Symptoms and General Pathology

All Conditions

Recurrence

Antineoplastic Agents

All Drugs and Chemicals

Immune Checkpoint Inhibitors

Immunomodulating Agents

Momchilo Vuyisich, PhD

Ryan Toma, MS

Jessica Chestnut

Nathalie McKenzie, MD

Robert Holloway, MD

James Kendrick, MD

30 participants with advanced or recurrent gynecological cancer from are enrolled for this study. Eligible participants then provide fecal specimen, blood, vaginal swab, oral mucosal swab and receive food dietary recommendation. Additional samples are collected for results analysis.

30 patients diagnosed with advanced or recurrent gynecological cancer who plan to receive immunotherapy treatment with a checkpoint inhibitor at AHMG AdventHealth Orlando Gynecological Oncology Group are recruited. Patients will be recruited 1-2 weeks prior to the beginning of treatment and appropriate informed consent will be obtained. Fecal samples; blood; saliva and vaginal swab samples will be collected among participants prior to their first treatment, after four doses of immunotherapy, and again at the completion of immunotherapy (follow-up). These 4 biomarker samples will undergo metatranscriptomic analysis, also known as RNAseq, method of sample analysis. Only RNA molecules are sequenced, while DNA is degraded. for bacterial community analysis. These findings will help to design a future study to examine the role of the gut microbiome in antitumor immunity and its effect on immune checkpoint inhibitor therapy for advanced or recurrent gynecological cancer. NHANES Food Frequency Questionnaire will be collected prior to participants' first treatments.

The short-term goals of this pilot study are to obtain preliminary data on the gut bacterial microbiome of patients with advanced or recurrent gynecological cancer. The long-term goals of this study is to begin to understand how the gut microbiome changes within an individual patient undergoing immunotherapy, to gut microbiome differs among patients undergoing immunotherapy, and to examine whether the gut microbiome is associated with the response to cancer immunotherapy.

Only RNA molecules are sequenced, while DNA is degraded. The AdventHealth Research Laboratory will process the de-identified blood samples and store; Plasma, Serum and Buffy Coat for future analysis. The Advent Health Research Laboratory will store these samples in the biorepository, inventory and chain of custody will be managed by the STARLIMS program.

Gut Microbiome and Treatment for Gynecological Cancer Patients Receiving Immunotherapy

Pilot Feasibility Study of the Interplay Between the Host Gut Microbiome and Efficacy of Treatment for Advanced or Recurrent Gynecological Cancer Patients Receiving Immunotherapy

Changes are measured between the genetic microbiome signatures of advanced or recurrent gynecological cancer patients who are receiving immune checkpoint inhibitors.

AdventHealth

Viome

Neoplasms

Respiratory Tract (Lung and Bronchial) Diseases

Carcinoma, Non-Small-Cell Lung

Lung Neoplasms

Carcinoma

Carcinoma, Bronchogenic

Bronchial Neoplasms

Respiratory Tract Neoplasms

Thoracic Neoplasms

Lung Diseases

Respiratory Tract Diseases

All patients included in Explore ALK GFPC 03-2019 study who agree to participate in Bioexalk.

1. Tissue : RNAseq will be performed on tumor biopsy (10 slides of 5 microns) to identify the ALK fusion partner and its variant and associated co-mutations.
2. ctDNA : NGS panel on DNA including a large panel of fusions and mutations will be performed on blood samples

RNAseq

Florian GUISIER

Aurélie SWALDUZ

Diane MOREAU

Géraldine FRANCOIS

Julian PINSOLLE

Lise THIBONNIER

Marie MARCQ

Cécile DUJON

Olivier MOLINIER

Eric DANSIN

Alexis CORTOT

Pierre BOMBARON

Karima SABOUNDJI

Anne MADROSZYK

Camille TRAVERT

Karim AMRANE

Hugues H MOREL

Catherine DANIEL

Aldo RENAULT

Gwenaelle LE GARFF

Hélène DOUBRE

Jean-Michel PELONI

Clarisse AUDIGIER VALETTE

Olivier BYLICKI

Gonzague DE CHABOT

Benjamin BESSE

Alexa MAIROVITZ

Nicolas DELBERGHE

Christos CHOUAID

BioEXALK is a prospective study evaluating the biological characteristics of advanced ALK-rearranged NSCLC treated with next generation TKIs in first line, included in the national EXPLORE ALK cohort (GFPC 03-2019), a non-interventional, national, multi-center cohort of ALK-rearranged NSCLC patients.

