Molecular profiles and urinary biomarkers of upper tract urothelial carcinomas associated with aristolochic acid exposure.

Recurrent upper tract urothelial carcinomas (UTUCs) arise in the context of nephropathy linked to exposure to the herbal carcinogen aristolochic acid (AA). Here we delineated the molecular programs underlying UTUC tumorigenesis in patients from endemic aristolochic acid nephropathy (AAN) regions in Southern Europe. We applied an integrative multiomics analysis of UTUCs, corresponding unaffected tissues and of patient urines. Quantitative microRNA (miRNA) and messenger ribonucleic acid (mRNA) expression profiling, immunohistochemical analysis by tissue microarrays and exome and transcriptome sequencing were performed in UTUC and nontumor tissues. Urinary miRNAs of cases undergoing surgery were profiled before and after tumor resection. Ribonucleic acid (RNA) and protein levels were analyzed using appropriate statistical tests and trend assessment. Dedicated bioinformatic tools were used for analysis of pathways, mutational signatures and result visualization. The results delineate UTUC-specific miRNA:mRNA networks comprising 89 miRNAs associated with 1,862 target mRNAs, involving deregulation of cell cycle, deoxyribonucleic acid (DNA) damage response, DNA repair, bladder cancer, oncogenes, tumor suppressors, chromatin structure regulators and developmental signaling pathways. Key UTUC-specific transcripts were confirmed at the protein level. Exome and transcriptome sequencing of UTUCs revealed AA-specific mutational signature SBS22, with 68% to 76% AA-specific, deleterious mutations propagated at the transcript level, a possible basis for neoantigen formation and immunotherapy targeting. We next identified a signature of UTUC-specific miRNAs consistently more abundant in the patients' urine prior to tumor resection, thereby defining biomarkers of tumor presence. The complex gene regulation programs of AAN-associated UTUC tumors involve regulatory miRNAs prospectively applicable to noninvasive urine-based screening of AAN patients for cancer presence and recurrence.

The International Collaboration for Cancer Classification and Research.

Gaps in the translation of research findings to clinical management have been recognized for decades. They exist for the diagnosis as well as the management of cancer. The international standards for cancer diagnosis are contained within the World Health Organization (WHO) Classification of Tumours, published by the International Agency for Research on Cancer (IARC) and known worldwide as the WHO Blue Books. In addition to their relevance to individual patients, these volumes provide a valuable contribution to cancer research and surveillance, fulfilling an important role in scientific evidence synthesis and international standard setting. However, the multidimensional nature of cancer classification, the way in which the WHO Classification of Tumours is constructed, and the scientific information overload in the field pose important challenges for the translation of research findings to tumour classification and hence cancer diagnosis. To help address these challenges, we have established the International Collaboration for Cancer Classification and Research (IC3 R) to provide a forum for the coordination of efforts in evidence generation, standard setting and best practice recommendations in the field of tumour classification. The first IC3 R meeting, held in Lyon, France, in February 2019, gathered representatives of major institutions involved in tumour classification and related fields to identify and discuss translational challenges in data comparability, standard setting, quality management, evidence evaluation and copyright, as well as to develop a collaborative plan for addressing these challenges.

Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants.

Germline pathogenic variants in TP53 are associated with Li-Fraumeni syndrome, a cancer predisposition disorder inherited in an autosomal dominant pattern associated with a high risk of malignancy, including early-onset breast cancers, sarcomas, adrenocortical carcinomas, and brain tumors. Intense cancer surveillance for individuals with TP53 germline pathogenic variants is associated with reduced cancer-related mortality. Accurate and consistent classification of germline variants across clinical and research laboratories is important to ensure appropriate cancer surveillance recommendations. Here, we describe the work performed by the Clinical Genome Resource TP53 Variant Curation Expert Panel (ClinGen TP53 VCEP) focused on specifying the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification to the TP53 gene. Specifications were developed for 20 ACMG/AMP criteria, while nine were deemed not applicable. The original strength level for the 10 criteria was also adjusted due to current evidence. Use of TP53-specific guidelines and sharing of clinical data among experts and clinical laboratories led to a decrease in variants of uncertain significance from 28% to 12% compared with the original guidelines. The ClinGen TP53 VCEP recommends the use of these TP53-specific ACMG/AMP guidelines as the standard strategy for TP53 germline variant classification.

