterations were TP53, PIK3CA, and NF1 mutations, and CCNE1 amplification. Together, BRCA1 and BRCA2 mutations were associated with longer PFS (hazard ratio [HR], 0.62; 95% confidence interval [CI], 0.42-0.92; p = .02), whereas AKT2 amplification was associated with shorter PFS (HR, 3.86; 95% CI, 1.002-14.88; p < .05). Multivariate Cox regression and clustering analyses identified several combinations of genetic alterations that corresponded to outcomes in patients with high-grade serous carcinoma. CONCLUSIONS: tbNGS often yields clinically relevant information. Detailed analysis of population-level tumor genomics may help to identify therapeutic targets and guide development of clinical decision support tools. PLAIN LANGUAGE SUMMARY: Although more and more patients with ovarian cancer are undergoing tumor-based next-generation sequencing to identify genetic mutations in their tumors, the benefits of such testing are not well established. In a group of over 400 patients with ovarian cancer who underwent tumor-based next-generation sequencing in the course of their treatment, nearly all patients had one or more genetic alterations detected, and one out of four patients had a mutation that qualified them for a personalized treatment option.

Integrative Clinical and Genomic Characterization of MTAP-deficient Metastatic Urothelial Cancer.

Deficiency of MTAP (MTAPdef) mainly occurs because of homozygous loss of chromosome 9p21, which is the most common copy-number loss in metastatic urothelial cancer (mUC). We characterized the clinical and genomic features of MTAPdef mUC in 193 patients treated at MD Anderson Cancer Center (MDACC) and 298 patients from the phase 2 IMvigor210 trial, which investigated atezolizumab in cisplatin-ineligible and platinum-refractory disease. In the MDACC cohort, visceral metastases were significantly more common for MTAPdef (n = 48) than for MTAP-proficient (MTAPprof; n = 145) patients (75% vs 55.2%; p = 0.02). MTAPdef was associated with poor prognosis (median overall survival [mOS] 12.3 vs 20.2 mo; p = 0.007) with an adjusted hazard ratio of 1.93 (95% confidence interval 1.35-2.98). Similarly, IMvigor210 patients with MTAPlo (n = 29) had a higher incidence of visceral metastases than those with MTAPhi tumors (n = 269; 86.2% vs 72.5%; p = 0.021) and worse prognosis (mOS 8.0 vs 11.3 mo; p = 0.042). Hyperplasia-associated genes were more frequently mutated in MTAPdef tumors (FGFR3: 31% vs 8%; PI3KCA: 31% vs 19%), while alterations in dysplasia-associated genes were less common in MTAPdef tumors (TP53: 41% vs 67%; RB1: 0% vs 16%). Our findings support a distinct biology in MTAPdef mUC that is associated with early visceral disease and worse prognosis. PATIENT SUMMARY: We investigated the outcomes for patients with the most common gene loss (MTAP gene) in metastatic cancer of the urinary tract. We found that this loss correlates with worse prognosis and a higher risk of metastasis in internal organs. There seems to be distinct tumor biology for urinary tract cancer with MTAP gene loss and this could be a potential target for treatment.

Association of Prediagnosis Obesity and Postdiagnosis Aspirin With Survival From Stage IV Colorectal Cancer.

