Bedside Back to Bench: Building Bridges between Basic and Clinical Genomic Research.

Genome sequencing has revolutionized the diagnosis of genetic diseases. Close collaborations between basic scientists and clinical genomicists are now needed to link genetic variants with disease causation. To facilitate such collaborations, we recommend prioritizing clinically relevant genes for functional studies, developing reference variant-phenotype databases, adopting phenotype description standards, and promoting data sharing.

Common variation in a long non-coding RNA gene modulates variation of circulating TGF-ß2 levels in metastatic colorectal cancer patients (Alliance).

BACKGROUND: Herein, we report results from a genome-wide study conducted to identify protein quantitative trait loci (pQTL) for circulating angiogenic and inflammatory protein markers in patients with metastatic colorectal cancer (mCRC). The study was conducted using genotype, protein marker, and baseline clinical and demographic data from CALGB/SWOG 80405 (Alliance), a randomized phase III study designed to assess outcomes of adding VEGF or EGFR inhibitors to systemic chemotherapy in mCRC patients. Germline DNA derived from blood was genotyped on whole-genome array platforms. The abundance of protein markers was quantified using a multiplex enzyme-linked immunosorbent assay from plasma derived from peripheral venous blood collected at baseline. A robust rank-based method was used to assess the statistical significance of each variant and protein pair against a strict genome-wide level. A given pQTL was tested for validation in two external datasets of prostate (CALGB 90401) and pancreatic cancer (CALGB 80303) patients. Bioinformatics analyses were conducted to further establish biological bases for these findings. RESULTS: The final analysis was carried out based on data from 540,021 common typed genetic variants and 23 protein markers from 869 genetically estimated European patients with mCRC. Correcting for multiple testing, the analysis discovered a novel cis-pQTL in LINC02869, a long non-coding RNA gene, for circulating TGF-ß2 levels (rs11118119; AAF = 0.11; P-value < 1.4e-14). This finding was validated in a cohort of 538 prostate cancer patients from CALGB 90401 (AAF = 0.10, P-value < 3.3e-25). The analysis also validated a cis-pQTL we had previously reported for VEGF-A in advanced pancreatic cancer, and additionally identified trans-pQTLs for VEGF-R3, and cis-pQTLs for CD73. CONCLUSIONS: This study has provided evidence of a novel cis germline genetic variant that regulates circulating TGF-ß2 levels in plasma of patients with advanced mCRC and prostate cancer. Moreover, the validation of previously identified pQTLs for VEGF-A, CD73, and VEGF-R3, potentiates the validity of these associations.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis.

BACKGROUND: Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity. METHODS: Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC). RESULTS: Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants. CONCLUSIONS: FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

Pharmacogenetic and clinical risk factors for bevacizumab-related gastrointestinal hemorrhage in prostate cancer patients treated on CALGB 90401 (Alliance).

The objective of this study was to discover clinical and pharmacogenetic factors associated with bevacizumab-related gastrointestinal hemorrhage in Cancer and Leukemia Group B (Alliance) 90401. Patients with metastatic castration-resistant prostate cancer received docetaxel and prednisone ± bevacizumab. Patients were genotyped using Illumina HumanHap610-Quad and assessed using cause-specific risk for association between single nucleotide polymorphisms (SNPs) and gastrointestinal hemorrhage. In 1008 patients, grade 2 or higher gastrointestinal hemorrhage occurred in 9.5% and 3.8% of bevacizumab (n = 503) and placebo (n = 505) treated patients, respectively. Bevacizumab (P < 0.001) and age (P = 0.002) were associated with gastrointestinal hemorrhage. In 616 genetically estimated Europeans (n = 314 bevacizumab and n = 302 placebo treated patients), grade 2 or higher gastrointestinal hemorrhage occurred in 9.6% and 2.0% of patients, respectively. One SNP (rs1478947; HR 6.26; 95% CI 3.19-12.28; P = 9.40 × 10-8) surpassed Bonferroni-corrected significance. Grade 2 or higher gastrointestinal hemorrhage rate was 33.3% and 6.2% in bevacizumab-treated patients with the AA/AG and GG genotypes, versus 2.9% and 1.9% in the placebo arm, respectively. Prospective validation of these findings and functional analyses are needed to better understand the genetic contribution to treatment-related gastrointestinal hemorrhage.

Deceptive learning in histopathology.

