Prediction and prioritization of rare oncogenic mutations in the cancer Kinome using novel features and multiple classifiers

Dark kinase annotation, mining, and visualization using the Protein Kinase Ontology

The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships among protein kinase sequence, structure, function, and disease in a human and machine-readable format. In this study, we have significantly expanded ProKinO by incorporating additional data on expression patterns and drug interactions. Furthermore, we have developed a completely new browser from the ground up to render the knowledge graph visible and interactive on the web. We have enriched ProKinO with new classes and relationships that capture information on kinase ligand binding sites, expression patterns, and functional features. These additions extend ProKinO's capabilities as a discovery tool, enabling it to uncover novel insights about understudied members of the protein kinase family. We next demonstrate the application of ProKinO. Specifically, through graph mining and aggregate SPARQL queries, we identify the p21-activated protein kinase 5 (PAK5) as one of the most frequently mutated dark kinases in human cancers with abnormal expression in multiple cancers, including a previously unappreciated role in acute myeloid leukemia. We have identified recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation. Additionally, we have identified common ligand/drug binding residues in PAK family kinases, underscoring ProKinO's potential application in drug discovery. The updated ontology browser and the addition of a web component, ProtVista, which enables interactive mining of kinase sequence annotations in 3D structures and Alphafold models, provide a valuable resource for the signaling community. The updated ProKinO database is accessible at https://prokino.uga.edu.

Isolation of TTF-1 Positive Circulating Tumor Cells for Single-Cell Sequencing by Using an Automatic Platform Based on Microfluidic Devices

Single-cell sequencing provides promising information in tumor evolution and heterogeneity. Even with the recent advances in circulating tumor cell (CTC) technologies, it remains a big challenge to precisely and effectively isolate CTCs for downstream analysis. The Cell Reveal^TM system integrates an automatic CTC enrichment and staining machine, an AI-assisted automatic CTC scanning and identification system, and an automatic cell picking machine for CTC isolation. H1975 cell line was used for the spiking test. The identification of CTCs and the isolation of target CTCs for genetic sequencing were performed from the peripheral blood of three cancer patients, including two with lung cancer and one with both lung cancer and thyroid cancer. The spiking test revealed a mean recovery rate of 81.81% even with extremely low spiking cell counts with a linear relationship between the spiked cell counts and the recovered cell counts (Y = 0.7241 × X + 19.76, R² = 0.9984). The three cancer patients had significantly higher TTF-1⁺ CTCs than healthy volunteers. All target CTCs were successfully isolated by the Cell Picker machine for a subsequent genetic analysis. Six tumor-associated mutations in four genes were detected. The present study reveals the Cell Reveal^TM platform can precisely identify and isolate target CTCs and then successfully perform single-cell sequencing by using commercially available genetic devices.

Inferring gene expression from cell-free DNA fragmentation profiles

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

NGS-based profiling of key cancer genes in Indian triple-negative breast cancer patients reinforces molecular heterogeneity of the disease

Triple-negative breast cancers (TNBC) are one of the most aggressive forms of breast cancers. With poor patient outcomes, it presents a great burden on the healthcare systems. There have been some efforts to explore the genomic changes that occur in TNBCs. However, there is not enough data on Indian TNBCs. We sought to understand the mutational landscape of key cancer-associated genes in Indian TNBC patients using TruSeq Cancer Amplicon Panel. We sequenced 51 TNBC patient samples and found great heterogeneity amongst samples with respect to the genomic variants. Several previously reported including alterations in PI3K-AKT pathway genes were also identified. Likewise, we identified several novel high-frequency variants, for example, GNAQ F341S (17%), the functional role of which remains unclear. Our study lays the foundation of larger efforts needed to understand the genomic landscape of Indian TNBCs which can aid in classification and better therapeutic management of patients.

Quality evaluation of signals collected by portable ECG devices using dimensionality reduction and flexible model integration

OBJECTIVE

Portable devices for collecting electrocardiograms (ECGs) and telemedicine systems for diagnosis are available to residents in deprived areas, but ECGs collected by non-professionals are not necessarily reliable and may impair the accuracy of diagnosis. We propose an algorithm for accurate ECG quality assessment, which can help improve the reliability of ECGs collected by portable devices.