Importance: The potential relationship between obesity and colorectal cancer (CRC) outcome is poorly understood in patients with late-stage disease. Increased body mass index may negate aspirin use for cancer prevention, but its role as a factor on the effectiveness of postdiagnosis aspirin use is unclear. Objective: To evaluate how prediagnosis obesity and postdiagnosis aspirin use may be associated with overall survival in patients with late-stage colorectal cancer. Design, Setting, and Participants: This cross-sectional study used self-reported data from patients with metastatic or treatment-refractory disease who consented to a clinical protocol at MD Anderson Cancer Center, a large US cancer treatment center. Patients were enrolled between 2010 and 2018 and followed up for mortality through July 2020. Analyses were conducted through March 2022. Exposures: Body mass index in the decade prior to initial diagnosis and regular aspirin use at survey completion. Main Outcomes and Measures: Overall survival was measured from stage IV diagnosis until death or last follow-up. Cox proportional hazards models were constructed to estimate associations of prediagnosis obesity and postdiagnosis aspirin use with overall survival. Results: Of 656 patients included in this analysis, 280 (42.7%) were women, 135 (20.6%) were diagnosed with CRC before age 45 years, 414 (63.1%) were diagnosed between ages 45 and 65 years, and 107 (16.3%) were diagnosed at 65 years or older; 105 patients (16.0%) were Black or Hispanic, and 501 (76.4%) were non-Hispanic White. Controlling for age, sex, race, stage at initial diagnosis, and weight change between prediagnosis and survey date, patients with obesity in the decade prior to CRC diagnosis had significantly higher likelihood of death (hazard ratio, 1.45; 95% CI, 1.11-1.91) compared with those with normal prediagnosis body mass index. Furthermore, only patients with normal prediagnosis body mass index experienced significant survival benefit with postdiagnosis aspirin use (hazard ratio, 0.59; 95% CI, 0.39-0.90). Conclusions and Relevance: In this cross-sectional study, our findings suggest potentially differential tumor development in the long-term physiologic host environment of obesity. Confirmation and further evaluation are needed to determine whether prediagnosis body mass index may be used to estimate the benefit from postdiagnosis aspirin use.

Clinical and Molecular Characterization of POLE Mutations as Predictive Biomarkers of Response to Immune Checkpoint Inhibitors in Advanced Cancers.

PURPOSE: DNA polymerase epsilon is critical to DNA proofreading and replication. Mutations in POLE have been associated with hypermutated tumors and antitumor response to immune checkpoint inhibitor (ICI) therapy. We present a clinicopathologic analysis of patients with advanced cancers harboring POLE mutations, the pattern of co-occurring mutations, and their response to ICI therapy within the context of mutation pathogenicity. METHODS: We conducted a retrospective analysis of next-generation sequencing data at MD Anderson Cancer Center to identify patient tumors with POLE mutations and their co-occurring mutations. The pathogenicity of each mutation was annotated using InterVar and ClinVar. Differences in therapeutic response to ICI, survival, and co-occurring mutations were reported by POLE pathogenicity status. RESULTS: Four hundred fifty-eight patient tumors with POLE mutations were identified from 14,229 next-generation sequencing reports; 15.0% of POLE mutations were pathogenic, 15.9% benign, and 69.1% variant of unknown significance. Eighty-two patients received either programmed death 1 or programmed death ligand-1 inhibitors as monotherapy or in combination with cytotoxic T-cell lymphocyte-4 inhibitors. Patients with pathogenic POLE mutations had improved clinical benefit rate (82.4% v 30.0%; P = .013), median progression-free survival (15.1 v 2.2 months; P < .001), overall survival (29.5 v 6.8 months; P < .001), and longer treatment duration (median 15.5 v 2.5 months; P < .001) compared to those with benign variants. Progression-free survival and overall survival remained superior when adjusting for number of co-occurring mutations (≥ 10 v < 10) and/or microsatellite instability status (proficient mismatch repair v deficient mismatch repair). The number of comutations was not associated with response to ICI (clinical benefit v progressive disease: median 13 v 11 comutations; P = .18). CONCLUSION: Pathogenic POLE mutations were associated with clinical benefit to ICI therapy. Further studies are warranted to validate POLE mutation as a predictive biomarker of ICI therapy.

A functional genomic approach to actionable gene fusions for precision oncology.

Fusion genes represent a class of attractive therapeutic targets. Thousands of fusion genes have been identified in patients with cancer, but the functional consequences and therapeutic implications of most of these remain largely unknown. Here, we develop a functional genomic approach that consists of efficient fusion reconstruction and sensitive cell viability and drug response assays. Applying this approach, we characterize ~100 fusion genes detected in patient samples of The Cancer Genome Atlas, revealing a notable fraction of low-frequency fusions with activating effects on tumor growth. Focusing on those in the RTK-RAS pathway, we identify a number of activating fusions that can markedly affect sensitivity to relevant drugs. Last, we propose an integrated, level-of-evidence classification system to prioritize gene fusions systematically. Our study reiterates the urgent clinical need to incorporate similar functional genomic approaches to characterize gene fusions, thereby maximizing the utility of gene fusions for precision oncology.

Natural Language Processing-Assisted Literature Retrieval and Analysis for Combination Therapy in Cancer.

