Treatment Decisions For Cancer Patients Research Articles

Abstract 2416: Personalized minimal residual disease detection using tumor-derived structural variants in cell-free DNA

Abstract We demonstrate development and technical validation of a novel approach for analysis of plasma circulating-tumor DNA (ctDNA) for residual disease detection and monitoring that offers improvements over existing technologies. ctDNA in blood can be leveraged to monitor treatment response, detect cancer recurrence, and inform treatment decisions for cancer patients. However, accurate detection and quantification of ctDNA is technically challenging due to low concentration of plasma DNA, especially in the adjuvant setting. Most current assays rely on interrogating multiple patient-specific point mutations to achieve exquisite limits of detection but struggle with polymerase errors, sequencing artifacts and limited conversion of input DNA. To overcome these challenges, we developed an approach called Structural Variant Enrichment and Normalization (SVEN) that targets patient-specific genomic rearrangements to achieve sensitive detection and quantification of plasma ctDNA. This method leverages intrinsic features of tumor-derived structural variants (SVs) to improve enrichment and confidence of detection at low tumor fraction through multiplexed PCR and amplicon-based next generation sequencing. To evaluate the assay, we performed whole genome sequencing of DNA from two breast cancer cell lines, as well as matched FFPE tumor and buffy coat samples from 21 early-stage breast cancer patients. We identified consensus SVs, and designed multiplexed SV-specific primers for each subject. We then conducted PCR amplification of cell-free DNA followed by sequencing, amplicon identification, and quantification. Analytical validation was conducted using 284 replicates of cell line dilutions from 1% to 0.003%, and 5 to 40 ng of input. We developed multiplexed assays targeting 25 and 32 SVs across two cell lines, and 3 - 43 SVs across breast cancer patients (median 23 per patient). 91% and 42% of PCR targets were successfully validated for cell lines and FFPE samples respectively. Cell line dilutions demonstrated a sensitivity of 89% at 0.003% tumor fraction with 10 ng input or more. Tumor fractions measured using SVEN agreed with known values (R2 = 0.989). Application of validated panels to patient plasma samples and tumor/germline dilutions is ongoing. SVEN is a novel approach for tumor-guided ctDNA detection and quantification with potential relevance for residual disease detection. On-going studies are investigating the performance of this approach for ctDNA detection in patients with early and locally advanced breast cancer treated with neoadjuvant therapy. Citation Format: Bradon R. McDonald, Kirsten L. Dennison, Amanda L. Schussman, Stephanie M. McGregor, Barbara A. Pockaj, Muhammed Murtaza. Personalized minimal residual disease detection using tumor-derived structural variants in cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2416.

A Comparative Analysis of Chatgpt Vs Expert in Managing Anticancer Drug in Patients Renal Insufficiency

Introduction The appropriate and safe use of anticancer drugs in patients with renal insufficiency (RI) remains a significant challenge in oncology. Recent advancements in natural language processing and machine learning have introduced novel possibilities for clinical decision support. ChatGPT, a state-of-the-art language model, presents a potential solution to support healthcare professionals (HCPs) in making informed treatment management for patients with RI. But a question remains, how ChatGPT would perform is such situations? The aim of this analysis was to compare the recommendations from (human) experts vs ChatGPT regarding the management of anticancer drug in RI patients and more specifically about the potential dose adjustment. Methods In this work, we aimed to compare the performance of ChatGPT 3.5 with experts that are making recommendations on SiteGPR.com. SiteGPR is providing recommendations on how to manage drugs in RI patients and is led by “Service ICAR” from the Nephrology department of the French Pitié-Salpêtrière Hospital (Paris, France). The prompt, “Is there a need to adapt the dose of [name of the drug] in patients with renal impairment and if yes for which level of renal function? was run in a separate ”new chat“ for 175 anticancer drugs in March 2023. Answers were collected and compared with the recommendations from SiteGPR. Both answers from ChatGPT and recommendations from SiteGPR were categorised as ”Yes“ when dose adjustment was required, ”No“ when adjustment was not necessary, and ”ND“ when no data were available. For both ”Yes“ and ”ND“, the level of renal function for which there is a need to change the dose (”Yes“) and for which there are no data below (”ND“) was also collected Results Among 175 anticancer drugs, ChatGPT and SiteGPR had the same general conclusion for 37.1% (65/175) of these drugs (Table, Bold) when the level of RI was not analysed. When ChatGPT had a recommendation to adapt (Yes) or not to adapt (No) the dose of an anticancer drug (n=77 Yes or No drugs), SiteGPR did not agree for 57.1% (44/77) of the drugs. Reversely, when SiteGPR had a strong recommendation to adapt (Yes) or not to adapt (No) the dose of an anticancer drug (n=118 Yes or No drugs), ChatGPT was not aligned in 72.0% (85/118) of the cases. From a clinical perspective, if a HCP had followed ChatGPT instead SiteGPR, patients would have been exposed to a misused for 48.6% (85/175) of the drugs. Both ChatGPR and SiteGPR were not aware of few drugs, however, there is always a way to contact “Service ICAR” if a drug was not investigated on the website. Regarding the level of renal function for which there was a need to adapt the dose (Yes), ChatGPT was able to give a cut-off for 9.6% (7/73) of the anticancer drugs, vs 100.0% (42/42) for SiteGPR. Finally, from a quality perspective, it is important to mention that ChatGPT answers were not always clear. Regarding the level of renal function for which there was no data (ND), ChatGPT was able to give a cut-off for 12.0% (11/92) of the anticancer drugs, vs 100.0% (44/44) for SiteGPR. Finally, from a quality perspective, it is important to mention that ChatGPT answers were not always clear. At the end, when comparing the general recommendations and when considering the level of renal function and after excluding all N/A drugs, ChatGPT and SiteGPR had the same conclusion for only 5.6% (9/161) of anticancer drugs. Conclusion Our findings suggest that ChatGPT does not have (yet) the potential to be an effective clinical decision support tool for optimizing anticancer drug management in RI patients. Further investigations will compare the recommended dose and monitoring between ChatGPT 4.0 and SiteGPR and will also include other AI models. Combining the power of artificial intelligence with human expertise can lead to more personalized and evidence-based treatment decisions in cancer patients. However, it is crucial to acknowledge that while ChatGPT shows some promise, human clinicians remain indispensable for addressing intricate and unique patient situations.