AIMS: Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the extent to which the visual strategies learned by deep learning models in histopathological analysis are trustworthy or not has yet to be systematically analysed. Here, we systematically evaluate deep neural networks (DNNs) trained for histopathological analysis in order to understand if their learned strategies are trustworthy or deceptive. METHODS AND RESULTS: We trained a variety of DNNs on a novel data set of 221 whole-slide images (WSIs) from lung adenocarcinoma patients, and evaluated their effectiveness at (1) molecular profiling of KRAS versus EGFR mutations, (2) determining the primary tissue of a tumour and (3) tumour detection. While DNNs achieved above-chance performance on molecular profiling, they did so by exploiting correlations between histological subtypes and mutations, and failed to generalise to a challenging test set obtained through laser capture microdissection (LCM). In contrast, DNNs learned robust and trustworthy strategies for determining the primary tissue of a tumour as well as detecting and localising tumours in tissue. CONCLUSIONS: Our work demonstrates that DNNs hold immense promise for aiding pathologists in analysing tissue. However, they are also capable of achieving seemingly strong performance by learning deceptive strategies that leverage spurious correlations, and are ultimately unsuitable for research or clinical work. The framework we propose for model evaluation and interpretation is an important step towards developing reliable automated systems for histopathological analysis.

High-throughput screening and genome-wide analyses of 44 anticancer drugs in the 1000 Genomes cell lines reveals an association of the NQO1 gene with the response of multiple anticancer drugs.

Cancer patients exhibit a broad range of inter-individual variability in response and toxicity to widely used anticancer drugs, and genetic variation is a major contributor to this variability. To identify new genes that influence the response of 44 FDA-approved anticancer drug treatments widely used to treat various types of cancer, we conducted high-throughput screening and genome-wide association mapping using 680 lymphoblastoid cell lines from the 1000 Genomes Project. The drug treatments considered in this study represent nine drug classes widely used in the treatment of cancer in addition to the paclitaxel + epirubicin combination therapy commonly used for breast cancer patients. Our genome-wide association study (GWAS) found several significant and suggestive associations. We prioritized consistent associations for functional follow-up using gene-expression analyses. The NAD(P)H quinone dehydrogenase 1 (NQO1) gene was found to be associated with the dose-response of arsenic trioxide, erlotinib, trametinib, and a combination treatment of paclitaxel + epirubicin. NQO1 has previously been shown as a biomarker of epirubicin response, but our results reveal novel associations with these additional treatments. Baseline gene expression of NQO1 was positively correlated with response for 43 of the 44 treatments surveyed. By interrogating the functional mechanisms of this association, the results demonstrate differences in both baseline and drug-exposed induction.

Biomarkers for Response to Anti-PD-1/Anti-PD-L1 Immune Checkpoint Inhibitors: A Large Meta-Analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) that block PD-1/PD-L1 have consistently demonstrated durable clinical activity across multiple histologies but have low overall response rates for many cancers-indicating that too few patients benefit from ICIs. Many studies have explored potential predictive biomarkers (eg, PD-1/PD-L1 expression, tumor mutational burden [TMB]), no consensus biomarker has been identified. METHODS: This meta-analysis combined predictive accuracy metrics for various biomarkers, across multiple cancer types, to determine which biomarkers are most accurate for predicting ICI response. Data from 18,792 patients from 100 peer-reviewed studies that evaluated putative biomarkers for response to anti-PD-1/anti- PD-L1 treatment were meta-analyzed using bivariate linear mixed models. Biomarker performance was assessed based on the global area under the receiver operating characteristic curve (AUC) and 95% bootstrap confidence intervals. RESULTS: PD-L1 immunohistochemistry, TMB, and multimodal biomarkers discriminated responders and nonresponders better than random assignment (AUCs >.50). Excluding multimodal biomarkers, these biomarkers correctly classified at least 50% of the responders (sensitivity 95% CIs, >.50). Notably, variation in biomarker performance was observed across cancer types. CONCLUSIONS: Although some biomarkers consistently performed better, heterogeneity in performance was observed across cancer types, and additional research is needed to identify highly accurate and precise biomarkers for widespread clinical use.

A two-stage genome-wide association study to identify novel genetic loci associated with acute radiotherapy toxicity in nasopharyngeal carcinoma.