PVAmpliconFinder: a workflow for the identification of human papillomaviruses from high-throughput amplicon sequencing.

BACKGROUND: The detection of known human papillomaviruses (PVs) from targeted wet-lab approaches has traditionally used PCR-based methods coupled with Sanger sequencing. With the introduction of next-generation sequencing (NGS), these approaches can be revisited to integrate the sequencing power of NGS. Although computational tools have been developed for metagenomic approaches to search for known or novel viruses in NGS data, no appropriate tool is available for the classification and identification of novel viral sequences from data produced by amplicon-based methods. RESULTS: We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify known and potentially new Papillomaviridae sequences from NGS amplicon sequencing with degenerate PV primers. Here, we describe the features of PVAmpliconFinder and its implementation using biological data obtained from amplicon sequencing of human skin swab specimens and oral rinses from healthy individuals. CONCLUSIONS: PVAmpliconFinder identified putative new HPV sequences, including one that was validated by wet-lab experiments. PVAmpliconFinder can be easily modified and applied to other viral families. PVAmpliconFinder addresses a gap by providing a solution for the analysis of NGS amplicon sequencing, increasingly used in clinical research. The PVAmpliconFinder workflow, along with its source code, is freely available on the GitHub platform: https://github.com/IARCbioinfo/PVAmpliconFinder.

Anthropometry, body shape in early-life and risk of premenopausal breast cancer among Latin American women: results from the PRECAMA study.

Cumulating evidence in Caucasian women suggests a positive association between height and premenopausal breast cancer risk and a negative association with overall adiposity; however data from Latin America are scarce. We investigated the associations between excess adiposity, body shape evolution across life, and risk of premenopausal breast cancer among 406 cases (women aged 20-45) and 406 matched population-based controls from Chile, Colombia, Costa Rica, and Mexico. Negative associations between adult adiposity and breast cancer risk were observed in adjusted models (body mass index (BMI): Odds ratio (OR) per 1 kg/m2 = 0.93; 95% confidence interval = 0.89-0.96; waist circumference (WC): OR per 10 cm = 0.81 (0.69-0.96); hip circumference (HC): OR per 10 cm = 0.80 (0.67-0.95)). Height and leg length were not associated with risk. In normal weight women (18.5 ≤ BMI < 25), women with central obesity (WC > 88 cm) had an increased risk compared to women with normal WC (OR = 3.60(1.47-8.79)). Residuals of WC over BMI showed positive associations when adjusted for BMI (OR per 10 cm = 1.38 (0.98-1.94)). Body shape at younger ages and body shape evolution were not associated with risk. No heterogeneity was observed by receptor status. In this population of Latin American premenopausal women, different fat distributions in adulthood were differentially associated with risk of breast cancer.

Project profile: a multicenter study on breast cancer in young women in Latin America (PRECAMA study).

OBJECTIVE: To describe the rationale and the methodology of a multicenter project to study the etiology of breast cancer in young Latin American women. MATERIALS AND METHODS: The International Agency for Research on Cancer has established an international collaborative population-based case-control study in four countries in Latin America: Chile, Colombia, Costa Rica, and Mexico (the PRECAMA study). Standardized methodologies were developed to collect information on reproductive variables, lifestyle, anthropometry, diet, clinical and pathological data, and biological specimens. The study will be extended to other countries in the region. CONCLUSIONS: PRECAMA is unique in its multidisciplinary approach that combines genetics, genomics, and metabolomics with lifestyle factors. Then data generated through this project will be instrumental to identify major risk factors for molecular subtypes of breast cancer in young women, which will be important for pre- vention and targeted screening programs in Latin America.