PURPOSE: Despite advances in molecular therapeutics, few anticancer agents achieve durable responses. Rational combinations using two or more anticancer drugs have the potential to achieve a synergistic effect and overcome drug resistance, enhancing antitumor efficacy. A publicly accessible biomedical literature search engine dedicated to this domain will facilitate knowledge discovery and reduce manual search and review. METHODS: We developed RetriLite, an information retrieval and extraction framework that leverages natural language processing and domain-specific knowledgebase to computationally identify highly relevant papers and extract key information. The modular architecture enables RetriLite to benefit from synergizing information retrieval and natural language processing techniques while remaining flexible to customization. We customized the application and created an informatics pipeline that strategically identifies papers that describe efficacy of using combination therapies in clinical or preclinical studies. RESULTS: In a small pilot study, RetriLite achieved an F1 score of 0.93. A more extensive validation experiment was conducted to determine agents that have enhanced antitumor efficacy in vitro or in vivo with poly (ADP-ribose) polymerase inhibitors: 95.9% of the papers determined to be relevant by our application were true positive and the application's feature of distinguishing a clinical paper from a preclinical paper achieved an accuracy of 97.6%. Interobserver assessment was conducted, which resulted in a 100% concordance. The data derived from the informatics pipeline have also been made accessible to the public via a dedicated online search engine with an intuitive user interface. CONCLUSION: RetriLite is a framework that can be applied to establish domain-specific information retrieval and extraction systems. The extensive and high-quality metadata tags along with keyword highlighting facilitate information seekers to more effectively and efficiently discover knowledge in the combination therapy domain.

Emergence of mTOR mutation as an acquired resistance mechanism to AKT inhibition, and subsequent response to mTORC1/2 inhibition.

Acquired resistance to molecular targeted therapy is a significant challenge of the precision medicine era. The ability to understand these mechanisms of resistance may improve patient selection and allow for the development of rationally designed next-line or combination treatment strategies and improved patient outcomes. AKT is a critical effector of the phosphoinositide 3-kinase signaling cascade, one of the most commonly activated pathways in human cancer. Deregulation of signaling pathways, such as RAF/MEK/ERK are previously described mechanisms of resistance to AKT/PI3K inhibitors. Mutations in the mTOR gene, however, are exceedingly rare. We present a case of acquired mTOR resistance, following targeted AKT inhibition, and subsequent response to mTOR1/2 inhibitor in a patient with metastatic endometrial cancer, the first documented response to ATP-competitive mTOR inhibition in this setting. This case supports mTOR mutation as a mechanism of resistance, and underscores the importance of tumor molecular profiling, exemplifying precision medicine in action.

RAC1 Alterations Induce Acquired Dabrafenib Resistance in Association with Anaplastic Transformation in a Papillary Thyroid Cancer Patient.

BRAF-activating mutations are the most frequent driver mutations in papillary thyroid cancer (PTC). Targeted inhibitors such as dabrafenib have been used in advanced BRAF-mutated PTC; however, acquired resistance to the drug is common and little is known about other effectors that may play integral roles in this resistance. In addition, the induction of PTC dedifferentiation into highly aggressive KRAS-driven anaplastic thyroid cancer (ATC) has been reported. We detected a novel RAC1 (P34R) mutation acquired during dabrafenib treatment in a progressive metastatic lesion with ATC phenotype. To identify a potential functional link between this novel mutation and tumor dedifferentiation, we developed a cell line derived from the metastatic lesion and compared its behavior to isogenic cell lines and primary tumor samples. Our data demonstrated that RAC1 mutations induce changes in cell morphology, reorganization of F-actin almost exclusively at the cell cortex, and changes in cell adhesion properties. We also established that RAC1 amplification, with or without mutation, is sufficient to drive cell proliferation and resistance to BRAF inhibition. Further, we identified polyploidy of chromosome 7, which harbors RAC1, in both the metastatic lesion and its derived cell line. Copy number amplification and overexpression of other genes located on this chromosome, such as TWIST1, EGFR, and MET were also detected, which might also lead to dabrafenib resistance. Our study suggests that polyploidy leading to increased expression of specific genes, particularly those located on chromosome 7, should be considered when analyzing aggressive thyroid tumor samples and in further treatments.

Retrospective Case Series Analysis of RAF Family Alterations in Pancreatic Cancer: Real-World Outcomes From Targeted and Standard Therapies.