BACKGROUND: Genetic variants associated with acute side effects of radiotherapy in nasopharyngeal carcinoma (NPC) remain largely unknown. METHODS: We performed a two-stage genome-wide association analysis including a total of 1084 patients, where 319 individuals in the discovery stage were genotyped for 688,783 SNPs using whole genome-wide screening microarray. Significant variants were then validated in an independent cohort of 765 patients using the MassARRAY system. Gene mapping, linkage disequilibrium, genome-wide association analysis, and polygenic risk score were conducted or calculated using FUMA, LDBlockShow, PLINK, and PRSice software programs, respectively. RESULTS: Five SNPs (rs6711678, rs4848597, rs4848598, rs2091255, and rs584547) showed statistical significance after validation. Radiotherapy toxicity was more serious in mutant minor allele carriers of all five SNPs. Stratified analysis further indicated that rs6711678, rs4848597, rs4848598, and rs2091255 correlated with skin toxicity in patients of EBV positive, late stage (III and IV), receiving both concurrent chemoradiotherapy and induction/adjuvant chemotherapy, and with OR values ranging from 1.92 to 2.66. For rs584547, high occurrence of dysphagia was found in A allele carriers in both the discovery (P = 1.27 × 10- 6, OR = 1.55) and validation (P = 0.002, OR = 4.20) cohorts. Furthermore, prediction models integrating both genetic and clinical factors for skin reaction and dysphagia were established. The area under curve (AUC) value of receiver operating characteristic (ROC) curves were 0.657 (skin reaction) and 0.788 (dysphagia). CONCLUSIONS: Rs6711678, rs4848597, rs4848598, and rs2091255 on chromosome 2q14.2 and rs584547 were found to be novel risk loci for skin toxicity and dysphagia in NPC patients receiving radiotherapy. TRIAL REGISTRATION: Chinese Clinical Trial Register (registration number: ChiCTR-OPC-14005257 and CTXY-140007-2).

Bevacizumab-induced hypertension and proteinuria: a genome-wide study of more than 1000 patients.

BACKGROUND: Hypertension and proteinuria are common bevacizumab-induced toxicities. No validated biomarkers are available for identifying patients at risk of these toxicities. METHODS: A genome-wide association study (GWAS) meta-analysis was performed in 1039 bevacizumab-treated patients of European ancestry in four clinical trials (CALGB 40502, 40503, 80303, 90401). Grade ≥2 hypertension and proteinuria were recorded (CTCAE v.3.0). Single-nucleotide polymorphism (SNP)-toxicity associations were determined using a cause-specific Cox model adjusting for age and sex. RESULTS: The most significant SNP associated with hypertension with concordant effect in three out of the four studies (p-value <0.05 for each study) was rs6770663 (A > G) in KCNAB1, with the G allele increasing the risk of hypertension (p-value = 4.16 × 10-6). The effect of the G allele was replicated in ECOG-ACRIN E5103 in 582 patients (p-value = 0.005). The meta-analysis of all five studies for rs6770663 led to p-value = 7.73 × 10-8, close to genome-wide significance. The most significant SNP associated with proteinuria was rs339947 (C > A, between DNAH5 and TRIO), with the A allele increasing the risk of proteinuria (p-value = 1.58 × 10-7). CONCLUSIONS: The results from the largest study of bevacizumab toxicity provide new markers of drug safety for further evaluations. SNP in KCNAB1 validated in an independent dataset provides evidence toward its clinical applicability to predict bevacizumab-induced hypertension. ClinicalTrials.gov Identifier: NCT00785291 (CALGB 40502); NCT00601900 (CALGB 40503); NCT00088894 (CALGB 80303) and NCT00110214 (CALGB 90401).

Race and smoking status associated with paclitaxel drug response in patient-derived lymphoblastoid cell lines.

The use of ex-vivo model systems to provide a level of forecasting for in-vivo characteristics remains an important need for cancer therapeutics. The use of lymphoblastoid cell lines (LCLs) is an attractive approach for pharmacogenomics and toxicogenomics, due to their scalability, efficiency, and cost-effectiveness. There is little data on the impact of demographic or clinical covariates on LCL response to chemotherapy. Paclitaxel sensitivity was determined in LCLs from 93 breast cancer patients from the University of North Carolina Lineberger Comprehensive Cancer Center Breast Cancer Database to test for potential associations and/or confounders in paclitaxel dose-response assays. Measures of paclitaxel cell viability were associated with patient data included treatment regimens, cancer status, demographic and environmental variables, and clinical outcomes. We used multivariate analysis of variance to identify the in-vivo variables associated with ex-vivo dose-response. In this unique dataset that includes both in-vivo and ex-vivo data from breast cancer patients, race (P = 0.0049) and smoking status (P = 0.0050) were found to be significantly associated with ex-vivo dose-response in LCLs. Racial differences in clinical dose-response have been previously described, but the smoking association has not been reported. Our results indicate that in-vivo smoking status can influence ex-vivo dose-response in LCLs, and more precise measures of covariates may allow for more precise forecasting of clinical effect. In addition, understanding the mechanism by which exposure to smoking in-vivo effects ex-vivo dose-response in LCLs may open up new avenues in the quest for better therapeutic prediction.

