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Based on the success of cancer immunotherapy, personalized cancer vaccines have emerged as a leading oncology treatment. Antigen presentation on MHC class I (MHC-I) is crucial for the adaptive immune response to cancer cells, necessitating highly predictive computational methods to model this phenomenon. Here, we introduce HLApollo, a transformer-based model for peptide-MHC-I (pMHC-I) presentation prediction, leveraging the language of peptides, MHC, and source proteins. HLApollo provides end-to-end treatment of MHC-I sequences and deconvolution of multi-allelic data, using a negative-set switching strategy to mitigate misassigned negatives in unlabelled ligandome data. HLApollo shows a 12.65% increase in average precision (AP) on ligandome data and a 4.1% AP increase on immunogenicity test data compared to next-best models. Incorporating protein features from protein language models yields further gains and reduces the need for gene expression measurements. Guided by clinical use, we demonstrate pan-allelic generalization which effectively captures rare alleles in underrepresented ancestries., Competing Interests: Competing interests: The authors of this study are or were employees of Genentech Inc. at the time this work was done. The architecture of the deep learning method described here is related to a US patent filing (US-20220122690-A1) with K.L., N.L., W.J.T, Q.B., L.D., and S.J. as inventors., (© 2024. The Author(s).)

Most colorectal (CRC) tumors are dependent on EGFR/KRAS/BRAF/MAPK signaling activation. ARID1A is an epigenetic regulator mutated in approximately 5% of non-hypermutated CRC tumors. Here we show that anti-EGFR but not anti-VEGF treatment enriches for emerging ARID1A mutations in CRC patients. In addition, we find that patients with ARID1A mutations, at baseline, are associated with worse outcome when treated with cetuximab- but not bevacizumab-containing therapies; thus, this suggests that ARID1A mutations may provide both an acquired and intrinsic mechanism of resistance to anti-EGFR therapies. We find that, ARID1A and EGFR-pathway genetic alterations are mutually exclusive across lung and colorectal cancers, further supporting a functional connection between these pathways. Our results not only suggest that ARID1A could be potentially used as a predictive biomarker for cetuximab treatment decisions but also provide a rationale for exploring therapeutic MAPK inhibition in an unexpected but genetically defined segment of CRC patients., (© 2022. The Author(s).)

Many cancer patients report the use of supplements and herbal medicines but may not always disclose their use to their health-care team. Along with potential interactions, these therapies may also affect outcomes of treatment. During JADPRO Live Virtual 2021, Roberta Bourgon, ND, emphasized the importance of opening a dialogue with patients regarding complementary and alternative medicine and guiding patients in making appropriate choices in their treatment., Competing Interests: The presenter had no conflicts of interest to disclose., (© 2022 Harborside™.)