APPROACH

Using challenge data from CinC (2019), signals were classified as 'acceptable' and 'unacceptable' by annotators. The training set contained 998 12-lead ECGs and the test set contained 500. A 998 × 84 feature matrix, S, was formed by feature extraction and three basic models were obtained through training SVM, DT and NBC on S. The feature subsets S1, S2 and S3 were obtained by dimensionality reduction on S using SVM, DT and NBC, respectively. Three other basic models were obtained through training SVM on S1, DT on S2 and NBC on S3. By combining these six basic models, several integrated models were formed. An iterative method was proposed to select the integrated model with the highest accuracy on the training set. Having compared differences between the output labels and the original data labels, evaluation criteria were calculated.

MAIN RESULTS

An accuracy of 98.70% and 98.60% was achieved on the training and test datasets, respectively. High F1 score and Kappa values were also obtained.

SIGNIFICANCE

The proposed algorithm has advantages over previously reported approaches during automatic assessment of ECG quality and can thus help to reduce reliance on highly trained professionals when assessing the quality of ECGs.

Genomics of lethal prostate cancer at diagnosis and castration resistance

The genomics of primary prostate cancer differ from those of metastatic castration-resistant prostate cancer (mCRPC). We studied genomic aberrations in primary prostate cancer biopsies from patients who developed mCRPC, also studying matching, same-patient, diagnostic, and mCRPC biopsies following treatment. We profiled 470 treatment-naive prostate cancer diagnostic biopsies and, for 61 cases, mCRPC biopsies, using targeted and low-pass whole-genome sequencing (n = 52). Descriptive statistics were used to summarize mutation and copy number profile. Prevalence was compared using Fisher's exact test. Survival correlations were studied using log-rank test. TP53 (27%) and PTEN (12%) and DDR gene defects (BRCA2 7%; CDK12 5%; ATM 4%) were commonly detected. TP53, BRCA2, and CDK12 mutations were markedly more common than described in the TCGA cohort. Patients with RB1 loss in the primary tumor had a worse prognosis. Among 61 men with matched hormone-naive and mCRPC biopsies, differences were identified in AR, TP53, RB1, and PI3K/AKT mutational status between same-patient samples. In conclusion, the genomics of diagnostic prostatic biopsies acquired from men who develop mCRPC differ from those of the nonlethal primary prostatic cancers. RB1/TP53/AR aberrations are enriched in later stages, but the prevalence of DDR defects in diagnostic samples is similar to mCRPC.

Clinical Impact of Rare and Compound Mutations of Epidermal Growth Factor Receptor in Patients With Non-Small-Cell Lung Cancer

BACKGROUND

Standard therapy of advanced non-small-cell lung cancer harboring an activating mutation in the epidermal growth factor receptor (EGFR) gene is treatment with tyrosine kinase inhibitors (TKI). However, for rare and compound mutations of the EGFR gene, the clinical evidence of TKI therapy is still unclear.

PATIENTS AND METHODS

A total of 2906 lung cancer samples were analyzed for EGFR mutations during routine analysis between 2010 and 2017. The samples have been investigated by Sanger sequencing and since 2014 by next-generation sequencing.

RESULTS

We detected EGFR mutations in 408 specimens (14%). Among these, we found 41 samples with rare and 22 with compound mutations. In these 63 samples, 56 different rare EGFR mutations occurred. Information about the clinical outcome was available for 37. Among those with rare mutations, only one patient harboring the mutation p.G874D had disease that responded to first-generation TKI therapy. In contrast, the disease of all patients with compound mutations responded to first- or second-generation TKI therapy. Furthermore, we collected data on clinical relevance regarding TKI therapy from different databases and from an additional literature search, and only found data for 36 of the 56 detected rare mutations.

CONCLUSION

Information about the clinical outcome of patients with rare and compound EGFR mutations remains limited. At present, second- and third-generation TKIs are available, which may represent new treatment strategies for these patients. Therefore, it is becoming increasingly important to maintain databases concerning rare EGFR mutations.