OBJETIVO: Describir la justificación y la metodología para el establecimiento de un proyecto multicéntrico sobre el cáncer de mama en mujeres jóvenes de América Latina. MATERIAL Y MÉTODOS: La Agencia Internacional para la Investigación del Cáncer (IARC) ha establecido un estudio colaborativo internacional de casos y controles con base poblacional en cuatro países de América Latina: Chile, Colombia, Costa Rica y México (el estudio PRECAMA). Se han desarrollado metodologías estandarizadas para recolectar información sobre variables reproductivas, estilos de vida, antropometría y dieta, datos clínicos y patológicos y muestras biológicas. CONCLUSIONES: PRECAMA es único en su enfoque multidisciplinario. Los datos generados a través de este proyecto serán fundamentales para identificar los principales factores de riesgo del cáncer de mama en mujeres jóvenes. Los hallazgos serán relevantes para la prevención y los programas de detección oportuna en América Latina, con beneficios clínicos inmediatos.

Project profile: a multicenter study on breast cancer in young women in Latin America (PRECAMA study) / Perfil de Proyecto: Un estudio multicéntrico sobre el cáncer de mama en mujeres jóvenes en América Latina (estudio PRECAMA)

Abstract: Objective: To describe the rationale and the methodology of a multicenter project to study the etiology of breast cancer in young Latin American women. Materials and methods: The International Agency for Research on Cancer has established an international collaborative population-based case-control study in four countries in Latin America: Chile, Colombia, Costa Rica, and Mexico (the PRECAMA study). Standardized methodologies were developed to collect information on reproductive variables, lifestyle, anthropometry, diet, clinical and pathological data, and biological specimens. The study will be extended to other countries in the region. Conclusion: PRECAMA is unique in its multidisciplinary approach that combines genetics, genomics, and metabolomics with lifestyle factors. The data generated through this project will be instrumental to identify major risk factors for molecular subtypes of breast cancer in young women, which will be important for prevention and targeted screening programs in Latin America.

Resumen: Objetivo: Describir la justificación y la metodología para el establecimiento de un proyecto multicéntrico sobre el cáncer de mama en mujeres jóvenes de América Latina. Material y métodos: La Agencia Internacional para la Investigación del Cáncer (IARC) ha establecido un estudio colaborativo internacional de casos y controles con base poblacional en cuatro países de América Latina: Chile, Colombia, Costa Rica y México (el estudio PRECAMA). Se han desarrollado metodologías estandarizadas para recolectar información sobre variables reproductivas, estilos de vida, antropometría y dieta, datos clínicos y patológicos y muestras biológicas. Conclusión: PRECAMA es único en su enfoque multidisciplinario. Los datos generados a través de este proyecto serán fundamentales para identificar los principales factores de riesgo del cáncer de mama en mujeres jóvenes. Los hallazgos serán relevantes para la prevención y los programas de detección oportuna en América Latina, con beneficios clínicos inmediatos.

Experimental and pan-cancer genome analyses reveal widespread contribution of acrylamide exposure to carcinogenesis in humans.

Humans are frequently exposed to acrylamide, a probable human carcinogen found in commonplace sources such as most heated starchy foods or tobacco smoke. Prior evidence has shown that acrylamide causes cancer in rodents, yet epidemiological studies conducted to date are limited and, thus far, have yielded inconclusive data on association of human cancers with acrylamide exposure. In this study, we experimentally identify a novel and unique mutational signature imprinted by acrylamide through the effects of its reactive metabolite glycidamide. We next show that the glycidamide mutational signature is found in a full one-third of approximately 1600 tumor genomes corresponding to 19 human tumor types from 14 organs. The highest enrichment of the glycidamide signature was observed in the cancers of the lung (88% of the interrogated tumors), liver (73%), kidney (>70%), bile duct (57%), cervix (50%), and, to a lesser extent, additional cancer types. Overall, our study reveals an unexpectedly extensive contribution of acrylamide-associated mutagenesis to human cancers.

A quantitative model to predict pathogenicity of missense variants in the TP53 gene.

