Computational prediction of MHC anchor locations guides neoantigen identification and prioritization.

Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient's specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.

Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer.

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

Personalized ctDNA micro-panels can monitor and predict clinical outcomes for patients with triple-negative breast cancer.

Circulating tumor DNA (ctDNA) in peripheral blood has been used to predict prognosis and therapeutic response for triple-negative breast cancer (TNBC) patients. However, previous approaches typically use large comprehensive panels of genes commonly mutated across all breast cancers. Given the reduction in sequencing costs and decreased turnaround times associated with panel generation, the objective of this study was to assess the use of custom micro-panels for tracking disease and predicting clinical outcomes for patients with TNBC. Paired tumor-normal samples from patients with TNBC were obtained at diagnosis (T0) and whole exome sequencing (WES) was performed to identify somatic variants associated with individual tumors. Custom micro-panels of 4-6 variants were created for each individual enrolled in the study. Peripheral blood was obtained at baseline, during Cycle 1 Day 3, at time of surgery, and in 3-6 month intervals after surgery to assess variant allele fraction (VAF) at different timepoints during disease course. The VAF was compared to clinical outcomes to evaluate the ability of custom micro-panels to predict pathological response, disease-free intervals, and patient relapse. A cohort of 50 individuals were evaluated for up to 48 months post-diagnosis of TNBC. In total, there were 33 patients who did not achieve pathological complete response (pCR) and seven patients developed clinical relapse. For all patients who developed clinical relapse and had peripheral blood obtained ≤ 6 months prior to relapse (n = 4), the custom ctDNA micro-panels identified molecular relapse at an average of 4.3 months prior to clinical relapse. The custom ctDNA panel results were moderately associated with pCR such that during disease monitoring, only 11% of patients with pCR had a molecular relapse, whereas 47% of patients without pCR had a molecular relapse (Chi-Square; p-value = 0.10). In this study, we show that a custom micro-panel of 4-6 markers can be effectively used to predict outcomes and monitor remission for patients with TNBC. These custom micro-panels show high sensitivity for detecting molecular relapse in advance of clinical relapse. The use of these panels could improve patient outcomes through early detection of relapse with preemptive intervention prior to symptom onset.

Characterization of the Genomic and Immunologic Diversity of Malignant Brain Tumors through Multisector Analysis.

Despite some success in secondary brain metastases, targeted or immune-based therapies have shown limited efficacy against primary brain malignancies such as glioblastoma (GBM). Although the intratumoral heterogeneity of GBM is implicated in treatment resistance, it remains unclear whether this diversity is observed within brain metastases and to what extent cancer cell-intrinsic heterogeneity sculpts the local immune microenvironment. Here, we profiled the immunogenomic state of 93 spatially distinct regions from 30 malignant brain tumors through whole-exome, RNA, and T-cell receptor sequencing. Our analyses identified differences between primary and secondary malignancies, with gliomas displaying more spatial heterogeneity at the genomic and neoantigen levels. In addition, this spatial diversity was recapitulated in the distribution of T-cell clones in which some gliomas harbored highly expanded but spatially restricted clonotypes. This study defines the immunogenomic landscape across a cohort of malignant brain tumors and contains implications for the design of targeted and immune-based therapies against intracranial malignancies. SIGNIFICANCE: This study describes the impact of spatial heterogeneity on genomic and immunologic characteristics of gliomas and brain metastases. The results suggest that gliomas harbor significantly greater intratumoral heterogeneity of genomic alterations, neoantigens, and T-cell clones than brain metastases, indicating the importance of multisector analysis for clinical or translational studies.This article is highlighted in the In This Issue feature, p. 1.

Immunogenomic profiling and pathological response results from a clinical trial of docetaxel and carboplatin in triple-negative breast cancer.