Background: Colorectal cancer (CRC) is a leading cause of cancer-related deaths, with a 5% 5-year survival rate for metastatic disease, yet with limited therapeutic advancements due to insufficient understanding of and inability to accurately capture high-risk CRC patients who are most likely to recur. We aimed to improve high-risk classification by identifying biological pathways associated with outcome in adjuvant stage II/III CRC., Methods and Findings: We included 1062 patients with stage III or high-risk stage II colon carcinoma from the prospective three-arm randomized phase 3 AVANT trial, and performed expression profiling to identify a prognostic signature. Data from validation cohort GSE39582, The Cancer Genome Atlas, and cell lines were used to further validate the prognostic biology. Our retrospective analysis of the adjuvant AVANT trial uncovered a prognostic signature capturing three biological functions-stromal, proliferative and immune-that outperformed the Consensus Molecular Subtypes (CMS) and recurrence prediction signatures like Oncotype Dx in an independent cohort. Importantly, within the immune component, high granzyme B (GZMB) expression had a significant prognostic impact while other individual T-effector genes were less or not prognostic. In addition, we found GZMB to be endogenously expressed in CMS2 tumor cells and to be prognostic in a T cell independent fashion. A limitation of our study is that these results, although robust and derived from a large dataset, still need to be clinically validated in a prospective study., Conclusions: This work furthers our understanding of the underlying biology that propagates stage II/III CRC disease progression and provides scientific rationale for future high-risk stratification and targeted treatment evaluation in biomarker defined subpopulations of resectable high-risk CRC. Our results also shed light on an alternative GZMB source with context-specific implications on the disease's unique biology., Competing Interests: All authors were employees of, and may have been shareholders of, Genentech/Roche at the time this work was completed. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Individualized neoantigen-specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. It is assumed that clonal neoantigens are preferred targets for immunotherapy, but the distributions of clonal neoantigens are not well characterized across cancer types., Methods: We combined multiregion sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients in order to characterize their globally clonal neoantigen content and factors that would impact neoantigen targeting., Results: Branching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. In colorectal, renal, and bladder cancer, most tumors had few globally clonal neoantigens. Prioritizing mutations with higher purity-adjusted and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases., Conclusions: We show that tumor type, multilesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection, and may also be important factors to consider in the development of biomarker strategies., Competing Interests: Competing interests: The authors from Genentech are employed by and stockholders of Genentech, Inc., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Distinct T cell infiltration patterns, i.e., immune infiltrated, excluded, and desert, result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these tumor immune phenotypes remain elusive. Here, we provide a high-resolution dissection of the entire tumor ecosystem through single-cell RNA-sequencing analysis of 15 ovarian tumors. Immune-desert tumors are characterized by unique tumor cell-intrinsic features, including metabolic pathways and low antigen presentation, and an enrichment of monocytes and immature macrophages. Immune-infiltrated and -excluded tumors differ markedly in their T cell composition and fibroblast subsets. Furthermore, our study reveals chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumor cell-T cell cross talk via CXCL16-CXCR6 and stromal-immune cell cross talk via CXCL12/14-CXCR4. Our data highlight potential molecular mechanisms that shape the tumor immune phenotypes and may inform therapeutic strategies to improve clinical benefit from cancer immunotherapies., Competing Interests: Declaration of interests M.H., M.D., S.L., Y.G., S.K., A.A.L., S.K., J.L.M.R., X.W., J.G., O.M., S.J.T., R.B., A.D., and Y.W. are Genentech/Roche employees. S.L., Y.G., S.K., A.L., S.K., J.L.M.R., X.W., J.G., O.M., S.J.T., R.B., A.D., and Y.W. hold Roche stocks., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Fibroblasts are non-haematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and have key roles in fibrosis, cancer, autoimmunity and wound healing 1 . Recent studies have described fibroblast heterogeneity within individual tissues 1 . However, the field lacks a characterization of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here we constructed fibroblast atlases by integrating single-cell transcriptomic data from about 230,000 fibroblasts across 17 tissues, 50 datasets, 11 disease states and 2 species. Mouse fibroblast atlases and a Dpt IRESCreERT2 knock-in mouse identified two universal fibroblast transcriptional subtypes across tissues. Our analysis suggests that these cells can serve as a reservoir that can yield specialized fibroblasts across a broad range of steady-state tissues and activated fibroblasts in disease. Comparison to an atlas of human fibroblasts from perturbed states showed that fibroblast transcriptional states are conserved between mice and humans, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In summary, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution has identified key organizing principles of the fibroblast lineage in health and disease.

Many cancers evade immune rejection by suppressing major histocompatibility class I (MHC-I) antigen processing and presentation (AgPP). Such cancers do not respond to immune checkpoint inhibitor therapies (ICIT) such as PD-1/PD-L1 [PD-(L)1] blockade. Certain chemotherapeutic drugs augment tumor control by PD-(L)1 inhibitors through potentiation of T-cell priming but whether and how chemotherapy enhances MHC-I-dependent cancer cell recognition by cytotoxic T cells (CTLs) is not entirely clear. We now show that the lysine acetyl transferases p300/CREB binding protein (CBP) control MHC-I AgPPM expression and neoantigen amounts in human cancers. Moreover, we found that two distinct DNA damaging drugs, the platinoid oxaliplatin and the topoisomerase inhibitor mitoxantrone, strongly up-regulate MHC-I AgPP in a manner dependent on activation of nuclear factor kappa B (NF-κB), p300/CBP, and other transcription factors, but independently of autocrine IFNγ signaling. Accordingly, NF-κB and p300 ablations prevent chemotherapy-induced MHC-I AgPP and abrogate rejection of low MHC-I-expressing tumors by reinvigorated CD8 + CTLs. Drugs like oxaliplatin and mitoxantrone may be used to overcome resistance to PD-(L)1 inhibitors in tumors that had "epigenetically down-regulated," but had not permanently lost MHC-I AgPP activity., Competing Interests: Competing interest statement: I.M., J.R.L., R.B., Q.T.P. and G.H. are employees of Genentech.