PURPOSE: In pancreatic cancer (PC), the RAF family alterations define a rare subset of patients that may predict response to inhibition of the BRAF/MEK/ERK signaling pathway. A comprehensive understanding of the molecular and clinical characteristics of RAF-mutated PC may support future development of RAF-directed strategies. METHODS: Clinical outcomes were assessed across a multi-institutional case series of 81 patients with RAF family-mutated PC. Mutational subgroups were defined on the basis of RAF alteration hotspots and therapeutic implications. RESULTS: The frequency of RAF alterations in PC was 2.2% (84 of 3,781) within a prevalence cohort derived from large molecular databases where BRAF V600E (Exon 15), BRAF ΔNVTAP (Exon 11), and SND1-BRAF fusions were the most common variants. In our retrospective case series, we identified 17 of 81 (21.0%) molecular profiles with a BRAF V600/Exon 15 mutation without any confounding drivers, 25 of 81 (30.9%) with BRAF or RAF1 fusions, and 18 of 81 (22.2%) with Exon 11 mutations. The remaining 21 of 81 (25.9%) profiles had atypical RAF variants and/or multiple oncogenic drivers. Clinical benefit from BRAF/MEK/ERK inhibitors was observed in 3 of 3 subjects within the V600 subgroup (two partial responses), 4 of 6 with fusions (two partial responses), 2 of 6 with Exon 11 mutations (one partial response), and 0 of 3 with confounding drivers. Outcomes analyses also suggested a trend favoring fluorouracil-based regimens over gemcitabine/nab-paclitaxel within the fusion subgroup (P = .027). CONCLUSION: Prospective evaluation of RAF-directed therapies is warranted in RAF-mutated PC; however, differential responses to targeted agents or standard regimens for each mutational subgroup should be a consideration when designing clinical trials.

Integrated clinico-molecular profiling of appendiceal adenocarcinoma reveals a unique grade-driven entity distinct from colorectal cancer.

BACKGROUND: Appendiceal adenocarcinoma (AA) is an orphan disease with unique clinical attributes but often treated as colorectal cancer (CRC). Understanding key molecular differences between AA and CRC is critical. METHODS: We performed retrospective analyses of AA patients (N = 266) with tumour and/or blood next-generation sequencing (NGS) (2013-2018) with in-depth clinicopathological annotation. Overall survival (OS) was examined. For comparison, CRC cohorts annotated for sidedness, consensus molecular subtypes (CMS) and mutations (N = 3283) were used. RESULTS: Blood-NGS identified less RAS/GNAS mutations compared to tissue-NGS (4.2% vs. 60.9%, P < 0.0001) and showed poor concordance with tissue for well-/moderately differentiated tumours. RAS (56.2%), GNAS (28.1%) and TP53 (26.9%) were most frequent mutations. Well/moderately differentiated tumours harboured more RAS (69.2%/64.0% vs. 40.5%) and GNAS (48.7%/32.0% vs. 10.1%) while moderate/poorly differentiated tumours had more TP53 (26.0%/27.8% vs. 7.7%) mutations. Appendiceal adenocarcinoma (compared to CRC) harboured significantly fewer APC (9.1% vs. 55.4%) and TP53 (26.9% vs. 67.5%) and more GNAS mutations (28.1% vs. 2.0%) (P < 0.0001). Appendiceal adenocarcinoma mutation profile did not resemble either right-sided CRC or any of the four CMS in CRC. High grade, but no mutation, was independently predictive of survival. CONCLUSION: Integrated clinico-molecular profiling of AA identified key molecular drivers distinct from CRC. Appendiceal adenocarcinoma has a predominantly grade-driven biology that trumps mutations.

Evolving insights into the genomic complexity and immune landscape of diffuse large B-cell lymphoma: opportunities for novel biomarkers.