PURPOSE: Patients with triple-negative breast cancer (TNBC) who do not achieve pathological complete response (pCR) following neoadjuvant chemotherapy have a high risk of recurrence and death. Molecular characterization may identify patients unlikely to achieve pCR. This neoadjuvant trial was conducted to determine the pCR rate with docetaxel and carboplatin and to identify molecular alterations and/or immune gene signatures predicting pCR. EXPERIMENTAL DESIGN: Patients with clinical stages II/III TNBC received 6 cycles of docetaxel and carboplatin. The primary objective was to determine if neoadjuvant docetaxel and carboplatin would increase the pCR rate in TNBC compared to historical expectations. We performed whole-exome sequencing (WES) and immune profiling on pre-treatment tumor samples to identify alterations that may predict pCR. Thirteen matching on-treatment samples were also analyzed to assess changes in molecular profiles. RESULTS: Fifty-eight of 127 (45.7%) patients achieved pCR. There was a non-significant trend toward higher mutation burden for patients with residual cancer burden (RCB) 0/I versus RCB II/III (median 80 versus 68 variants, p 0.88). TP53 was the most frequently mutated gene, observed in 85.7% of tumors. EGFR, RB1, RAD51AP2, SDK2, L1CAM, KPRP, PCDHA1, CACNA1S, CFAP58, COL22A1, and COL4A5 mutations were observed almost exclusively in pre-treatment samples from patients who achieved pCR. Seven mutations in PCDHA1 were observed in pre-treatment samples from patients who did not achieve pCR. Several immune gene signatures including IDO1, PD-L1, interferon gamma signaling, CTLA4, cytotoxicity, tumor inflammation signature, inflammatory chemokines, cytotoxic cells, lymphoid, PD-L2, exhausted CD8, Tregs, and immunoproteasome were upregulated in pre-treatment samples from patients who achieved pCR. CONCLUSION: Neoadjuvant docetaxel and carboplatin resulted in a pCR of 45.7%. WES and immune profiling differentiated patients with and without pCR. TRIAL REGISTRATION: Clinical trial information: NCT02124902, Registered 24 April 2014 & NCT02547987, Registered 10 September 2015.

Splicing factor SF3B1 promotes endometrial cancer progression via regulating KSR2 RNA maturation.

Although endometrial cancer is the most common cancer of the female reproductive tract, we have little understanding of what controls endometrial cancer beyond the transcriptional effects of steroid hormones such as estrogen. As a result, we have limited therapeutic options for the ~62,000 women diagnosed with endometrial cancer each year in the United States. Here, in an attempt to identify new prognostic and therapeutic targets, we focused on a new area for this cancer-alternative mRNA splicing-and investigated whether splicing factor, SF3B1, plays an important role in endometrial cancer pathogenesis. Using a tissue microarray, we found that human endometrial tumors expressed more SF3B1 protein than non-cancerous tissues. Furthermore, SF3B1 knockdown reduced in vitro proliferation, migration, and invasion of the endometrial cancer cell lines Ishikawa and AN3CA. Similarly, the SF3B1 inhibitor, Pladienolide-B (PLAD-B), reduced the Ishikawa and AN3CA cell proliferation and invasion in vitro. Moreover, PLAD-B reduced tumor growth in an orthotopic endometrial cancer mouse model. Using RNA-Seq approach, we identified ~2000 differentially expressed genes (DEGs) with SF3B1 knockdown in endometrial cancer cells. Additionally, alternative splicing (AS) events analysis revealed that SF3B1 depletion led to alteration in multiple categories of AS events including alternative exon skipping (ES), transcript start site usage (TSS), and transcript termination site (TTS) usage. Subsequently, bioinformatics analysis showed KSR2 as a potential candidate for SF3B1-mediated functions in endometrial cancer. Specifically, loss of SF3B1 led to decrease in KSR2 expression, owing to reduced maturation of KSR2 pre-mRNA to a mature RNA. Importantly, we found rescuing the KSR2 expression with SF3B1 knockdown partially restored the cell growth of endometrial cancer cells. Taken together, our data suggest that SF3B1 plays a crucial oncogenic role in the tumorigenesis of endometrial cancer and hence may support the development of SF3B1 inhibitors to treat this disease.

Working Collaboratively: Outcomes of Geriatrician Input in Older Patients Undergoing Emergency Laparotomy in a District General Hospital.