A CATH domain functional family based approach to identify putative cancer driver genes and driver mutations

Tumour sequencing identifies highly recurrent point mutations in cancer driver genes, but rare functional mutations are hard to distinguish from large numbers of passengers. We developed a novel computational platform applying a multi-modal approach to filter out passengers and more robustly identify putative driver genes. The primary filter identifies enrichment of cancer mutations in CATH functional families (CATH-FunFams) – structurally and functionally coherent sets of evolutionary related domains. Using structural representatives from CATH-FunFams, we subsequently seek enrichment of mutations in 3D and show that these mutation clusters have a very significant tendency to lie close to known functional sites or conserved sites predicted using CATH-FunFams. Our third filter identifies enrichment of putative driver genes in functionally coherent protein network modules confirmed by literature analysis to be cancer associated. Our approach is complementary to other domain enrichment approaches exploiting Pfam families, but benefits from more functionally coherent groupings of domains. Using a set of mutations from 22 cancers we detect 151 putative cancer drivers, of which 79 are not listed in cancer resources and include recently validated cancer associated genes EPHA7, DCC netrin-1 receptor and zinc-finger protein ZNF479.

Newly emergent acquired EGFR exon 18 G724S mutation after resistance of a T790M specific EGFR inhibitor osimertinib in non-small-cell lung cancer: a case report

Background

T790M mutation is well known as the most common mechanism for resistance to the first- and second-generation tyrosine kinase inhibitors (TKIs) for EGFR mutation in non-small-cell lung cancer. Several third-generation EGFR TKIs, such as osimertinib, have been explored and approved for conquering this resistance; however, acquired resistance to osimertinib is evident and the resistance mechanisms remain complex and incompletely explored.

Case presentation

A non-smoking 58-year-old female patient was initially diagnosed with lung adenocarcinoma harboring EGFR exon 19 deletion and clinically responded to initial gefitinib treatment. The patient progressed on gefitinib after >1 year and a T790M mutation was detected in tissue biopsy by next-generation sequencing (NGS). Osimertinib treatment was administrated for several months and an acquired rare EGFR G724S mutation was detected via NGS blood sample after osimertinib resistance.

Conclusion

The specific mechanisms of acquiring drug resistance for EGFR-TKIs have not been fully explored. EGFR G724S mutation might be associated with osimertinib resistance but more studies about the mechanism should be explored.

Analysis of Circulating Cell-Free DNA Identifies Multiclonal Heterogeneity of BRCA2 Reversion Mutations Associated with Resistance to PARP Inhibitors

Approximately 20% of metastatic prostate cancers harbor mutations in genes required for DNA repair by homologous recombination repair (HRR) such as BRCA2 HRR defects confer synthetic lethality to PARP inhibitors (PARPi) such as olaparib and talazoparib. In ovarian or breast cancers, olaparib resistance has been associated with HRR restoration, including by BRCA2 mutation reversion. Whether similar mechanisms operate in prostate cancer, and could be detected in liquid biopsies, is unclear. Here, we identify BRCA2 reversion mutations associated with olaparib and talazoparib resistance in patients with prostate cancer. Analysis of circulating cell-free DNA (cfDNA) reveals reversion mutation heterogeneity not discernable from a single solid-tumor biopsy and potentially allows monitoring for the emergence of PARPi resistance.Significance: The mechanisms of clinical resistance to PARPi in DNA repair-deficient prostate cancer have not been described. Here, we show BRCA2 reversion mutations in patients with prostate cancer with metastatic disease who developed resistance to talazoparib and olaparib. Furthermore, we show that PARPi resistance is highly multiclonal and that cfDNA allows monitoring for PARPi resistance. Cancer Discov; 7(9); 999-1005. ©2017 AACR.See related commentary by Domchek, p. 937See related article by Kondrashova et al., p. 984See related article by Goodall et al., p. 1006This article is highlighted in the In This Issue feature, p. 920.