MP14-05 EXTRACELLULAR VESICLE BIOMARKER SIGNATURE DETECTION PLATFORM FOR GUIDING CANCER DETECTION AND THERAPY

You have accessJournal of UrologyCME1 Apr 2023MP14-05 EXTRACELLULAR VESICLE BIOMARKER SIGNATURE DETECTION PLATFORM FOR GUIDING CANCER DETECTION AND THERAPY Thomas Osinski, Samuel Walker, Karen Doersch, Jonathan Flax, and James McGrath Thomas OsinskiThomas Osinski More articles by this author , Samuel WalkerSamuel Walker More articles by this author , Karen DoerschKaren Doersch More articles by this author , Jonathan FlaxJonathan Flax More articles by this author , and James McGrathJames McGrath More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003234.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Extracellular Vesicles (EVs) have tremendous potential in cancer diagnostics and personalized cancer therapeutics. They are abundant in all biofluids, carry molecular markers of their cell-of-origin and can be readily obtained via noninvasive techniques. Current EV biomarker assessments have several limitiations. Pooled EVs from samples have low detection sensitivity for less abundant biomarkers and preclude colocalization of biomarkers on individual EVs. Currently, expensive specialized devices requiring large biofluid inputs are needed for more detailed EV analysis. Here, we develop an easy to use and inexpensive device that permits optical detection of multiple markers on individual EVs using only 10 µl of serum. This work investigates whether the microfluidic strategy we call ‘catch and display for liquid biopsy [CAD-LB]’ can detect biomarkers on single EVs. We also sought to determine the dynamic range of accurate quantitation using purified EVs and serum and validate detection of immune checkpoint proteins (PD-L1 and/or PD-1), which may help to distinguish immune checkpoint immunotherapy (ICI) responders from non-responders in bladder cancer. METHODS: For this study EVs were derived from: 1. ultracentrifuge purified urinary EVs; 2. EVs from media of 5637 bladder cancer and primary bladder epithelium cell lines and; 3. Serum from patients with advanced urothelial carcinoma or healthy controls. EVs were labeled with the pan-EV marker carboxyfluorescein succinimidyl ester and fluorescently labeled primary antibodies. Small volumes (10 µL) of solutions were captured on our membrane with nanopores in a transparent membrane and imaged using fluorescence microscopy. Detection range was assessed by serial dilutions of EVs. EV surface antigen labeling was assessed by CAD-LB. RESULTS: 1. Counting curves demonstrate a wide dynamic range of CAD-LB (102 – 106 EVs) for purified EVs while serum plateaus at lower inputs (∼104 EVs). 2. CAD-LB detects PD-1 and PD-L1 biomarkers in urothelial carcinoma patients’ serum. 3. CAD-LB detects T cell biomarker CD3 on approximately 1-2% of EVs in healthy control serum. CONCLUSIONS: CAD-LB can detect rare and clinically significant EV associated biomarkers in conditioned medium and patient serum samples. Furthermore, CAD-LB provides single EV characterization with small sample volumes. These qualities make CAD-LB a potentially useful tool to help discover novel markers that could aid in diagnosis and treatment decisions for cancer patients. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e183 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Thomas Osinski More articles by this author Samuel Walker More articles by this author Karen Doersch More articles by this author Jonathan Flax More articles by this author James McGrath More articles by this author Expand All Advertisement PDF downloadLoading ...

Evidence of exhausted lymphocytes after the third anti-SARS-CoV-2 vaccine dose in cancer patients.

Evidence is scant regarding the long-term humoral and cellular responses Q7 triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines in cancer patients after repeated booster doses. The possibility of T-cell exhaustion following these booster doses in this population has not yet been fully studied and remains uncertain. In this single-center prospective observational study, we explored the specific humoral and cellular response to S1 antigen in 36 patients with solid malignancies at baseline, and after the second and third doses of the mRNA-1273 vaccine. A dual behavior was observed: 24 (66.7%) patients showed partial specific IFN-γ response after the second dose that was further enhanced after the third dose; and 11 (30.5%) already showed an optimal response after the second dose and experienced a marked fall-off of specific IFN-γ production after the third (4 patients negativization), which might suggest T cell exhaustion due to repetitive priming to the same antigen. One (2.8%) patient had persistently negative responses after all three doses. Seroconversion occurred in all patients after the second dose. We then studied circulating exhausted CD8+ T-cells in 4 patients from each of the two response patterns, those with increase and those with decrease in cellular response after the third booster. The patients with decreased cellular response after the booster had a higher expression of PD1+CD8+ and CD57+PD1+CD8+ exhausted T cells compared with those with an increased cellular response both in vivo and in vitro. The proportion of PD1+CD8+ and CD57+PD1+CD8+ exhausted T cells inversely correlated with IFN-γ production. Our preliminary data show that the two-dose SARS-CoV-2 vaccine regimen was beneficial in all cancer patients of our study. An additional booster seems to be beneficial in suboptimal vaccine seroconverters, in contrast to maximal responders that might develop exhaustion. Our data should be interpreted with caution given the small sample size and highlight the urgent need to validate our results in other independent and larger cohorts. Altogether, our data support the relevance of immunological functional studies to personalize preventive and treatment decisions in cancer patients.