With the increasing median age of survival in the UK, there is an increased burden on the provision of medical and surgical care to the population. The 2010 National Confidential Enquiry into Patient Outcome and Death report, "An Age Old Problem," emphasizes the early involvement of surgical and geriatric consultant input to improve perioperative care in older patients. This study describes the development of a Geriatric Surgical Liaison Service aimed at providing consultant-led geriatrician support to improve the outcomes of older patients undergoing Emergency Laparotomy (EL). The primary outcome is the reduction in length of stay (LOS) compared to baseline data prior to geriatrician involvement. The service was designed to include one clinical session involving a consultant geriatrician and two and a half days with a junior doctor in a week. Data was collected prospectively from February 2018 till July 2018 for surgical patients aged ≥ 70 years, who underwent EL, had an inpatient stay of more than seven days, and who were diagnosed with delirium or incurred inpatient falls (intervention group). Baseline data, prior to geriatrician involvement, were collected retrospectively for EL patients aged ≥ 70 years from December 2015 until May 2016. Length of stay and 30-day mortality were also compared between the two cohorts undergoing EL. A total of 69 patients were included in the intervention group; 45 patients underwent EL and their mean LOS was 17.5 days, which was reduced from 22.5 days prior to geriatrician involvement (n=57). There was no difference in median length of stay and 30-day mortality between the retrospective baseline group and the intervention groups. In the intervention group, 8.5% of patients had a new medical diagnosis and 26.8% of patients were offered follow-ups. Although statistically not significant (p=0.40), a shorter stay in hospital by five days can potentially have a positive impact on patient outcomes by reducing psychosocial, cognitive, and functional deconditioning. This would also improve patient flow, release capacity, and waiting times and would be of benefit to the financially strained National Health Service (NHS). Overall, our study suggests that a collaborative, consultant-led geriatric service can improve the management of older surgical patients by potentially reducing length of stay, identifying high-risk patients, and facilitating early and appropriate specialty input alongside adequate and required outpatient follow-up.

Best practices for bioinformatic characterization of neoantigens for clinical utility.

Neoantigens are newly formed peptides created from somatic mutations that are capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens and to create personalized immunotherapies for cancer treatment. To create a personalized cancer vaccine, neoantigens must be computationally predicted from matched tumor-normal sequencing data, and then ranked according to their predicted capability in stimulating a T cell response. This candidate neoantigen prediction process involves multiple steps, including somatic mutation identification, HLA typing, peptide processing, and peptide-MHC binding prediction. The general workflow has been utilized for many preclinical and clinical trials, but there is no current consensus approach and few established best practices. In this article, we review recent discoveries, summarize the available computational tools, and provide analysis considerations for each step, including neoantigen prediction, prioritization, delivery, and validation methods. In addition to reviewing the current state of neoantigen analysis, we provide practical guidance, specific recommendations, and extensive discussion of critical concepts and points of confusion in the practice of neoantigen characterization for clinical use. Finally, we outline necessary areas of development, including the need to improve HLA class II typing accuracy, to expand software support for diverse neoantigen sources, and to incorporate clinical response data to improve neoantigen prediction algorithms. The ultimate goal of neoantigen characterization workflows is to create personalized vaccines that improve patient outcomes in diverse cancer types.

Bacteria-to-Human Protein Networks Reveal Origins of Endogenous DNA Damage.

DNA damage provokes mutations and cancer and results from external carcinogens or endogenous cellular processes. However, the intrinsic instigators of endogenous DNA damage are poorly understood. Here, we identify proteins that promote endogenous DNA damage when overproduced: the DNA "damage-up" proteins (DDPs). We discover a large network of DDPs in Escherichia coli and deconvolute them into six function clusters, demonstrating DDP mechanisms in three: reactive oxygen increase by transmembrane transporters, chromosome loss by replisome binding, and replication stalling by transcription factors. Their 284 human homologs are over-represented among known cancer drivers, and their RNAs in tumors predict heavy mutagenesis and a poor prognosis. Half of the tested human homologs promote DNA damage and mutation when overproduced in human cells, with DNA damage-elevating mechanisms like those in E. coli. Our work identifies networks of DDPs that provoke endogenous DNA damage and may reveal DNA damage-associated functions of many human known and newly implicated cancer-promoting proteins.

Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples.