Background: We aimed to develop a gene expression-based prognostic signature for isocitrate dehydrogenase (IDH) wild-type glioblastoma using clinical trial datasets representative of glioblastoma clinical trial populations., Methods: Samples were collected from newly diagnosed patients with IDH wild-type glioblastoma in the ARTE, TAMIGA, EORTC 26101 (referred to as "ATE"), AVAglio, and GLARIUS trials, or treated at UCLA. Transcriptional profiling was achieved with the NanoString gene expression platform. To identify genes prognostic for overall survival (OS), we built an elastic net penalized Cox proportional hazards regression model using the discovery ATE dataset. For validation in independent datasets (AVAglio, GLARIUS, UCLA), we combined elastic net-selected genes into a robust z-score signature (ATE score) to overcome gene expression platform differences between discovery and validation cohorts., Results: NanoString data were available from 512 patients in the ATE dataset. Elastic net identified a prognostic signature of 9 genes (CHEK1, GPR17, IGF2BP3, MGMT, MTHFD1L, PTRH2, SOX11, S100A9, and TFRC). Translating weighted elastic net scores to the ATE score conserved the prognostic value of the genes. The ATE score was prognostic for OS in the ATE dataset (P < 0.0001), as expected, and in the validation cohorts (AVAglio, P < 0.0001; GLARIUS, P = 0.02; UCLA, P = 0.004). The ATE score remained prognostic following adjustment for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and corticosteroid use at baseline. A positive correlation between ATE score and proneural/proliferative subtypes was observed in patients with MGMT non-methylated promoter status., Conclusions: The ATE score showed prognostic value and may enable clinical trial stratification for IDH wild-type glioblastoma., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what controls the spatial distribution of T cells in the tumour microenvironment is not well understood. Here we couple digital pathology and transcriptome analysis on a large ovarian tumour cohort and develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFβ and activated stroma. Furthermore, we identify TGFβ as an important mediator of T cell exclusion. TGFβ reduces MHC-I expression in ovarian cancer cells in vitro. TGFβ also activates fibroblasts and induces extracellular matrix production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFβ might be a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic. Currently, predicted peptide binding affinity for MHC-I is often the major criterion for prioritizing neoantigens, although little progress has been made toward understanding the precise functional relationship between affinity and immunogenicity. We therefore systematically assessed the immunogenicity of peptides containing single amino acid mutations in mouse tumor models and divided them into two classes of immunogenic mutations. The first comprises mutations at a nonanchor residue, for which we find that the predicted absolute binding affinity is predictive of immunogenicity. The second involves mutations at an anchor residue; here, predicted relative affinity (compared with the WT counterpart) is a better predictor. Incorporating these features into an immunogenicity model significantly improves neoantigen ranking. Importantly, these properties of neoantigens are also predictive in human datasets, suggesting that they can be used to prioritize neoantigens for individualized neoantigen-specific immunotherapies., Competing Interests: Disclosures: Dr. Jhunjhunwala, Dr. Lupardus, and Dr. Delamarre reported a patent to US 20160069895 A1 pending. Dr. Wong reported personal fees from Oncomed Pharmaceuticals, personal fees from Array BioPharma, and personal fees from Pfizer outside the submitted work. Dr. de la Cruz reported "other" from Genentech outside the submitted work. Dr. Mellman reported personal fees from Genentech and grants from Genentech during the conduct of the study. No other disclosures were reported., (© 2020 Capietto et al.)

Despite the resounding clinical success in cancer treatment of antibodies that block the interaction of PD1 with its ligand PDL1 1 , the mechanisms involved remain unknown. A major limitation to understanding the origin and fate of T cells in tumour immunity is the lack of quantitative information on the distribution of individual clonotypes of T cells in patients with cancer. Here, by performing deep single-cell sequencing of RNA and T cell receptors in patients with different types of cancer, we survey the profiles of various populations of T cells and T cell receptors in tumours, normal adjacent tissue, and peripheral blood. We find clear evidence of clonotypic expansion of effector-like T cells not only within the tumour but also in normal adjacent tissue. Patients with gene signatures of such clonotypic expansion respond best to anti-PDL1 therapy. Notably, expanded clonotypes found in the tumour and normal adjacent tissue can also typically be detected in peripheral blood, which suggests a convenient approach to patient identification. Analyses of our data together with several external datasets suggest that intratumoural T cells, especially in responsive patients, are replenished with fresh, non-exhausted replacement cells from sites outside the tumour, suggesting continued activity of the cancer immunity cycle in these patients, the acceleration of which may be associated with clinical response.