Recently, comprehensive genomic analyses have allowed a better molecular characterization of diffuse large B-cell lymphoma (DLBCL), offering novel opportunities in patient risk stratification and management. In the era of precision medicine, this has allowed us to move closer toward a more promising therapeutic outcome in the setting of DLBCL. In this review, we highlight the newly reported heterogeneous mutational landscapes of DLBCL (from two whole-exome sequencing studies, and from a more recent work targeting a 293-gene of a hematologic malignancy-designed panel. Altogether, these studies provide further evidence of the clinical applicability of genomic tests. We also briefly review established biomarkers in DLBCL (e.g., MYC and TP53), and our understanding of the germinal center cell reaction, including its epigenetic regulation, emphasizing some of the key epigenetic modifiers that play a role in lymphomagenesis, with available therapeutic targets. In addition, we present current data regarding the role of immune landscapes in DLBCL (inflamed versus non-inflamed), how the recently defined molecular DLBCL subtypes may affect the cellular composition of the tumor microenvironment and the function of the immune cells, and how this new knowledge may result in promising therapeutic approaches in the near future.

HEREDITARY ENDOCRINE TUMOURS: CURRENT STATE-OF-THE-ART AND RESEARCH OPPORTUNITIES: The state of science in medullary thyroid carcinoma: current challenges and unmet needs.

The 16th International Multiple Endocrine Neoplasia Workshop (MEN2019) held in Houston, TX, USA, focused on emerging topics in the pathogenesis and therapy of malignant endocrine tumors associated with MEN syndromes. With MEN-2 syndromes, the most common malignancy is medullary thyroid carcinoma (MTC). In the spirit of the original MEN meeting workshop model, the conference included didactic lectures and interactive working groups of clinicians and researchers focused on the state of science in MTC and ongoing challenges or unmet needs in the understanding of MTC and to develop strategies to address these issues.

Comparison of Real-Time Fluorescence Confocal Digital Microscopy With Hematoxylin-Eosin-Stained Sections of Core-Needle Biopsy Specimens.

Importance: Strategies to procure high-quality core-needle biopsy (CNB) specimens are critical for making basic tissue diagnoses and for ancillary testing. Objectives: To investigate acquisition of fluorescence confocal microscopy (FCM) images of interventional radiology (IR)-guided CNB in real time in the radiology suite and to compare the accuracy of FCM diagnoses with those of hematoxylin-eosin (H&E)-stained CNB sections. Design, Setting, and Participants: In this diagnostic study, FCM imaging of IR-guided CNBs was performed in the radiology suite at a major cancer center for patients with an imaging abnormality from August 1, 2016, to April 30, 2019. The time taken to acquire FCM images and the quality of FCM images based on percentage of interpretable tissue with optimal resolution was recorded. The FCM images were read by 2 pathologists and categorized as nondiagnostic, benign/atypical, or suspicious/malignant; these diagnoses were compared with those made using H&E-stained tissue sections. Cases with discrepant diagnosis were reassessed by the pathologists together for a consensus diagnosis. Data were analyzed from June 3 to July 19, 2019. Interventions: Each IR-guided CNB was stained with 0.6mM acridine orange, subjected to FCM imaging, and then processed to generate H&E-stained sections. Main Outcomes and Measures: Mean time taken for acquisition of FCM images, quality of FCM images based on interpretable percentage of the image, and accuracy of diagnostic categorization based on FCM images compared with H&E-stained sections. Results: A total of 105 patients (57 male [54.3%]; mean [SD] age, 63 [13] years) underwent IR-guided CNBs in a mean (SD) of 7 (2) minutes each. The FCM images showed at least 20% of the tissue with optimal quality in 101 CNB specimens (96.2%). The FCM images were accurately interpreted by the 2 pathologists in 100 of 105 cases (95.2%) (2 false-positive and 3 false-negative) and 90 of 105 cases (85.7%) (6 false-positive and 9 false-negative). A reassessment of 14 discordant diagnoses resulted in consensus diagnoses that were accurate in 101 of 105 cases (96.2%) (1 false-positive and 3 false-negative). Conclusions and Relevance: The ease of acquisition of FCM images of acceptable quality and the high accuracy of the diagnoses suggest that FCM may be useful for rapid evaluation of IR-guided CNBs. This approach warrants further investigation.

Comprehensive assessment of computational algorithms in predicting cancer driver mutations.