PURPOSE: Following automated variant calling, manual review of aligned read sequences is required to identify a high-quality list of somatic variants. Despite widespread use in analyzing sequence data, methods to standardize manual review have not been described, resulting in high inter- and intralab variability. METHODS: This manual review standard operating procedure (SOP) consists of methods to annotate variants with four different calls and 19 tags. The calls indicate a reviewer's confidence in each variant and the tags indicate commonly observed sequencing patterns and artifacts that inform the manual review call. Four individuals were asked to classify variants prior to, and after, reading the SOP and accuracy was assessed by comparing reviewer calls with orthogonal validation sequencing. RESULTS: After reading the SOP, average accuracy in somatic variant identification increased by 16.7% (p value = 0.0298) and average interreviewer agreement increased by 12.7% (p value < 0.001). Manual review conducted after reading the SOP did not significantly increase reviewer time. CONCLUSION: This SOP supports and enhances manual somatic variant detection by improving reviewer accuracy while reducing the interreviewer variability for variant calling and annotation.

The Small RNA GcvB Promotes Mutagenic Break Repair by Opposing the Membrane Stress Response.

Microbes and human cells possess mechanisms of mutagenesis activated by stress responses. Stress-inducible mutagenesis mechanisms may provide important models for mutagenesis that drives host-pathogen interactions, antibiotic resistance, and possibly much of evolution generally. In Escherichia coli, repair of DNA double-strand breaks is switched to a mutagenic mode, using error-prone DNA polymerases, via the SOS DNA damage and general (σS) stress responses. We investigated small RNA (sRNA) clients of Hfq, an RNA chaperone that promotes mutagenic break repair (MBR), and found that GcvB promotes MBR by allowing a robust σS response, achieved via opposing the membrane stress (σE) response. Cells that lack gcvB were MBR deficient and displayed reduced σS-dependent transcription but not reduced σS protein levels. The defects in MBR and σS-dependent transcription in ΔgcvB cells were alleviated by artificially increasing σS levels, implying that GcvB promotes mutagenesis by allowing a normal σS response. ΔgcvB cells were highly induced for the σE response, and blocking σE response induction restored both mutagenesis and σS-promoted transcription. We suggest that GcvB may promote the σS response and mutagenesis indirectly, by promoting membrane integrity, which keeps σE levels lower. At high levels, σE might outcompete σS for binding RNA polymerase and so reduce the σS response and mutagenesis. The data show the delicate balance of stress response modulation of mutagenesis. IMPORTANCE: Mutagenesis mechanisms upregulated by stress responses promote de novo antibiotic resistance and cross-resistance in bacteria, antifungal drug resistance in yeasts, and genome instability in cancer cells under hypoxic stress. This paper describes the role of a small RNA (sRNA) in promoting a stress-inducible-mutagenesis mechanism, mutagenic DNA break repair in Escherichia coli The roles of many sRNAs in E. coli remain unknown. This study shows that ΔgcvB cells, which lack the GcvB sRNA, display a hyperactivated membrane stress response and reduced general stress response, possibly because of sigma factor competition for RNA polymerase. This results in a mutagenic break repair defect. The data illuminate a function of GcvB sRNA in opposing the membrane stress response, and thus indirectly upregulating mutagenesis.

Holliday junction trap shows how cells use recombination and a junction-guardian role of RecQ helicase.

DNA repair by homologous recombination (HR) underpins cell survival and fuels genome instability, cancer, and evolution. However, the main kinds and sources of DNA damage repaired by HR in somatic cells and the roles of important HR proteins remain elusive. We present engineered proteins that trap, map, and quantify Holliday junctions (HJs), a central DNA intermediate in HR, based on catalytically deficient mutant RuvC protein of Escherichia coli. We use RuvCDefGFP (RDG) to map genomic footprints of HR at defined DNA breaks in E. coli and demonstrate genome-scale directionality of double-strand break (DSB) repair along the chromosome. Unexpectedly, most spontaneous HR-HJ foci are instigated, not by DSBs, but rather by single-stranded DNA damage generated by replication. We show that RecQ, the E. coli ortholog of five human cancer proteins, nonredundantly promotes HR-HJ formation in single cells and, in a novel junction-guardian role, also prevents apparent non-HR-HJs promoted by RecA overproduction. We propose that one or more human RecQ orthologs may act similarly in human cancers overexpressing the RecA ortholog RAD51 and find that cancer genome expression data implicate the orthologs BLM and RECQL4 in conjunction with EME1 and GEN1 as probable HJ reducers in such cancers. Our results support RecA-overproducing E. coli as a model of the many human tumors with up-regulated RAD51 and provide the first glimpses of important, previously elusive reaction intermediates in DNA replication and repair in single living cells.