Germline pathogenic variants in the TP53 gene cause Li-Fraumeni syndrome, a condition that predisposes individuals to a wide range of cancer types. Identification of individuals carrying a TP53 pathogenic variant is linked to clinical management decisions, such as the avoidance of radiotherapy and use of high-intensity screening programs. The aim of this study was to develop an evidence-based quantitative model that integrates independent in silico data (Align-GVGD and BayesDel) and somatic to germline ratio (SGR), to assign pathogenicity to every possible missense variant in the TP53 gene. To do this, a likelihood ratio for pathogenicity (LR) was derived from each component calibrated using reference sets of assumed pathogenic and benign missense variants. A posterior probability of pathogenicity was generated by combining LRs, and algorithm outputs were validated using different approaches. A total of 730 TP53 missense variants could be assigned to a clinically interpretable class. The outputs of the model correlated well with existing clinical information, functional data, and ClinVar classifications. In conclusion, these quantitative outputs provide the basis for individualized assessment of cancer risk useful for clinical interpretation. In addition, we propose the value of the novel SGR approach for use within the ACMG/AMP guidelines for variant classification.

Molecular features of premenopausal breast cancers in Latin American women: Pilot results from the PRECAMA study.

BACKGROUND: In Latin America (LA), there is a high incidence rate of breast cancer (BC) in premenopausal women, and the genomic features of these BC remain unknown. Here, we aim to characterize the molecular features of BC in young LA women within the framework of the PRECAMA study, a multicenter population-based case-control study of BC in premenopausal women. METHODS: Pathological tumor tissues were collected from incident cases from four LA countries. Immunohistochemistry (IHC) was performed centrally for ER, PR, HER2, Ki67, EGFR, CK5/6, and p53 protein markers. Targeted deep sequencing was done on genomic DNA extracted from formalin-fixed, paraffin-embedded tumor tissues and their paired blood samples to screen for somatic mutations in eight genes frequently mutated in BC. A subset of samples was analyzed by exome sequencing to identify somatic mutational signatures. RESULTS: The majority of cases were positive for ER or PR (168/233; 72%), and 21% were triple-negative (TN), mainly of basal type. Most tumors were positive for Ki67 (189/233; 81%). In 126 sequenced cases, TP53 and PIK3CA were the most frequently mutated genes (32.5% and 21.4%, respectively), followed by AKT1 (9.5%). TP53 mutations were more frequent in HER2-enriched and TN IHC subtypes, whereas PIK3CA/AKT1 mutations were more frequent in ER-positive tumors, as expected. Interestingly, a higher proportion of G:C>T:A mutations was observed in TP53 in PRECAMA cases compared with TCGA and METABRIC BC series (27% vs 14%). Exome-wide mutational patterns in 10 TN cases revealed alterations in signal transduction pathways and major contributions of mutational signatures caused by altered DNA repair pathways. CONCLUSIONS: These pilot results on PRECAMA tumors give a preview of the molecular features of premenopausal BC in LA. Although the overall mutation burden was as expected from data in other populations, mutational patterns observed in TP53 and exome-wide suggested possible differences in mutagenic processes giving rise to these tumors compared with other populations. Further -omics analyses of a larger number of cases in the near future will enable the investigation of relationships between these molecular features and risk factors.

Reproductive factors and molecular subtypes of breast cancer among premenopausal women in Latin America: the PRECAMA study.

Etiological differences among breast cancer (BC) subtypes have not been clearly established, especially among young women in Latin America. This study examined the relationship between reproductive factors and BC subtypes among 288 BC cases (20-45 years) and population-based matched controls in four Latin American countries. Immunohistochemistry was determined centrally. Associations between BC and reproductive factors were determined. Older age at first full-term pregnancy (FFTP) (Odds Ratio (OR) = 1.11; 95% Confidence Interval (CI), 1.04-1.19 per year), longer time between menarche and FFTP (OR = 1.12; 95%CI: 1.04-1.20 per year), and older age at last pregnancy (OR = 1.10; 95%CI, 1.02-1.19 per year) were associated with an increased risk of estrogen receptor positive (ER+) tumors (n = 122). Ever pregnant (OR = 0.35; 95%CI, 0.13-0.96), number of childbirths (OR = 0.64; 95%CI, 0.47-0.87 per child), time since last birth (OR = 0.92; 95%CI, 0.85-0.99 per year), and history of breastfeeding (OR = 0.23; 95%CI, 0.09-0.58) were inversely associated with the risk of ER+ tumor. Older age at menarche (OR = 0.63; 95%CI, 0.45-0.89 per year) and longer duration of breastfeeding (OR = 0.97; 95%CI, 0.94-1.01 per month) were inversely associated with estrogen receptor negative (ER-) tumors (n = 48). Reproductive factors may be differentially associated with BC subtypes in young Latin American women.