Profound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens.

The identification of early breast cancer patients who may benefit from adjuvant chemotherapy has evolved to include assessment of clinicopathologic features such as tumor size and nodal status, as well as several gene-expression profiles for ER-positive, HER2-negative cancers. However, these tools do not reliably identify patients at the greatest risk of recurrence. The mutation and copy-number landscape of triple-negative breast cancer (TNBC) subtypes defined by gene expression is also largely unknown, and elucidation of this landscape may shed light on novel therapeutic opportunities. The USO01062 phase III clinical trial of standard chemotherapy (with or without capecitabine) enrolled a cohort of putatively high-risk patients based on clinical features, yet only observed a 5-year disease-free survival event rate of 11.6%. In order to uncover genomic aberrations associated with recurrence, a targeted next-generation sequencing panel was used to compare tumor specimens from patients who had a recurrence event with a matched set who did not. The somatic mutation and copy-number alteration landscapes of high-risk early breast cancer patients were characterized and alterations associated with relapse were identified. Tumor mutational burden was evaluated but was not prognostic in this study, nor did it correlate with PDL1 or CD8 gene expression. However, TNBC subtypes had substantial genomic heterogeneity with a distinct pattern of genomic alterations and putative underlying driver mutations. IMPLICATIONS: The present study uncovers a compendium of genomic alterations with utility to more precisely identify high-risk patients for adjuvant trials of novel therapeutic agents., (©2018 American Association for Cancer Research.)

Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies. Here we examined tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent (atezolizumab) and identified major determinants of clinical outcome. Response to treatment was associated with CD8 + T-effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden. Lack of response was associated with a signature of transforming growth factor β (TGFβ) signalling in fibroblasts. This occurred particularly in patients with tumours, which showed exclusion of CD8 + T cells from the tumour parenchyma that were instead found in the fibroblast- and collagen-rich peritumoural stroma; a common phenotype among patients with metastatic urothelial cancer. Using a mouse model that recapitulates this immune-excluded phenotype, we found that therapeutic co-administration of TGFβ-blocking and anti-PD-L1 antibodies reduced TGFβ signalling in stromal cells, facilitated T-cell penetration into the centre of tumours, and provoked vigorous anti-tumour immunity and tumour regression. Integration of these three independent biological features provides the best basis for understanding patient outcome in this setting and suggests that TGFβ shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.

As the impact of genetics, genomics, and bioinformatics on drug discovery has been increasingly recognized, this session of the 2018 Pacific Symposium on Biocomputing (PSB) aims to facilitate scientific discussions between academia and pharmaceutical industry on how to best apply genetics, genomics and bioinformatics to enable drug discovery. The selected papers focus on developing and applying computational approaches to understand drug mechanisms of action and develop drug combination strategies, to enable in silico drug screening, and to further delineate disease pathways for target identification and validation.