Analysis of somatic mutations across the kinome reveals loss-of-function mutations in multiple cancer types

In this study we use somatic cancer mutations to identify important functional residues within sets of related genes. We focus on protein kinases, a superfamily of phosphotransferases that share homologous sequences and structural motifs and have many connections to cancer. We develop several statistical tests for identifying Significantly Mutated Positions (SMPs), which are positions in an alignment with mutations that show signs of selection. We apply our methods to 21,917 mutations that map to the alignment of human kinases and identify 23 SMPs. SMPs occur throughout the alignment, with many in the important A-loop region, and others spread between the N and C lobes of the kinase domain. Since mutations are pooled across the superfamily, these positions may be important to many protein kinases. We select eleven mutations from these positions for functional validation. All eleven mutations cause a reduction or loss of function in the affected kinase. The tested mutations are from four genes, including two tumor suppressors (TGFBR1 and CHEK2) and two oncogenes (KDR and ERBB2). They also represent multiple cancer types, and include both recurrent and non-recurrent events. Many of these mutations warrant further investigation as potential cancer drivers.

BRCA2, EGFR, and NTRK mutations in mismatch repair-deficient colorectal cancers with MSH2 or MLH1 mutations

Deficient mismatch repair (MMR) and microsatellite instability (MSI) contribute to ~15% of colorectal cancer (CRCs). We hypothesized MSI leads to mutations in DNA repair proteins including BRCA2 and cancer drivers including EGFR. We analyzed mutations among a discovery cohort of 26 MSI-High (MSI-H) and 558 non-MSI-H CRCs profiled at Caris Life Sciences. Caris-profiled MSI-H CRCs had high mutation rates (50% vs 14% in non-MSI-H, P < 0.0001) in BRCA2. Of 1104 profiled CRCs from a second cohort (COSMIC), MSH2/MLH1-mutant CRCs showed higher mutation rates in BRCA2 compared to non-MSH2/MLH1-mutant tumors (38% vs 6%, P < 0.0000001). BRCA2 mutations in MSH2/MLH1-mutant CRCs included 75 unique mutations not known to occur in breast or pancreatic cancer per COSMIC v73. Only 5 deleterious BRCA2 mutations in CRC were previously reported in the BIC database as germ-line mutations in breast cancer. Some BRCA2 mutations were predicted to disrupt interactions with partner proteins DSS1 and RAD51. Some CRCs harbored multiple BRCA2 mutations. EGFR was mutated in 45.5% of MSH2/MLH1-mutant and 6.5% of non-MSH2/MLH1-mutant tumors (P < 0.0000001). Approximately 15% of EGFR mutations found may be actionable through TKI therapy, including N700D, G719D, T725M, T790M, and E884K. NTRK gene mutations were identified in MSH2/MLH1-mutant CRC including NTRK1 I699V, NTRK2 P716S, and NTRK3 R745L. Our findings have clinical relevance regarding therapeutic targeting of BRCA2 vulnerabilities, EGFR mutations or other identified oncogenic drivers such as NTRK in MSH2/MLH1-mutant CRCs or other tumors with mismatch repair deficiency.

Analysis of Circulating Cell-Free DNA Identifies Multiclonal Heterogeneity of BRCA2 Reversion Mutations Associated with Resistance to PARP Inhibitors

Approximately 20% of metastatic prostate cancers harbor mutations in genes required for DNA repair by homologous recombination repair (HRR) such as BRCA2 HRR defects confer synthetic lethality to PARP inhibitors (PARPi) such as olaparib and talazoparib. In ovarian or breast cancers, olaparib resistance has been associated with HRR restoration, including by BRCA2 mutation reversion. Whether similar mechanisms operate in prostate cancer, and could be detected in liquid biopsies, is unclear. Here, we identify BRCA2 reversion mutations associated with olaparib and talazoparib resistance in patients with prostate cancer. Analysis of circulating cell-free DNA (cfDNA) reveals reversion mutation heterogeneity not discernable from a single solid-tumor biopsy and potentially allows monitoring for the emergence of PARPi resistance.Significance: The mechanisms of clinical resistance to PARPi in DNA repair-deficient prostate cancer have not been described. Here, we show BRCA2 reversion mutations in patients with prostate cancer with metastatic disease who developed resistance to talazoparib and olaparib. Furthermore, we show that PARPi resistance is highly multiclonal and that cfDNA allows monitoring for PARPi resistance. Cancer Discov; 7(9); 999-1005. ©2017 AACR.See related commentary by Domchek, p. 937See related article by Kondrashova et al., p. 984See related article by Goodall et al., p. 1006This article is highlighted in the In This Issue feature, p. 920.