Improved, ACMG-compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants.

Clinical interpretation of germline missense variants represents a major challenge, including those in the TP53 Li-Fraumeni syndrome gene. Bioinformatic prediction is a key part of variant classification strategies. We aimed to optimize the performance of the Align-GVGD tool used for p53 missense variant prediction, and compare its performance to other bioinformatic tools (SIFT, PolyPhen-2) and ensemble methods (REVEL, BayesDel). Reference sets of assumed pathogenic and assumed benign variants were defined using functional and/or clinical data. Area under the curve and Matthews correlation coefficient (MCC) values were used as objective functions to select an optimized protein multisequence alignment with best performance for Align-GVGD. MCC comparison of tools using binary categories showed optimized Align-GVGD (C15 cut-off) combined with BayesDel (0.16 cut-off), or with REVEL (0.5 cut-off), to have the best overall performance. Further, a semi-quantitative approach using multiple tiers of bioinformatic prediction, validated using an independent set of nonfunctional and functional variants, supported use of Align-GVGD and BayesDel prediction for different strength of evidence levels in ACMG/AMP rules. We provide rationale for bioinformatic tool selection for TP53 variant classification, and have also computed relevant bioinformatic predictions for every possible p53 missense variant to facilitate their use by the scientific and medical community.

Genome-scale mutational signatures of aflatoxin in cells, mice, and human tumors.

Aflatoxin B1 (AFB1) is a mutagen and IARC (International Agency for Research on Cancer) Group 1 carcinogen that causes hepatocellular carcinoma (HCC). Here, we present the first whole-genome data on the mutational signatures of AFB1 exposure from a total of >40,000 mutations in four experimental systems: two different human cell lines, in liver tumors in wild-type mice, and in mice that carried a hepatitis B surface antigen transgene-this to model the multiplicative effects of aflatoxin exposure and hepatitis B in causing HCC. AFB1 mutational signatures from all four experimental systems were remarkably similar. We integrated the experimental mutational signatures with data from newly sequenced HCCs from Qidong County, China, a region of well-studied aflatoxin exposure. This indicated that COSMIC mutational signature 24, previously hypothesized to stem from aflatoxin exposure, indeed likely represents AFB1 exposure, possibly combined with other exposures. Among published somatic mutation data, we found evidence of AFB1 exposure in 0.7% of HCCs treated in North America, 1% of HCCs from Japan, but 16% of HCCs from Hong Kong. Thus, aflatoxin exposure apparently remains a substantial public health issue in some areas. This aspect of our study exemplifies the promise of future widespread resequencing of tumor genomes in providing new insights into the contribution of mutagenic exposures to cancer incidence.

Genome Sequence of a Novel Human Gammapapillomavirus Isolated from Skin.

A new human gammapapillomavirus (HPV_MTS2) genome was isolated and fully cloned from a skin swab. The L1 open reading frame of HPV_MTS2 was 79% and 80% identical to those of its closest relatives, HPV type 149 (species Gamma-7 of the genus Gammapapillomavirus) and HPV isolate Dysk2 (GenBank accession no. KX781281), respectively, thus qualifying it as a new HPV type.

Identification of Circulating Tumor DNA for the Early Detection of Small-cell Lung Cancer.