Circulating tumor DNA (ctDNA) has potential to serve as a biomarker for noninvasive monitoring of treatment response and disease progression. However, broad clinical applicability of ctDNA has been limited by the low sensitivity, throughput, and patient coverage offered by existing ctDNA detection methods. Herein, we report the adaptation and characterization of the microfluidics multiplex PCR sequencing technology for high-throughput and sensitive quantitation of ctDNA. A multiplex PCR preamplification step was developed and incorporated into the microfluidics multiplex PCR sequencing work flow to enable low-input ctDNA analysis with enhanced sensitivity. An empirical bayesian model was developed to characterize both position and substitution-associated system errors specific to this platform and provided a tailored approach to greatly enhance the confidence and accuracy of variant calling for ctDNA analysis. Clinical validation of this platform for ctDNA mutation detection demonstrated an overall sensitivity of 92% and specificity of 100% when using mutation calls in the matched tumor tissues as a benchmark. Finally, we established an early proof of concept of clinical utility of this ctDNA work flow for monitoring disease progression using clinical trial samples. Our novel ctDNA work flow provides a high-throughput and sensitive platform that can be implemented in clinical trials for mutation detection and disease monitoring from plasma ctDNA., (Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Identifying follicular lymphoma (FL) patients with preexisting antitumor immunity will inform precision medicine strategies for novel cancer immunotherapies. Using clinical and genomic data from 249 FL patients, we determined the clinical impact of mutation load and an effector T-cell (T eff ) gene signature as proxies for the likelihood of a functional immune response. The FL mutation load estimate varied between 0 and 33 mutations per Mb (median, 6.6), and 92% of FL patients with a high mutation load had high T eff gene expression ( P = .001). The mutation load was associated with a benefit from rituximab maintenance: FL patients with low mutation loads experienced a profound benefit from rituximab maintenance (hazard ratio [HR], 0.29; 95% confidence interval [CI], 0.15-0.54; P < .001). The T eff gene signature was prognostic as a continuous predictor ( P = .008), and was used to separate FL patients into 2 groups, an "inflamed" subset (T eff -high; n = 74) and an "uninflamed" subset (T eff -low; n = 75), with longer progression-free survival (PFS) in the inflamed FL subset (PFS HR, 0.39; 95% CI, 0.21-0.70; P = .002). Furthermore, the subset of inflamed FL tumors demonstrated high expression of other T-cell signatures and counterregulatory genes, which also correlate with PFS. Mutation load and T eff gene expression may help identify immunologically distinct lymphoma subsets relevant for modern immunotherapies., Competing Interests: Conflict-of-interest disclosure: C.R.B., R.M., R.B., E.A.P., E.S.-G., and J.M.V. are employed by Genentech and are shareholders in F. Hoffman La Roche. G.M.F. is employed by Foundation Medicine. L.X. has received honoraria from Novartis, and G.S. is a consultant for and has received from honoraria from Gilead, Janssen, Celgene, Mundipharma, Roche/Genentech, Amgen, and Novartis. The remaining authors declare no competing financial interests.

Acquired resistance to cancer drug therapies almost always occurs in advanced-stage patients even following a significant response to treatment. In addition to mutational mechanisms, various non-mutational resistance mechanisms have now been recognized. We previously described a chromatin-mediated subpopulation of reversibly drug-tolerant persisters that is dynamically maintained within a wide variety of tumour cell populations. Here we explore a potential role for microRNAs in such transient drug tolerance. Functional screening of 879 human microRNAs reveals miR-371-3p as a potent suppressor of drug tolerance. We identify PRDX6 (peroxiredoxin 6) as a key target of miR-371-3p in establishing drug tolerance by regulating PLA2/PKCα activity and reactive oxygen species. PRDX6 expression is associated with poor prognosis in cancers of multiple tissue origins. These findings implicate miR-371-3p as a suppressor of PRDX6 and suggest that co-targeting of peroxiredoxin 6 or modulating miR-371-3p expression together with targeted cancer therapies may delay or prevent acquired drug resistance.

The use of large-scale genomic and drug response screening of cancer cell lines depends crucially on the reproducibility of results. Here we consider two previously published screens, plus a later critique of these studies. Using independent data, we show that consistency is achievable, and provide a systematic description of the best laboratory and analysis practices for future studies.

TNF superfamily death ligands are expressed on the surface of immune cells and can trigger apoptosis in susceptible cancer cells by engaging cognate death receptors. A recombinant soluble protein comprising the ectodomain of Apo2 ligand/TNF-related apoptosis-inducing ligand (Apo2L/TRAIL) has shown remarkable preclinical anticancer activity but lacked broad efficacy in patients, possibly owing to insufficient exposure or potency. We observed that antibody cross-linking substantially enhanced cytotoxicity of soluble Apo2L/TRAIL against diverse cancer cell lines. Presentation of the ligand on glass-supported lipid bilayers enhanced its ability to drive receptor microclustering and apoptotic signaling. Furthermore, covalent surface attachment of Apo2L/TRAIL onto liposomes--synthetic lipid-bilayer nanospheres--similarly augmented activity. In vivo, liposome-displayed Apo2L/TRAIL achieved markedly better exposure and antitumor activity. Thus, covalent synthetic-membrane attachment of a cell-surface ligand enhances efficacy, increasing therapeutic potential. These findings have translational implications for liposomal approaches as well as for Apo2L/TRAIL and other clinically relevant TNF ligands.