Predicting phenotype from genotype: Improving accuracy through more robust experimental and computational modeling

Computational prediction yields efficient and scalable initial assessments of how variants of unknown significance may affect human health. However, when discrepancies between these predictions and direct experimental measurements of functional impact arise, inaccurate computational predictions are frequently assumed as the source. Here, we present a methodological analysis indicating that shortcomings in both computational and biological data can contribute to these disagreements. We demonstrate that incomplete assaying of multifunctional proteins can affect the strength of correlations between prediction and experiments; a variant's full impact on function is better quantified by considering multiple assays that probe an ensemble of protein functions. Additionally, many variants predictions are sensitive to protein alignment construction and can be customized to maximize relevance of predictions to a specific experimental question. We conclude that inconsistencies between computation and experiment can often be attributed to the fact that they do not test identical hypotheses. Aligning the design of the computational input with the design of the experimental output will require cooperation between computational and biological scientists, but will also lead to improved estimations of computational prediction accuracy and a better understanding of the genotype–phenotype relationship.

Genomic Characterization of Primary Invasive Lobular Breast Cancer

Purpose

Invasive lobular breast cancer (ILBC) is the second most common histologic subtype after invasive ductal breast cancer (IDBC). Despite clinical and pathologic differences, ILBC is still treated as IDBC. We aimed to identify genomic alterations in ILBC with potential clinical implications.

Methods

From an initial 630 ILBC primary tumors, we interrogated oncogenic substitutions and insertions and deletions of 360 cancer genes and genome-wide copy number aberrations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinicopathologic and outcome features.

Results

Besides the high mutation frequency of CDH1 in 65% of tumors, alterations in one of the three key genes of the phosphatidylinositol 3-kinase pathway, PIK3CA, PTEN, and AKT1, were present in more than one-half of the cases. HER2 and HER3 were mutated in 5.1% and 3.6% of the tumors, with most of these mutations having a proven role in activating the human epidermal growth factor receptor/ERBB pathway. Mutations in FOXA1 and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than in IDBC. The histologic diversity of ILBC was associated with specific alterations, such as enrichment for HER2 mutations in the mixed, nonclassic, and ESR1 gains in the solid subtype. Survival analyses revealed that chromosome 1q and 11p gains showed independent prognostic value in ILBC and that HER2 and AKT1 mutations were associated with increased risk of early relapse.

Conclusion

This study demonstrates that we can now begin to individualize the treatment of ILBC, with HER2, HER3, and AKT1 mutations representing high-prevalence therapeutic targets and FOXA1 mutations and ESR1 gains deserving urgent dedicated clinical investigation, especially in the context of endocrine treatment.

Kinase regulation by hydrophobic spine assembly in cancer

A new model of kinase regulation based on the assembly of hydrophobic spines has been proposed. Changes in their positions can explain the mechanism of kinase activation. Here, we examined mutations in human cancer for clues about the regulation of the hydrophobic spines by focusing initially on mutations to Phe. We identified a selected number of Phe mutations in a small group of kinases that included BRAF, ABL1, and the epidermal growth factor receptor. Testing some of these mutations in BRAF, we found that one of the mutations impaired ATP binding and catalytic activity but promoted noncatalytic allosteric functions. Other Phe mutations functioned to promote constitutive catalytic activity. One of these mutations revealed a previously underappreciated hydrophobic surface that functions to position the dynamic regulatory αC-helix. This supports the key role of the C-helix as a signal integration motif for coordinating multiple elements of the kinase to create an active conformation. The importance of the hydrophobic space around the αC-helix was further tested by studying a V600F mutant, which was constitutively active in the absence of the negative charge that is associated with the common V600E mutation. Many hydrophobic mutations strategically localized along the C-helix can thus drive kinase activation.