Circulating tumor DNA (ctDNA) is emerging as a key potential biomarker for post-diagnosis surveillance but it may also play a crucial role in the detection of pre-clinical cancer. Small-cell lung cancer (SCLC) is an excellent candidate for early detection given there are no successful therapeutic options for late-stage disease, and it displays almost universal inactivation of TP53. We assessed the presence of TP53 mutations in the cell-free DNA (cfDNA) extracted from the plasma of 51 SCLC cases and 123 non-cancer controls. We identified mutations using a pipeline specifically designed to accurately detect variants at very low fractions. We detected TP53 mutations in the cfDNA of 49% SCLC patients and 11.4% of non-cancer controls. When stratifying the 51 initial SCLC cases by stage, TP53 mutations were detected in the cfDNA of 35.7% early-stage and 54.1% late-stage SCLC patients. The results in the controls were further replicated in 10.8% of an independent series of 102 non-cancer controls. The detection of TP53 mutations in 11% of the 225 non-cancer controls suggests that somatic mutations in cfDNA among individuals without any cancer diagnosis is a common occurrence, and poses serious challenges for the development of ctDNA screening tests.

TP53 Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data.

TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA-binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database.

MutSpec: a Galaxy toolbox for streamlined analyses of somatic mutation spectra in human and mouse cancer genomes.

BACKGROUND: The nature of somatic mutations observed in human tumors at single gene or genome-wide levels can reveal information on past carcinogenic exposures and mutational processes contributing to tumor development. While large amounts of sequencing data are being generated, the associated analysis and interpretation of mutation patterns that may reveal clues about the natural history of cancer present complex and challenging tasks that require advanced bioinformatics skills. To make such analyses accessible to a wider community of researchers with no programming expertise, we have developed within the web-based user-friendly platform Galaxy a first-of-its-kind package called MutSpec. RESULTS: MutSpec includes a set of tools that perform variant annotation and use advanced statistics for the identification of mutation signatures present in cancer genomes and for comparing the obtained signatures with those published in the COSMIC database and other sources. MutSpec offers an accessible framework for building reproducible analysis pipelines, integrating existing methods and scripts developed in-house with publicly available R packages. MutSpec may be used to analyse data from whole-exome, whole-genome or targeted sequencing experiments performed on human or mouse genomes. Results are provided in various formats including rich graphical outputs. An example is presented to illustrate the package functionalities, the straightforward workflow analysis and the richness of the statistics and publication-grade graphics produced by the tool. CONCLUSIONS: MutSpec offers an easy-to-use graphical interface embedded in the popular Galaxy platform that can be used by researchers with limited programming or bioinformatics expertise to analyse mutation signatures present in cancer genomes. MutSpec can thus effectively assist in the discovery of complex mutational processes resulting from exogenous and endogenous carcinogenic insults.

Circulating free DNA concentration is an independent prognostic biomarker in lung cancer.

Plasma circulating cell-free (cf)DNA is of interest in oncology because it has been shown to contain tumour DNA and may thus be used as liquid biopsy. In nonsmall cell lung cancer (NSCLC), cfDNA quantification has been proposed for the monitoring and follow-up of patients. However, available studies are limited and need to be confirmed by studies with larger sample sizes and including patients who receive more homogenous treatments. Our objective was to assess the predictive and prognostic value of plasma cfDNA concentration in a large series of patients with NSCLC and treated with a standard chemotherapy regimen.We included samples from lung cancer patients recruited into the Pharmacogenoscan study. The cfDNA of 218 patients was extracted and quantified by fluorometry before and after two or three cycles of platinum-based chemotherapy. The association between baseline and post-chemotherapy concentrations and treatment response, assessed by RECIST (response evaluation criteria in solid tumours) or patient survival was analysed.Patients with high cfDNA concentrations (highest tertile) at baseline had a significantly worse disease-free and overall survival than those with lower concentrations (lowest and middle tertiles) (median overall survival 10 months (95% CI 10.7-13.9) versus 14.2 months (95% CI 12.6-15.8), respectively; p=0.001). In multivariate analysis, increased baseline concentration of cfDNA was an independent prognostic factor. However, we did not find any association between cfDNA concentration and response to treatment.cfDNA may be a biomarker for the assessment of prognosis in NSCLC. However, total concentration of cfDNA does not appear to predict chemotherapy response.