Cell line misidentification, contamination and poor annotation affect scientific reproducibility. Here we outline simple measures to detect or avoid cross-contamination, present a framework for cell line annotation linked to short tandem repeat and single nucleotide polymorphism profiles, and provide a catalogue of synonymous cell lines. This resource will enable our community to eradicate the use of misidentified lines and generate credible cell-based data.

Smoothened (SMO) inhibitors are under clinical investigation for the treatment of several cancers. Vismodegib is approved for the treatment of locally advanced and metastatic basal cell carcinoma (BCC). Most BCC patients experience significant clinical benefit on vismodegib, but some develop resistance. Genomic analysis of tumor biopsies revealed that vismodegib resistance is associated with Hedgehog (Hh) pathway reactivation, predominantly through mutation of the drug target SMO and to a lesser extent through concurrent copy number changes in SUFU and GLI2. SMO mutations either directly impaired drug binding or activated SMO to varying levels. Furthermore, we found evidence for intra-tumor heterogeneity, suggesting that a combination of therapies targeting components at multiple levels of the Hh pathway is required to overcome resistance., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.

Cell lines are the foundation for much of the fundamental research into the mechanisms underlying normal biologic processes and disease mechanisms. It is estimated that 15%-35% of human cell lines are misidentified or contaminated, resulting in a huge waste of resources and publication of false or misleading data. Here we evaluate a panel of 96 single-nucleotide polymorphism (SNP) assays utilizing Fluidigm microfluidics technology for authentication and sex determination of human cell lines. The SNPtrace Panel was tested on 907 human cell lines. Pairwise comparison of these data show the SNPtrace Panel discriminated among identical, related and unrelated pairs of samples with a high degree of confidence, equivalent to short tandem repeat (STR) profiling. We also compared annotated sex calls with those determined by the SNPtrace Panel, STR and Illumina SNP arrays, revealing a high number of male samples are identified as female due to loss of the Y chromosome. Finally we assessed the sensitivity of the SNPtrace Panel to detect intra-human cross-contamination, resulting in detection of as little as 2% contaminating cell population. In conclusion, this study has generated a database of SNP fingerprints for 907 cell lines used in biomedical research and provides a reliable, fast, and economic alternative to STR profiling which can be applied to any human cell line or tissue sample.

Cancer genomes maintain a complex array of somatic alterations required for maintenance and progression of the disease, posing a challenge to identify driver genes among this genetic disorder. Toward this end, we mapped regions of recurrent amplification in a large collection (n=392) of primary human cancers and selected 620 genes whose expression is elevated in tumors. An RNAi loss-of-function screen targeting these genes across a panel of 32 cancer cell lines identified potential driver genes. Subsequent functional assays identified SHMT2, a key enzyme in the serine/glycine synthesis pathway, as necessary for tumor cell survival but insufficient for transformation. The 26S proteasomal subunit, PSMB4, was identified as the first proteasomal subunit with oncogenic properties promoting cancer cell survival and tumor growth in vivo. Elevated expression of SHMT2 and PSMB4 was found to be associated with poor prognosis in human cancer, supporting the development of molecular therapies targeting these genes or components of their pathways., (©2014 American Association for Cancer Research.)

Purpose: Tailoring cancer treatment to tumor molecular characteristics promises to make personalized medicine a reality. However, reliable genetic profiling of archived clinical specimens has been hindered by limited sensitivity and high false-positive rates. Here, we describe a novel methodology, MMP-seq, which enables sensitive and specific high-throughput, high-content genetic profiling in archived clinical samples., Experimental Design: We first validated the technical performance of MMP-seq in 66 cancer cell lines and a Latin square cross-dilution of known somatic mutations. We next characterized the performance of MMP-seq in 17 formalin-fixed paraffin-embedded (FFPE) clinical samples using matched fresh-frozen tissue from the same tumors as benchmarks. To demonstrate the potential clinical utility of our methodology, we profiled FFPE tumor samples from 73 patients with endometrial cancer., Results: We demonstrated that MMP-seq enabled rapid and simultaneous profiling of a panel of 88 cancer genes in 48 samples, and detected variants at frequencies as low as 0.4%. We identified DNA degradation and deamination as the main error sources and developed practical and robust strategies for mitigating these issues, and dramatically reduced the false-positive rate. Applying MMP-seq to a cohort of endometrial tumor samples identified extensive, potentially actionable alterations in the PI3K (phosphoinositide 3-kinase) and RAS pathways, including novel PIK3R1 hotspot mutations that may disrupt negative regulation of PIK3CA., Conclusions: MMP-seq provides a robust solution for comprehensive, reliable, and high-throughput genetic profiling of clinical tumor samples, paving the way for the incorporation of genomic-based testing into clinical investigation and practice., (©2014 AACR.)