Pharmacogenetic study in gastric cancer patients treated with adjuvant fluorouracil/leucovorin or epirubicin/cisplatin/fluorouracil before and after chemoradiation on CALGB 80101 (Alliance).

There is a lack of pharmacogenetic predictors of outcome in gastric cancer patients. The aim of this study was to assess previously identified candidate genes associated with 5-fluorouracil (5-FU), cisplatin, or epirubicin toxicity or response in a cohort of resected gastric cancer patients treated on CALGB (Alliance) 80101. Gastric or gastroesophageal cancer patients randomized to adjuvant 5-FU/leucovorin or epirubicin/cisplatin/5-FU before and after 5-FU chemoradiation were genotyped for single nucleotide polymorphisms (SNPs) in GSTP1 (rs1695), ERCC1 (rs11615 and rs3212986), XRCC1 (rs25487), UGT2B7 (rs7439366) and the 28 base-pair tandem repeats in TYMS (rs34743033). Logistic regression and log rank tests were used to assess the association between each SNP and incidence of grade 3/4 neutropenia and leukopenia, overall (OS) and progression-free survival (PFS), respectively. Toxicity endpoint analyses were adjusted for the treatment arm, while OS and PFS were also adjusted for performance status, sex, age, lymph node involvement, and primary tumor site and size. Of 281 subjects with successful genotyping results and available clinical (toxicity and efficacy) data, 166 self-reported non-Hispanic White patients were included in the final analysis. There was a lack of evidence of an association among any SNPs tested with grade 3/4 neutropenia and leukopenia or OS and PFS. Age, lymph node involvement, and primary tumor size were significantly associated with OS and PFS. This study failed to confirm results of previous gastric cancer pharmacogenetic studies.

Pharmacogenomics.

Genomic medicine, which uses DNA variation to individualise and improve human health, is the subject of this Series of papers. The idea that genetic variation can be used to individualise drug therapy-the topic addressed here-is often viewed as within reach for genomic medicine. We have reviewed general mechanisms underlying variability in drug action, the role of genetic variation in mediating beneficial and adverse effects through variable drug concentrations (pharmacokinetics) and drug actions (pharmacodynamics), available data from clinical trials, and ongoing efforts to implement pharmacogenetics in clinical practice.

Opportunities, resources, and techniques for implementing genomics in clinical care.

Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.

An initial genetic analysis of gemcitabine-induced high-grade neutropenia in pancreatic cancer patients in CALGB 80303 (Alliance).

OBJECTIVES: One of the standard of care regimens for advanced pancreatic cancer is gemcitabine-based chemotherapy. The efficacy of gemcitabine is limited by dose-limiting hematologic toxicities especially neutropenia. Uncovering the variability of these toxicities attributed to germline DNA variation is of great importance. PATIENTS AND METHODS: CALGB 80303 was a randomized study in advanced pancreatic cancer patients treated with gemcitabine with or without bevacizumab. The study protocol included genotyping of genes of gemcitabine disposition (CDA, DCTD, SLC29A1, SLC28A1, and SLC29A2), as well as a genome-wide analysis. The clinical phenotype was time to early high-grade neutropenia event accounting for progression or death or other treatment-terminating adverse events as competing for informative events. The inference was carried out on the basis of the association between genotype and cause-specific hazard of a neutropenic event. RESULTS: The primary analyses were carried out on the basis of 294 genetically estimated European pancreatic cancer patients. For CDA rs2072671 (A>C), AC and CC patients had a lower risk of neutropenia than AA patients (P=0.01, hazard ratio: 0.61, 95% confidence interval: 0.41-0.89). For SLC28A1 rs3825876 (G>A), AA patients have a higher risk of neutropenia than GA and GG patients (P=0.02, hazard ratio: 1.51, 95% confidence interval: 1.06-2.16). CDA rs2072671 was associated with increased mRNA expression in whole blood in three studies (P=2.7e-14, 6.61e-62, and 9.70e-65). In the genome-wide analysis, variants in TGFB2 were among the top hits (lowest P=1.62e-06) but had no effect in luciferase assays. CONCLUSION: This is the first genetic analysis of gemcitabine-induced neutropenia using a competing risk model in a prospective randomized clinical study has proposed a potentially novel mechanism of the protective effect of the CDA rs2072671 variant. Further confirmation is needed.