BACKGROUND: The initiation and subsequent evolution of cancer are largely driven by a relatively small number of somatic mutations with critical functional impacts, so-called driver mutations. Identifying driver mutations in a patient's tumor cells is a central task in the era of precision cancer medicine. Over the decade, many computational algorithms have been developed to predict the effects of missense single-nucleotide variants, and they are frequently employed to prioritize mutation candidates. These algorithms employ diverse molecular features to build predictive models, and while some algorithms are cancer-specific, others are not. However, the relative performance of these algorithms has not been rigorously assessed. RESULTS: We construct five complementary benchmark datasets: mutation clustering patterns in the protein 3D structures, literature annotation based on OncoKB, TP53 mutations based on their effects on target-gene transactivation, effects of cancer mutations on tumor formation in xenograft experiments, and functional annotation based on in vitro cell viability assays we developed including a new dataset of ~ 200 mutations. We evaluate the performance of 33 algorithms and found that CHASM, CTAT-cancer, DEOGEN2, and PrimateAI show consistently better performance than the other algorithms. Moreover, cancer-specific algorithms show much better performance than those designed for a general purpose. CONCLUSIONS: Our study is a comprehensive assessment of the performance of different algorithms in predicting cancer driver mutations and provides deep insights into the best practice of computationally prioritizing cancer mutation candidates for end-users and for the future development of new algorithms.

Identification of biomarkers of immune checkpoint blockade efficacy in recurrent or refractory solid tumor malignancies.

Patients with advanced solid malignancies recurrent or resistant to standard therapy have limited treatment options. The role of molecular biomarkers for predicting immune checkpoint blockade (ICB) efficacy are not well characterized in these patients. Tumor mutational profiles of 490 patients with a variety of advanced solid tumors enrolled in a prospective protocol were analyzed to identify prognostic and predictive biomarkers. ICB therapy was defined as treatment with any CTLA-4, PD-1, and/or PD-L1 monoclonal antibody. ICB treatment was associated with significantly improved overall survival compared to non-ICB therapy. Multivariate regression analysis including the two variables of tumor mutation burden (TMB) and ICB, and their interaction term, showed favorable survival associated with ICB, unfavorable survival associated with TMB without ICB treatment, and improved outcome with increasing TMB in ICB treated patients. Tumor TP53 mutation was associated with worse survival, but these patients still benefitted from ICB. A more comprehensive multivariate analysis including cancer type, specific gene mutations, and TMB revealed that ICB treatment was an independent predictor of improved overall survival. Therefore, ICB-based therapeutic trials are beneficial in patients with advanced solid malignancies, but the most benefit may be restricted to patients with the right combination of TMB and specific tumor histology and genotype.

Cell-free Circulating Tumor DNA Variant Allele Frequency Associates with Survival in Metastatic Cancer.

PURPOSE: Physicians are expected to assess prognosis both for patient counseling and for determining suitability for clinical trials. Increasingly, cell-free circulating tumor DNA (cfDNA) sequencing is being performed for clinical decision making. We sought to determine whether variant allele frequency (VAF) in cfDNA is associated with prognosis. EXPERIMENTAL DESIGN: We performed a retrospective analysis of 298 patients with metastatic disease who underwent clinical comprehensive cfDNA analysis and assessed association between VAF and overall survival. RESULTS: cfDNA mutations were detected in 240 patients (80.5%). Median overall survival (OS) was 11.5 months. cfDNA mutation detection and number of nonsynonymous mutations (NSM) significantly differed between tumor types, being lowest in appendiceal cancer and highest in colon cancer. Having more than one NSM detected was associated with significantly worse OS (HR = 2.3; P < 0.0001). VAF was classified by quartiles, Q1 lowest, Q4 highest VAF. Higher VAF levels were associated with a significantly worse overall survival (VAF Q3 HR 2.3, P = 0.0069; VAF Q4 HR = 3.8, P < 0.0001) on univariate analysis. On multivariate analysis, VAF Q4, male sex, albumin level <3.5 g/dL, number of nonvisceral metastatic sites >0 and number of prior therapies >4 were independent predictors of worse OS. CONCLUSIONS: Higher levels of cfDNA VAF and a higher number of NSMs were associated with worse OS in patients with metastatic disease. Further study is needed to determine optimal VAF thresholds for clinical decision making and the utility of cfDNA VAF as a prognostic marker in different tumor types.

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we trained deep neural networks for prediction of drug response and assessed their performance on multiple clinical cohorts. We demonstrate that deep neural networks outperform the current state in machine learning frameworks. We provide a proof of concept for the use of deep neural network-based frameworks to aid precision oncology strategies.