Potential value of the homologous recombination deficiency signature we developed in the prognosis and drug sensitivity of gastric cancer.

Background: Homologous recombination is an important DNA repair mechanism, which deficiency is a common feature of many cancers. Defining homologous recombination deficiency (HRD) status can provide information for treatment decisions of cancer patients. HRD score is a widely accepted method to evaluate HRD status. This study aimed to explored HRD in gastric cancer (GC) patients' clinical outcomes with genes related to HRD score and HRD components score [HRD-loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (NtAI)]. Methods: Based on LOH, NtAI scores, LST, and integrated HRD scores-related genes, a risk model for stratifying 346 TCGA GC cases were developed by Cox regression analysis and LASSO Cox regression. The risk scores of 33 cancers in TCGA were calculated to analyze the relationship between risk scores of each cancer and HRD scores and 3 HRD component scores. Relationship between the risk model and patient survival, BRCA1, BRCA2 mutation, response to Cisplatin and Talazoparib treatment was analyzed by generating Kaplan-Meier curve, mutations waterfall map and conducting Pearson correlation analysis. Results: An gene signature was constructed based on 11 HRD scores-related gene (BEX2, C1QL2, DKK1, DRC1, GLUD2, HCAR1, IGFBP1, NXPH1, PROC, SERPINA5, and SLCA1A2). Risk groups were stratified by risk score. Prognosis of the high-risk score group was worse than the low-risk ones. Risk score was associated with BRCA2 mutation, and patients grouped according to BRCA2 mutation status had distinguishable risk score, NtAI score, HRD-LOH, LST, and HRD scores. The low-score group showed higher sensitivity to Cisplatin and Talazoparib. The risk score of adrenocortical carcinoma (ACC), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC), kidney renal clear cell carcinoma (KIRC), sarcoma (SARC), prostate adenocarcinoma (PRAD), breast invasive carcinoma (BRCA) was significantly positively correlated with HRD score. Conclusion: We developed an 11 HRD scores-related genes risk model and revealed the potential association between HRD status and GC prognosis, gene mutations, patients' sensitivity to therapeutic drugs.

A mutation-based gene set predicts survival benefit after immunotherapy across multiple cancers and reveals the immune response landscape

BackgroundImmune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of many cancers. However, the limited population that benefits from ICI therapy makes it necessary to screen predictive biomarkers for stratifying patients. Currently, many biomarkers, such as tumor mutational burden (TMB), have been used in the clinic as indicative biomarkers. However, some high-TMB patients with mutations in genes that are closely related to immunotherapeutic resistance are not sensitive to ICI therapy. Thus, there is a need to move beyond TMB and identify specific genetic determinants of the response to ICI therapy. In this study, we established a comprehensive mutation-based gene set across different tumor types to predict the efficacy of ICI therapy.MethodsWe constructed and validated a mutational signature to predict the prognosis of patients treated with ICI therapy. Then, the underlying immune response landscapes of different subtypes were investigated with multidimensional data.ResultsThis study included genomic and clinical data for 12,647 patients. An eleven-gene mutation-based gene set was generated to divide patients into a high-risk group and a low-risk group in a training cohort (1572 patients with 9 types of cancers who were treated with ICI therapy). Validation was performed in a validation cohort (932 patients with 5 types of cancers who were treated with ICI therapy). Mutations in these 11 genes were associated with a better response to ICI therapy. In addition, the mutation-based gene set was demonstrated to be an independent prognostic factor after ICI therapy. We further explored the role of the immune context in determining the benefits of immunotherapy in 10,143 patients with 33 types of cancers and found distinct immune landscapes for the high- and low-risk groups.ConclusionsThe mutation-based gene set developed in this study can be used to reliably predict survival benefit across cancers in patients receiving ICI therapy. The close interplay between the extrinsic and intrinsic immune landscapes in the identified patient subgroups and the subgroups’ differing responses to ICI therapy could guide immunotherapy treatment decisions for cancer patients.

Abstract PO-045: Experiences of oncologists treating cancer patients living with HIV: Opportunities to improve care and reduce disparities