Influence of genetic variation in the vitamin D pathway on plasma 25-hydroxyvitamin D3 levels and survival among patients with metastatic colorectal cancer.

PURPOSE: The relationships of genetic variation in the vitamin D pathway with circulating 25-hydroxyvitamin D3 [25(OH)D] levels and survival remain largely unknown for patients with metastatic colorectal cancer (mCRC). METHODS: Among 535 patients participating in a randomized trial of chemotherapy for mCRC, we prospectively measured baseline plasma 25(OH)D and examined 124 tagging single-nucleotide polymorphisms (SNPs) within seven genes in the vitamin D pathway, including five SNPs associated with circulating 25(OH)D levels in previous genome-wide association studies (GWAS). We evaluated whether these SNPs were associated with plasma 25(OH)D levels and patient outcome (overall survival, time to progression, and tumor response), using linear, logistic, and Cox proportional hazards regression. RESULTS: We observed a significant association between 25(OH)D levels and an additive genetic risk score determined by the five GWAS-identified SNPs (p = 0.0009). We did not observe any direct association between 25(OH)D-associated SNPs, individually or as a genetic risk score, and patient outcome. However, we found a significant interaction between 25(OH)D levels and rs12785878 genotype in DHCR7 on overall survival (pinteraction = 0.02). CONCLUSION: Germline genetic variation in the vitamin D pathway informs baseline 25(OH)D levels among patients with mCRC. The association between 25(OH)D levels and overall survival may vary by DHCR7 genotype. ClinicalTrials.gov Identifier: NCT00003594 ( https://clinicaltrials.gov/ct2/show/NCT00003594 ).

Adherence to Adjuvant Imatinib Therapy in Patients with Gastrointestinal Stromal Tumor in Clinical Practice: A Cross-Sectional Study.

BACKGROUND: Adherence to imatinib therapy has been significantly associated with disease progression and direct medical costs in gastrointestinal stromal tumor (GIST) patients. However, adherence to oral anticancer drugs is frequently hindered by the influence of various factors. The aim of this study was to evaluate the prevalence of imatinib adherence and its influencing factors among GIST patients in the adjuvant setting. METHODS: Adherence of GIST patients (receiving imatinib for ≥1 month) was assessed using the 8-item Morisky Medication Adherence Scale (MMAS), with a score <8 indicating nonadherence. Quality of life and social support were evaluated by the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ C30) and Social Support Rating Scale (SSRS). Factors associated with nonadherence were identified by multivariate logistic regression analysis. Imatinib plasma concentrations were determined and compared between adherent and nonadherent groups. RESULTS: A total of 158 GIST patients were enrolled, 92 (58.2%) patients were considered nonadherent. Intentional nonadherence, especially feeling hassled by treatment plan (34.2% of patients), was common. In the multivariate logistic regression analysis, gender (OR 2.68, 95% CI 1.33-5.41; p = 0.0058), place of residence (OR 3.20, 95% CI 1.39-7.35; p = 0.0061), and global health status (OR 1.02, 95% CI 1.00-1.04; p = 0.0378) were significantly associated with nonadherence. Moreover, imatinib plasma concentrations in nonadherent patients were significantly lower than that in the good adherence group (p = 0.0338). CONCLUSIONS: Poor adherence to imatinib is a notable problem in Chinese GIST patients in the adjuvant therapy setting. The predominant indicators of nonadherence in this study were gender (female), living in a rural area, and harboring a low global health status score. These indicators may aid clinicians in determining where increased efforts in promoting adherence may be beneficial.

Value of Supportive Care Pharmacogenomics in Oncology Practice.