Lung cancer remains the primary cause of cancer-related deaths worldwide. Improved tools for early detection and therapeutic stratification would be expected to increase the survival rate for this disease. Alterations in the molecular pathways that drive lung cancer, which include epigenetic modifications, may provide biomarkers to help address this major unmet clinical need. Epigenetic changes, which are defined as heritable changes in gene expression that do not alter the primary DNA sequence, are one of the hallmarks of cancer, and prevalent in all types of cancer. These modifications represent a rich source of biomarkers that have the potential to be implemented in clinical practice. This perspective describes recent advances in the discovery of epigenetic biomarkers in lung cancer, specifically those that result in the methylation of DNA at CpG sites. We discuss one approach for methylation-based biomarker assay development that describes the discovery at a genome-scale level, which addresses some of the practical considerations for design of assays that can be implemented in the clinic. We emphasize that an integrated technological approach will enable the development of clinically useful DNA methylation-based biomarker assays. While this article focuses on current literature and primary research findings in lung cancer, the principles we describe here apply to the discovery and development of epigenetic biomarkers for other types of cancer.

Unlabelled: Connections between disease phenotypes and drug effects can be made by identifying commonalities in the associated patterns of differential gene expression. Searchable databases that record the impacts of chemical or genetic perturbations on the transcriptome--here referred to as 'connectivity maps'--permit discovery of such commonalities. We describe two R packages, gCMAP and gCMAPWeb, which provide a complete framework to construct and query connectivity maps assembled from user-defined collections of differential gene expression data. Microarray or RNAseq data are processed in a standardized way, and results can be interrogated using various well-established gene set enrichment methods. The packages also feature an easy-to-deploy web application that facilitates reproducible research through automatic generation of graphical and tabular reports., Availability and Implementation: The gCMAP and gCMAPWeb R packages are freely available for UNIX, Windows and Mac OS X operating systems at Bioconductor (http://www.bioconductor.org).

Purpose: We sought to identify predictive biomarkers for a novel nicotinamide phosphoribosyltransferase (NAMPT) inhibitor., Experimental Design: We use a NAMPT inhibitor, GNE-617, to evaluate nicotinic acid rescue status in a panel of more than 400 cancer cell lines. Using correlative analysis and RNA interference (RNAi), we identify a specific biomarker for nicotinic acid rescue status. We next determine the mechanism of regulation of expression of the biomarker. Finally, we develop immunohistochemical (IHC) and DNA methylation assays and evaluate cancer tissue for prevalence of the biomarker across indications., Results: Nicotinate phosphoribosyltransferase (NAPRT1) is necessary for nicotinic acid rescue and its expression is the major determinant of rescue status. We demonstrate that NAPRT1 promoter methylation accounts for NAPRT1 deficiency in cancer cells, and NAPRT1 methylation is predictive of rescue status in cancer cell lines. Bisulfite next-generation sequencing mapping of the NAPRT1 promoter identified tumor-specific sites of NAPRT1 DNA methylation and enabled the development of a quantitative methylation-specific PCR (QMSP) assay suitable for use on archival formalin-fixed paraffin-embedded tumor tissue., Conclusions: Tumor-specific promoter hypermethylation of NAPRT1 inactivates one of two NAD salvage pathways, resulting in synthetic lethality with the coadministration of a NAMPT inhibitor. NAPRT1 expression is lost due to promoter hypermethylation in most cancer types evaluated at frequencies ranging from 5% to 65%. NAPRT1-specific immunohistochemical or DNA methylation assays can be used on archival formalin paraffin-embedded cancer tissue to identify patients likely to benefit from coadministration of a Nampt inhibitor and nicotinic acid., (©2013 AACR.)

Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.

Purpose: Non-small cell lung cancers (NSCLC) comprise multiple distinct biologic groups with different prognoses. For example, patients with epithelial-like tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like tumors. Here, we test the hypothesis that epithelial-like NSCLCs can be distinguished from mesenchymal-like NSCLCs on the basis of global DNA methylation patterns., Experimental Design: To determine whether phenotypic subsets of NSCLCs can be defined on the basis of their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative reverse transcriptase PCR and methylation-specific PCR in formalin-fixed biopsies from patients with NSCLC who went on to fail front-line chemotherapy., Results: We show that patterns of methylation divide NSCLCs into epithelial-like and mesenchymal-like subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple differentially methylated regions, including one in ERBB2 and one in ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from patients with NSCLC who went on to fail front-line chemotherapy., Conclusions: Our data show that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used as a platform for predictive biomarker discovery and development., (©2012 AACR.)

Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we present SpeCond, a method to detect condition-specific genes that outperforms alternative approaches. We apply the method to a dataset of 32 human tissues to determine 2,673 specifically expressed genes. An implementation of SpeCond is freely available as a Bioconductor package at http://www.bioconductor.org/packages/release/bioc/html/SpeCond.html.

Background: When mismatches in heteroduplex DNA formed during meiotic recombination are left unrepaired, post-meiotic segregation of the two mismatched alleles occurs during the ensuing round of mitosis. This gives rise to somatic mosaicism in multicellular organisms and leads to unexpected allelic combinations among progeny. Despite its implications for inheritance, post-meiotic segregation has been studied at only a few loci., Results: By genotyping tens of thousands of genetic markers in yeast segregants and their clonal progeny, we analyzed post-meiotic segregation at a genome-wide scale. We show that post-meiotic segregation occurs in close to 10% of recombination events. Although the overall number of markers affected in a single meiosis is small, the rate of post-meiotic segregation is more than five orders of magnitude larger than the base substitution mutation rate. Post-meiotic segregation took place with equal relative frequency in crossovers and non-crossovers, and usually at the edges of gene conversion tracts. Furthermore, post-meiotic segregation tended to occur in markers that are isolated from other heterozygosities and preferentially at polymorphism types that are relatively uncommon in the yeast species., Conclusions: Overall, our survey reveals the genome-wide characteristics of post-meiotic segregation. The results show that post-meiotic segregation is widespread in meiotic recombination and could be a significant determinant of allelic inheritance and allele frequencies at the population level., (© 2011 Mancera et al. licensee BioMed Central Ltd.)

The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics. Here we report the identification of 2,576 somatic mutations across approximately 1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. We found that mutation rates and the sets of mutated genes varied substantially across tumour types and subtypes. Statistical analysis identified 77 significantly mutated genes including protein kinases, G-protein-coupled receptors such as GRM8, BAI3, AGTRL1 (also called APLNR) and LPHN3, and other druggable targets. Integrated analysis of somatic mutations and copy number alterations identified another 35 significantly altered genes including GNAS, indicating an expanded role for galpha subunits in multiple cancer types. Furthermore, our experimental analyses demonstrate the functional roles of mutant GNAO1 (a Galpha subunit) and mutant MAP2K4 (a member of the JNK signalling pathway) in oncogenesis. Our study provides an overview of the mutational spectra across major human cancers and identifies several potential therapeutic targets.

With high-dimensional data, variable-by-variable statistical testing is often used to select variables whose behavior differs across conditions. Such an approach requires adjustment for multiple testing, which can result in low statistical power. A two-stage approach that first filters variables by a criterion independent of the test statistic, and then only tests variables which pass the filter, can provide higher power. We show that use of some filter/test statistics pairs presented in the literature may, however, lead to loss of type I error control. We describe other pairs which avoid this problem. In an application to microarray data, we found that gene-by-gene filtering by overall variance followed by a t-test increased the number of discoveries by 50%. We also show that this particular statistic pair induces a lower bound on fold-change among the set of discoveries. Independent filtering-using filter/test pairs that are independent under the null hypothesis but correlated under the alternative-is a general approach that can substantially increase the efficiency of experiments.