Abstract Introduction: Prior database studies have demonstrated that cancer patients with comorbid human immunodeficiency virus (HIV) have higher cancer-specific mortality and are less likely to receive cancer treatment. People living with HIV (PLWH) who achieve viral suppression have near normal life expectancy, highlighting the critical importance of reducing cancer treatment disparities. The purpose of this study is to understand how oncologists make treatment decisions for cancer patients living with HIV and to elicit recommendations for improving care in this population. Methods: We conducted in-depth interviews with 25 attending medical, radiation, and surgical oncologists from Duke University, University of Utah, and community practices in Florida, Georgia, Louisiana, Pennsylvania, and Virginia who had recently engaged in a consultation with PLWH and cancer. In semi-structured interviews, we explored three domains: (1) care coordination with other healthcare professionals, (2) knowledge and attitudes regarding patients with comorbid HIV and cancer, and (3) recommendations for improvements in care delivery. Two analysts coded the data using ATLAS.ti. We utilized applied thematic analysis to identify inductive themes across the three domains. Results: Many participants (n=11) reported always communicating with a patient's Infectious Disease (ID) doctor, and others (n=5) said they only communicate with ID if the patient's HIV is not well-controlled. Ten medical oncologists noted they found it helpful to speak to an HIV pharmacist, particularly about drug-drug interactions. Participants also discussed efforts to connect patients with supportive services, such as transportation, payment assistance, and mental health counseling. Many participants described concerns in discussing the patient care plan in the presence of caregivers, given the possibility that patients have not disclosed their HIV status. None of the participants had formal training in management of comorbid cancer and HIV, and most noted that they learned through their own clinical practice. Participants made suggestions for improving treatment decision-making for PLWH, including: more evidence of the risk-benefit ratio of treatment (e.g. treatment goals, life expectancy calculators), greater access to social work and mental health resources, streamlined access to communication with HIV providers, and multidisciplinary HIV cancer rounds. Conclusions: This is the first physician-focused qualitative study interviewing oncologists caring for PLWH. Communication among multiple healthcare providers, particularly oncologist and ID doctor, are noted to be common but not universal in the care of comorbid HIV and cancer. Formal training in cancers in PLWH is lacking in medical training. Future steps to reduce disparities in cancer treatment and outcomes for PLWH may include the establishment of multidisciplinary HIV cancer rounds, facilitating connection and communication between healthcare providers, and enhancing supportive care resources for patients. Citation Format: Ashley Khouri, Jeanette Young, Patrick Galyean, Brandon Knettel, Emily M. Cherenack, Anthony Ariotti, Noelani Ho, Susan Zickmund, Melissa Watt, Kathryn Pollak, Peter Ubel, Angela Fagerlin, Gita Suneja. Experiences of oncologists treating cancer patients living with HIV: Opportunities to improve care and reduce disparities [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-045.

A systematic review of the effects of positive versus negative framing on cancer treatment decision making

Objective Presenting treatment outcomes positively or negatively may differently influence treatment preferences and lead to sub-optimal decision in a medical context. This review systematically organised how positive versus negative framing of treatment outcomes influenced cancer treatment decisions of cancer patients and individuals without a cancer diagnosis. Design Three databases (PubMed, PsycInfo and Scopus) were searched for studies reporting the effects of positive versus negative framing on cancer treatment decision-making from 1981 to December 2020. Main Outcome Measure The effects of positive versus negative framing on cancer treatment preferences and the elimination of framing effect were evaluated. Results A total of 12 studies that met inclusion criteria were reviewed. Framing effect was consistently observed in individuals without a cancer diagnosis. There was not enough evidence to suggest a robust framing effect in cancer patients. Surgery was preferred in positive framing, whereas adjuvant therapy was preferred in negative framing. Justification intervention significantly eliminated framing effect. Mixed framing failed to eliminate framing effect. Conclusion Current recommendations for presenting treatment options are based on research in cancer-screening decision-making. Knowledge of how positive versus negative framing affect cancer patients’ treatment decisions is still limited. Our review highlighted the need for continued research in this area.

Ideafix: a decision tree-based method for the refinement of variants in FFPE DNA sequencing data.

Increasingly, treatment decisions for cancer patients are being made from next-generation sequencing results generated from formalin-fixed and paraffin-embedded (FFPE) biopsies. However, this material is prone to sequence artefacts that cannot be easily identified. In order to address this issue, we designed a machine learning-based algorithm to identify these artefacts using data from >1 600 000 variants from 27 paired FFPE and fresh-frozen breast cancer samples. Using these data, we assembled a series of variant features and evaluated the classification performance of five machine learning algorithms. Using leave-one-sample-out cross-validation, we found that XGBoost (extreme gradient boosting) and random forest obtained AUC (area under the receiver operating characteristic curve) values >0.86. Performance was further tested using two independent datasets that resulted in AUC values of 0.96, whereas a comparison with previously published tools resulted in a maximum AUC value of 0.92. The most discriminating features were read pair orientation bias, genomic context and variant allele frequency. In summary, our results show a promising future for the use of these samples in molecular testing. We built the algorithm into an R package called Ideafix (DEAmination FIXing) that is freely available at https://github.com/mmaitenat/ideafix.

Identification and management of pathogenic mutations in BRCA1, BRCA2, and PALB2 in a tumor-only genomic testing program.

10528 Background: Tumor-genomic testing is increasingly used to guide treatment decisions in cancer patients. Although tumor-only testing cannot definitively distinguish between germline versus somatic alterations, the identification of pathogenic or likely pathogenic (P/LP) variants in certain genes should prompt consideration of germline testing. Germline P/LPs in BRCA1, BRCA2 and PALB2 ( B1B2PAL) are associated with hereditary cancer syndromes. Methods: We reviewed tumor-only genomic data (Dana-Farber Oncopanel) between 10/2016 and 6/2018 to examine the prevalence of P/LPs in BRCA1, BRCA2, PALB2 among adult cancer patients at Dana-Farber Cancer Institute/Brigham and Women’s Hospital. We characterized the frequency of P/LPs by primary tumor type, confirmation by germline testing before or within 12 months after Oncopanel testing or not, and factors associated with germline testing. Results: Among 7,575 patients, the median age was 62 (range 18-99); 53.9% were female. A total of 272 (3.6%) had P/LPs in BRCA1 (n = 90), BRCA2 (n = 162) and/or PALB2 (n = 29). P/LPs in B1B2PAL were detected in 5.3% (38/712) of breast, 11.9% (34/285) of ovarian, 6.6% (18/272) of pancreatic, and 5.1% (12/234) of prostate cancers. P/LPs in B1B2PAL were also detected in other neoplasms (12.9% (8/62) of non-melanoma skin, 5.0% (43/855) of colorectal, 7.6% (20/264) of endometrial, and 4.6% (10/216) of head and neck cancers). Of 169 patients who had not had prior germline testing, 29/169 (17.2%) completed germline testing within 12 months after Oncopanel; 13 (7.7%) referred for testing declined or did not complete testing within 12 months, 14 (8.3%) died before or within 3 months of the Oncopanel results, and 113 (66.9%) had no documented germline testing within 12 months. Among 132 patients who had germline testing, 117 (88.6%) had a clinical indication based on personal or family history compared to 66/140 (47.1%) who did not undergo germline testing. Among 132/272 (48.5%) germline-tested patients, 70.5% were positive for a germline mutation in B1B2PAL; the remainder had somatic B1B2PAL mutations only. Germline testing was more often performed in patients with B1B2PAL-associated tumors (breast, ovarian, pancreatic and prostate cancers) or other clinical indications for germline testing. Conclusions: A low but clinically meaningful rate of P/LPs in BRCA1, BRCA2 and PALB2 was detected by tumor-only genomic testing in diverse malignancies. Given the implications of B1B2PAL alterations on treatment and familial cancer risk, our data support current NCCN guidelines recommending germline testing among patients with cancer and P/LPs in B1B2PAL detected on tumor-genomic testing and highlights the need for systems to ensure germline testing when indicated.