Genomic medicine provides opportunities to personalize cancer therapy for an individual patient. Although novel targeted therapies prolong survival, most patients with cancer continue to suffer from burdensome symptoms including pain, depression, neuropathy, nausea and vomiting, and infections, which significantly impair quality of life. Suboptimal management of these symptoms can negatively affect response to cancer treatment and overall prognosis. The effect of genetic variation on drug response-otherwise known as pharmacogenomics-is well documented and directly influences an individual patient's response to antiemetics, opioids, neuromodulators, antidepressants, antifungals, and more. The growing body of pharmacogenomic data can now guide clinicians to select the safest and most effective supportive medications for an individual patient with cancer from the very first prescription. This review outlines a theoretical patient case and the implications of using pharmacogenetic test results to personalize supportive care throughout the cancer care continuum. IMPLICATIONS FOR PRACTICE: Integration of palliative medicine into the cancer care continuum has resulted in increased quality of life and survival for patients with many cancer types. However, suboptimal management of symptoms such as pain, neuropathy, depression, and nausea and vomiting continues to place a heavy burden on patients with cancer. As demonstrated in this theoretical case, pharmacogenomics can have a major effect on clinical response to medications used to treat these conditions. Recognizing the value of supportive care pharmacogenomics in oncology and application into routine practice offers an objective choice for the safest and most effective treatment compared with the traditional trial and error method.

Prediction of chemotherapy-induced nausea and vomiting from patient-reported and genetic risk factors.

PURPOSE: Chemotherapy-induced nausea and vomiting (CINV) is common among cancer patients. Early identification of patients at risk for CINV may help to personalize anti-emetic therapies. To date, few studies have examined the combined contributions of patient-reported and genetic risk factors to CINV. The goal of this study was to evaluate these risk factors. METHODS: Prior to their first chemotherapy infusion, participants completed demographic and risk factor questionnaires and provided a blood sample to measure genetic variants in ABCB1 (rs1045642) and HTR3B (rs45460698) as well as CYP2D6 activity score. The M.D. Anderson Symptom Inventory was completed at 24 h and 5-day post-infusion to assess the severity of acute and delayed CINV, respectively. RESULTS: Participants were 88 patients (55% female, M = 60 years). A total of 23% experienced acute nausea and 55% delayed nausea. Younger age, history of pregnancy-related nausea, fewer hours slept the night prior to infusion, and variation in ABCB1 were associated with more severe acute nausea; advanced-stage cancer and receipt of highly emetogenic chemotherapy were associated with more severe delayed nausea (p values < 0.05). In multivariable analyses, ABCB1 added an additional 5% predictive value beyond the 13% variance explained by patient-reported risk factors. CONCLUSIONS: The current study identified patient-reported and genetic factors that may place patients at risk for acute nausea despite receipt of guideline-consistent anti-emetic prophylaxis. Additional studies examining other genetic variants are needed, as well as the development of risk prediction models including both patient-reported and genetic risk factors.

A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study.

BACKGROUND: Despite its common use in cancer treatment, radiotherapy has not yet entered the era of precision medicine, and there have been no approaches to adjust dose based on biological differences between or within tumours. We aimed to assess whether a patient-specific molecular signature of radiation sensitivity could be used to identify the optimum radiotherapy dose. METHODS: We used the gene-expression-based radiation-sensitivity index and the linear quadratic model to derive the genomic-adjusted radiation dose (GARD). A high GARD value predicts for high therapeutic effect for radiotherapy; which we postulate would relate to clinical outcome. Using data from the prospective, observational Total Cancer Care (TCC) protocol, we calculated GARD for primary tumours from 20 disease sites treated using standard radiotherapy doses for each disease type. We also used multivariable Cox modelling to assess whether GARD was independently associated with clinical outcome in five clinical cohorts: Erasmus Breast Cancer Cohort (n=263); Karolinska Breast Cancer Cohort (n=77); Moffitt Lung Cancer Cohort (n=60); Moffitt Pancreas Cancer Cohort (n=40); and The Cancer Genome Atlas Glioblastoma Patient Cohort (n=98). FINDINGS: We calculated GARD for 8271 tissue samples from the TCC cohort. There was a wide range of GARD values (range 1·66-172·4) across the TCC cohort despite assignment of uniform radiotherapy doses within disease types. Median GARD values were lowest for gliomas and sarcomas and highest for cervical cancer and oropharyngeal head and neck cancer. There was a wide range of GARD values within tumour type groups. GARD independently predicted clinical outcome in breast cancer, lung cancer, glioblastoma, and pancreatic cancer. In the Erasmus Breast Cancer Cohort, 5-year distant-metastasis-free survival was longer in patients with high GARD values than in those with low GARD values (hazard ratio 2·11, 95% 1·13-3·94, p=0·018). INTERPRETATION: A GARD-based clinical model could allow the individualisation of radiotherapy dose to tumour radiosensitivity and could provide a framework to design genomically-guided clinical trials in radiation oncology. FUNDING: None.