Abstract P28: COVID-19 infection and mortality in patients with skin malignancies receiving systemic anti-cancer therapy (SACT): The Guy’s Cancer Centre experience

Abstract Background: The COVID-19 pandemic has influenced treatment decisions in cancer patients. There is increasing evidence that not all oncology patients are at increased risk of COVID-19 infection or death. This study aimed to look at rate of SARS-CoV-2 infection and mortality in patients with skin malignancies receiving systemic anti-cancer therapy (SACT) during the pandemic in Guy’s Cancer Centre. Methods: All patients with skin cancer receiving SACT at Guy’s Cancer Centre between March 1st and May 31st 2020 were included. Demographic data: sex, age, socio-economic status (SES), ethnicity, comorbidities, medications and smoking history were collected along with cancer characteristics: cancer type, stage, treatment paradigm, modality and line. COVID-19 infection was confirmed by PCR and severity defined by the World Health Organisation classification. Patients with radiological or clinical diagnoses alone were excluded. Results: Of 116 skin cancer patients on SACT over the 3-month period, 89% had Melanoma, 5% Kaposi’s Sarcoma (KS), 3% Squamous Cell, 2% Merkel Cell, 1% Basal Cell Carcinoma and 1% Angiosarcoma. 53% were male and 78% were of low SES. 62% were being treated with palliative intent and 70% of these were on first line palliative treatment. The median age was 57.6 years in COVID-19 positive patients (n=3) compared to 60.3 years in the negative group (n=113). 58.6% received immunotherapy, 28.4% targeted therapy, 7.8% chemotherapy and 4.3% combined treatment. Of the 3 patients (2.6%) with confirmed COVID-19 infection, the two patients with KS were receiving liposomal doxorubicin hydrochloride and the other paclitaxel chemotherapy and the patient with Melanoma was receiving encorafenib and binimetinib. All COVID-19 positive patients were of low SES, 2 females and 1 male. There was a low rate of co-morbidities with hypertension in 1 COVID-19 positive patient and none in the negative group. All 3 confirmed COVID-19 patients developed severe pneumonia and were diagnosed within 7 days of the onset of symptoms. There were no COVID related deaths and one disease-related death in the negative cohort. Conclusion: There was a low rate of COVID-19 infection in the 116 skin cancer patients on SACT (2.6%) with 60% of patients on immunotherapy. All 3 confirmed cases had severe pneumonia with no COVID-19 related deaths (0%); 2 were receiving chemotherapy and 1 on targeted therapy. Patients on treatment were encouraged to shield between hospital attendances during this period which may account for the reduced rate of SARS-CoV-2 infection. This data supports the emerging observations that immunotherapy does not confer an increased risk of severe COVID-19 infection in cancer patients. This observation is confounded by the relatively young age and low co-morbidity rates in the cohort which may have contributed to the low infection and mortality rate. Citation Format: Lucy Flanders, Beth Russell, Charlotte Moss, Kieran Palmer, Rushan Sylva, Gincy George, Danielle Crawley, Harriet Wylie, Fidelma Cahill, Anna Haire, Andrea D'Souza, Simon Gomberg, Richard Sullivan, Anne Rigg, Mieke Van Hemelrijck, Mark Harries, Irene De Francesco, Stephen Morris, Sophie Papa, Saiorse Dolly. COVID-19 infection and mortality in patients with skin malignancies receiving systemic anti-cancer therapy (SACT): The Guy’s Cancer Centre experience [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2021 Feb 3-5. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(6_Suppl):Abstract nr P28.

Abstract P4-14-05: A systematic review of concordance studies using Watson for Oncology (WfO) to support breast cancer treatment decisions: A four-year global experience

Abstract Background: Watson for Oncology (WfO) is an artificial intelligence (AI)-based clinical decision-support system (CDSS) that presents personalized therapeutic options to support cancer-treating physicians in making treatment decisions for cancer patients. WfO was released in 2015, and it has been deployed in over 200 institutions across the world. Many academic centers have examined WfO’s performance by measuring concordance between WfO therapeutic options and treatment recommendations by multidisciplinary tumor boards (MTBs) or individual clinicians (ICs). This study systematically reviewed the results of such concordance studies for breast cancer. Methods: We conducted a review of the WfO publication database and a PubMed search to identify WfO concordance studies in breast cancer patients, published from 01/01/2015 to 06/30/2019. Studies were excluded if they measured concordance for multiple cancer types but did not include individual concordance for breast cancer. Concordance was defined as agreement between WfO “Recommended” and “For Consideration” treatment options and treatments prescribed by MTBs or ICs. Mean concordance rates were calculated as an average, weighted by the number of patients in each study. Concordance rates between MTBs and ICs were compared with z-test of two proportions. Subgroup analyses for larger studies were summarized. Results: Table 1 presents the results of nine identified breast cancer concordance studies (4,427 patients) from China, India, and Thailand. Five studies (1,528 patients) determined concordance with MTB and 4 (2,899 patients) with ICs. WfO treatment options were compared to historical treatment recommendations by MTBs and ICs. Mean concordance for all studies was 70.8% (range 55 - 98%). Mean concordance with MTBs of 90.7% (range 79 - 98%) was significantly higher than the concordance between WfO and ICs of 59.9% (range 55-76%) p<0.0001. Table 1Study/LocationNumber of patientsConcordance Multidisciplinary Tumor Board Studies (MTBs)Zhang XC, et al. Ann Oncol 2017;28:x170 / China11979%Yue L, Yang L. Ann Oncol 2017;28:x162 / China3198%Somashekhar SP, et al. Ann Oncol 2018 1; 29(2):418-423 / India63893%Zhou N, et al. The Oncologist 2018;23:1-8 / China12082%Somashekhar SP, et al. J Clin Oncol 2019; 37 (suppl; abstr 6533) / India62092%MTB subtotals152890.7%Individual Clinicians Studies (ICs)Suwanvecho S, et al. J Clin Oncol 2017;35 (suppl; abstr 6589) / Thailand21176%Jiang Z, et al. J Clin Oncol 2018;36 (suppl; abstr 18566) / China1,99755%Suwanrusme H, et al. J Clin Oncol 2018;36 (suppl; abstr 18584) / Thailand26470%32672%Suwanvecho S et al. J Clin Oncol 2019; 37 (suppl; abstr 6553) / Thailand10160%ICs subtotals289959.9% Mean concordance in China, Thailand and India were 78.5%, 69.5%, and 92.5%, respectively. A large IC study from China including 1,997 patients found concordance in triple negative, high risk non-metastatic, and metastatic breast cancers of 69%, 66%, and 50%, respectively. A MTB study from China in 120 patients found concordance for luminal A, luminal B and triple negative breast cancers of 63%, 87% and 79%, respectively. Reported reasons for discordance varied among studies and included locally unavailable treatments, individual physician or MTB management preferences, and age older than 75 years. Conclusions Overall concordance between the WfO therapeutic options and decisions of both MTBs and ICs was high, demonstrating performance comparable with experts across the world. Higher concordance was observed between WfO and MTBs versus WfO and ICs, likely reflecting the multidisciplinary expertise having greater agreement with evidence and guideline-based recommendations of WfO than decisions of individual clinicians. This finding illustrates a role for clinical decision support in practice. Concordance varied across countries, reflecting the need for localization to address regional differences in practice. Citation Format: Yull Arriaga, Rezzan Hekmat, Karlis Draulis, Suwei Wang, Winnie Felix, Irene Dankwa-mullan, Kyu Rhee, Gretchen Jackson. A systematic review of concordance studies using Watson for Oncology (WfO) to support breast cancer treatment decisions: A four-year global experience [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-14-05.

Assessment of the Utility of Gene Positioning Biomarkers in the Stratification of Prostate Cancers

There is a pressing need for additional clinical biomarkers to predict the aggressiveness of individual cancers. Here, we examine the potential usefulness of spatial genome organization as a prognostic tool for prostate cancer. Using fluorescence in situ hybridization on formalin-fixed, paraffin embedded human prostate tissue specimens, we compared the nuclear positions of four genes between clinically relevant subgroups of prostate tissues. We find that directional repositioning of SP100 and TGFB3 gene loci stratifies prostate cancers of differing Gleason scores. A more peripheral position of SP100 and TGFB3 in the nucleus, compared to benign tissues, is associated with low Gleason score cancers, whereas more internal positioning correlates with higher Gleason scores. Conversely, LMNA is more internally positioned in many non-metastatic prostate cancers, while its position is indistinguishable from benign tissue in metastatic cancer. The false positive rates were relatively low, whereas, the false negative rates of single or combinations of genes were high, limiting the clinical utility of this assay in its current form. Nevertheless, our findings of subtype-specific gene positioning patterns in prostate cancer provides proof-of-concept for the potential usefulness of spatial gene positioning for prognostic applications, and encourage further exploration of spatial gene positioning patterns to identify novel clinically relevant molecular biomarkers, which may aid treatment decisions for cancer patients.

Preferences to Receive Unsolicited Findings of Germline Genome Sequencing in a Large Population of Cancer Patients

Background: In precision medicine, somatic and germline DNA sequencing are essential to make genome-guided treatment decisions in cancer patients. However, it can also uncover unsolicited findings (UFs) in germline DNA that could have a substantial impact on the lives of patients and their relatives. It is therefore critical to understand cancer patients' preferences concerning UFs derived from whole-exome (WES) or whole-genome sequencing (WGS). Methods: In a quantitative multi-center study, adult cancer patients (any stage and origin of disease) were surveyed through a digital questionnaire based on previous semi-structured interviews. Background knowledge was provided by showing two videos, introducing basic concepts of genetics and general information about different categories of UFs (actionable, non-actionable, reproductive significance, unknown significance). Findings: In total 1072 patients were included of whom 701 participants completed the whole questionnaire. Overall, 686 (85.1%) participants wanted to be informed about UFs in general. After introduction of four UFs categories, 113 participants (14.8%) changed their answer: 718 (94.2%) participants opted for actionable variants, 537 (72.4%) for non-actionable variants, 635 (87.0%) participants for UFs of reproductive significance and 521 (71.8%) for UFs of unknown significance. Men were more interested in receiving certain UFs than women: non-actionable: OR 3.32; 95% CI 2.05 - 5.37, reproductive significance: OR 1.97; 95% CI 1.05 - 3.67 and unknown significance: OR 2.00; 95% CI 1.25 - 3.21. In total 244 (33%) participants conceded family members to have access to their UFs while still alive. 603 (82%) participants agreed to information being shared with relatives, after they would pass away. Interpretation: Our study showed that the vast majority of cancer patients desires to receive all UFs of genome testing, although a substantial minority does not wish to receive non-actionable findings. Incorporation of categories in informed consent procedures supports patients in making informed decisions on UFs. Funding Statement: This work was supported by the Dutch Cancer Foundation (KWF) [grant UU2014-7469]. Declaration of Interests: The authors have declared no conflicts of interest. Ethics Approval Statement: The research protocol was approved by the Research Ethics Committee of the University Medical Center Utrecht (The Netherlands), and informed consent was obtained from all participants

Providing guidance for genomics-based cancer treatment decisions: insights from stakeholder engagement for post-prostatectomy radiation therapy

BackgroundDespite the emergence of genomics-based risk prediction tools in oncology, there is not yet an established framework for communication of test results to cancer patients to support shared decision-making. We report findings from a stakeholder engagement program that aimed to develop a framework for using Markov models with individualized model inputs, including genomics-based estimates of cancer recurrence probability, to generate personalized decision aids for prostate cancer patients faced with radiation therapy treatment decisions after prostatectomy.MethodsWe engaged a total of 22 stakeholders, including: prostate cancer patients, urological surgeons, radiation oncologists, genomic testing industry representatives, and biomedical informatics faculty. Slides were at each meeting to provide background information regarding the analytical framework. Participants were invited to provide feedback during the meeting, including revising the overall project aims. Stakeholder meeting content was reviewed and summarized by stakeholder group and by theme.ResultsThe majority of stakeholder suggestions focused on aspects of decision aid design and formatting. Stakeholders were enthusiastic about the potential value of using decision analysis modeling with personalized model inputs for cancer recurrence risk, as well as competing risks from age and comorbidities, to generate a patient-centered tool to assist decision-making. Stakeholders did not view privacy considerations as a major barrier to the proposed decision aid program. A common theme was that decision aids should be portable across multiple platforms (electronic and paper), should allow for interaction by the user to adjust model inputs iteratively, and available to patients both before and during consult appointments. Emphasis was placed on the challenge of explaining the model’s composite result of quality-adjusted life years.ConclusionsA range of stakeholders provided valuable insights regarding the design of a personalized decision aid program, based upon Markov modeling with individualized model inputs, to provide a patient-centered framework to support for genomic-based treatment decisions for cancer patients. The guidance provided by our stakeholders may be broadly applicable to the communication of genomic test results to patients in a patient-centered fashion that supports effective shared decision-making that represents a spectrum of personal factors such as age, medical comorbidities, and individual priorities and values.

Abstract 3926: Nanomechanical profiling of breast cancer: A novel tool for cancer diagnostics and prognostics

Abstract A crucial point in making treatment decisions for cancer patients is the assessment of tumor aggressiveness. Currently, for breast cancer, established prognostic markers exist that are routinely assessed by standard pathological examination. However, these parameters are often not sufficient to stratify patients, especially those with early stages of breast cancer and adjuvant therapy is frequently administered to patients who might have been cured by surgery and anti-hormonal treatment alone. The goal to avoid over- and under-treatment has led to an intensive search for prognostic and predictive markers in early breast cancer. Physical interactions between cancer cells and the extracellular matrix (ECM) that occur at the molecular (nanometer) scale are crucial for the metastatic process. Consequently, nanomechanical alterations of cells and ECM due to cancer progression can serves as potentially suitable markers of cancer aggressiveness that may help to optimize treatment strategies. This motivated us to develop an atomic force microscope (AFM)-based method for measuring nanomechanical (stiffness) profiles of unadulterated tissues in native physiological buffer conditions with an unprecedented stiffness sensitivity resolved at nanometer-scale spatial resolution. An AFM utilizes a ∼10 nm-sharp stylus or tip that makes ∼10’000 miniscule indentations across tissue. In our initial study using transgenic mouse model of human breast cancer we could show that the “softest” nanomechanical phenotype (∼0.4 - 0.8 kPa) present at the primary tumor site closely corresponded to the stiffness of the metastatic lesions obtained from the lungs of the same mouse (Plodinec et. al; Nature Nanotech. 2012). In this study, we have analyzed human 187 breast cancer samples from breast biopsies and tumor resections including primary breast cancers of various stage and grade, lymph node metastases, and non-neoplastic breast parenchyma. Post-AFM samples were fixed, paraffin embedded in an oriented manner and used for routine histology. Data showed for all human breast cancer samples, distinct stiffness phenotypes in comparison to the surrounding non-neoplastic and morphologically normal breast tissue and revealed specific nanomechanical profiles of phenotypes that lead to metastases. Interestingly, patients presenting nanomechanical changes in the adjacent tissue, which was histologically characterized as tumor free, typically exhibited local and/or distant metastases. Overall, our findings demonstrate the first application of nanomechanical profiling in a clinical setting that allows for fast, on-site assessment of specimen and does not suffer from inter-observer variability such as other markers (Obermann et al, Pathologe, 2012). The relative size and distribution of nanomechanical profiles can provide an indicator of cancer aggressiveness, and therefore orientate therapy choice, and support patient follow-up. Citation Format: Marija Plodinec, Christian Raez, Philipp Oertle, Adrian Hodel, Maja Fünfschilling, Roderick YH Lim, Ellen C. Obermann. Nanomechanical profiling of breast cancer: A novel tool for cancer diagnostics and prognostics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3926.

New Gene Profiling in Determination of Breast Cancer Recurrence and Prognosis in Iranian Women

Breast cancer (BC) is the second most common cancer in the world and by far the most frequent cancer among women, with an estimated 1.67 million new cancer cases diagnosed in 2012 (25% of all cancers). Polygene expression analysis is used to predict the prognosis and determine the most appropriate treatment regimen. The objective of this study was to examine the gene expression profiles of SIRT3, HRAS, LSP1, SCUBE2 and AP2A2 in Iranian women with BC.A total of 136 patients including healthy controls were categorized into three groups based on the relapse of the disease. Expression of desired genes in formalin-fixed, paraffin embedded tissues collected from all groups of participants was analyzed via the RT PCR method. RNA extraction and cDNA synthesis were performed then real-time quantitative PCR was carried out. Gene expression analysis revealed that the expression of SIRT3 was equal among patient and control groups. LSP1 was down regulated in all patient groups relative to controls but reduced expression in the metastatic group relative to the non-metastatic one was not significant. HRAS was significantly overexpressed in total and metastatic tumor samples versus normal but not in non-metastatic cases. SCUBE2 expression showed significant over-expression in both overall tumor samples and the non-metastatic group as compared to normal tissues. Gene expression level of AP2A2 in all groups was not detectable. Our data are compatible with a tumor suppressor role of LSP1 related to potential prognostic factor for tumor recurrence and outcome. This study for the first time assayed the prognostic value and changes in the expression of SIRT3, LSP1, HRAS, SCUBE2 and AP2A2 genes in women with breast cancer in the Iranian population and findings confirmed potential biomarker and prognostic capability of these genes. Such expression profiling data can critically improve prognosis and treatment decisions in cancer patients.

Clinical applications of next generation sequencing in cancer: from panels, to exomes, to genomes.

This article will review recent impact of massively parallel next-generation sequencing (NGS) in our understanding and treatment of cancer. While whole exome sequencing (WES) remains popular and effective as a method of genetically profiling different cancers, advances in sequencing technology has enabled an increasing number of whole-genome based studies. Clinically, NGS has been used or is being developed for genetic screening, diagnostics, and clinical assessment. Though challenges remain, clinicians are in the early stages of using genetic data to make treatment decisions for cancer patients. As the integration of NGS in the study and treatment of cancer continues to mature, we believe that the field of cancer genomics will need to move toward more complete 100% genome sequencing. Current technologies and methods are largely limited to coding regions of the genome. A number of recent studies have demonstrated that mutations in non-coding regions may have direct tumorigenic effects or lead to genetic instability. Non-coding regions represent an important frontier in cancer genomics.

Prediction of Treatment Effects for Individual Cancer Patients Using Data from Randomized Clinical Trials

ABSTRACT Aim: Results from randomized clinical trials (RCTs) evaluating the efficacy of chemotherapy are typically reported as relative risk or difference in median survival on a group level. Patients are most interested in their personal expected absolute treatment effect. Translating group level estimates to individual patients in clinical practice is challenging, as absolute treatment effects can vary substantially among individuals. We propose a method for individualized treatment effect prediction using data from RCTs, to identify cancer patients who benefit from specific treatments. Methods: Data from the NVALT7 study, a randomized phase II trial comparing pemetrexed (P) with P plus carboplatin (C) in 240 patients with non-small cell lung cancer relapsing after platinum based chemotherapy (Smit et al. J. Clin. Oncol. 2009), were analyzed. Cox proportional hazards models, including routinely available patient and tumor characteristics, were developed for individualized prediction of the absolute effects of adding C to P in terms of absolute increase in overall survival (OS), progression free survival (PFS) and risk of grade 3/4 toxicity. Models were internally validated and an external validation in the GOIRC 02 2006 randomized phase II study is planned. Results: The predicted individual benefit in OS of adding C to P ranged from -1.2 to 10.8 months. Patients with squamous tumors, particularly those with better performance status, lower leucocyte count and longer treatment free interval, had the highest predicted median OS benefit from addition of C (3.2 months ), though with a wide range (1.4 to 10.8 months). The difference in predicted PFS for individuals ranged from 0.1 to 3.2 months. Internal validation showed a satisfactory model calibration and discrimination (c-index: 0.69/0.65 for OS/PFS). The predicted absolute risk increase (ARI) of toxicity with addition of C was similar in patients with ≤3 months predicted OS (ARI 5.0%) and those with longer predicted OS (ARI 5.2%). Conclusions: Data from RCTs may be used to predict absolute treatment effects for individual patients before start of therapy. Individualized treatment effect predictions from validated models may guide treatment decisions in cancer patients by identifying those who benefit most in terms of OS and PFS and have low risk of toxicity. Disclosure: E.F. Smit: EFS has received honoraria from Eli Lilly. All other authors have declared no conflicts of interest.

Multidisciplinary cancer care: does it improve outcomes?

Multidisciplinary care has been advocated as a solution for increasingly complex treatment decisions in cancer patients. The impact of multidisciplinary care on patient survival has been studied, but evidence is limited by poor methodological quality. Lack of conclusive evidence for increased survival is balanced against improvements in quality of care, guideline adherence, reduction in wait times, and greater satisfaction for patients and care providers.