BioExALK study will be proposed to every patient included in the Explore ALK GFPC 03-2019 study.

Biological analysis will be performed on tumor tissue at diagnosis and at the time of disease progression when available and on circulating tumor DNA (ctDNA).

For plasma testing, after obtained patient consent, blood samples will be taken and analyzed at the Léon Bérard Center (Lyon).

Biological analysis on tissue obtained at diagnosis and at disease progression will be collected and be sent for centralized analysis to the Rouen University Hospital.

BioEXALK is a prospective study evaluating the biological characteristics of advanced ALK-rearranged NSCLC treated with new generation TKIs in first line, included in the national EXPLORE ALK cohort (GFPC 03-2019).

Explore ALK GFPC 03-2019 is a non-interventional, national, multi-center cohort of ALK-rearranged NSCLC patients, whose RCB reference is 2020-A00771-38 and which obtained an approval from the IDF II Ethic Committee on 25/05/2020. Biological analysis will be performed on tissue at diagnosis and at the time of disease progression when available and on circulating tumor DNA (ctDNA) on three timepoints (diagnosis, at first tumor evaluation and at the time of disease progression).

* Tissue : RNAseq will be performed on tumor biopsy (10 slides of 5 microns) to identify the ALK fusion partner and its variant and associated co-mutations..
* ctDNA : NGS panel on DNA including a large panel of fusions and mutations will be performed on blood samples (30mL on EDTA or STRECKs tubes) at diagnosis, at the time of the first evaluation and at the time of progression).

For plasma testing, after obtained patient consent, blood samples (35mL on EDTA or STRECKs tubes) at diagnosis, at the first evaluation and at disease progression will be taken.

The ALKis include alectinib and brigatinib as first-line therapy or other drugs with marketing authorizations (lorlatinib, entrectinib) or in early access programs (EAPs).

Liquid biopsies will be analyzed with a NGS panel allowing the identification of ALK fusion partners and resistance mechanisms (mutations, fusions, copy number variations). Samples will be sent for centralized analysis to the Léon Bérard Center (Lyon).

For biological analysis on tissue obtained at diagnosis, the ALK fusion partner and its variant will be identified by RNAseq. Whenever a tissue re-biopsy is performed at the time of disease progression as part of the standard of care management of the patient, the remaining tissue sample will be collected as part of the BioExALK study, so that RNAseq analysis will be performed to look for resistance mechanisms. Tissue samples (10 slides of 5 microns) will be sent for centralized analysis to the Rouen University Hospital.

Analysis of Biological Characteristics of Advanced ALK-rearranged NSCLC

Biological Characterization of Advanced ALK-rearranged Non-small Cell Lung (NSCLC) Cancer Included in EXPLOREALK Study

PFS assessed by local review using RECIST v1.1, defined as time from treatment initiation to the first clinical or radiological progression or death from any cause

OS defined as time from treatment initiation to death from any cause.

DoR assessed by local review using RECIST v1.1, defined as time from treatment initiation to the first clinical or radiological progression, death, consent withdrawn, adverse event, protocol deviations, lost to follow-up, or initiation of a new line of anticancer therapy.

ORR defined as objective response rate of complete response or partial response measured by local review RECIST v1.1.

ctDNA clearance will be determine as clearance of the fusion when detectable and/or clearance of relevant mutations when fusion not detected

The following mechanisms of resistance will be assessed: secondary mutations on ALK, mutations or translocations on other genes of interest, histological transformations

ALK fusion partner and co-mutation identifications based on liquid and tissue biopsies at Baseline

Takeda

Groupe Francais De Pneumo-Cancerologie

Patients receiving target drugs with the score value above 0,1 as monotherapy or in combination

Patients receiving only non-target drugs or target drugs with the score value equal to or below 0,1 as monotherapy or in combination

Next Generation Sequencing of RNA from tumor samples, rRNA-depleted.

RNA sequencing

Analysis of RNA-seq data using the Oncobox algorithm.

Transcriptome analysis

target drug with the score above 0,1

target drug with the score equal or below 0,1

non-target drug

palliative care

Anton A Buzdin, Ph.D., D.Sc

This is a prospective trial for a computation-based efficacy prediction method for anticancer target therapies. The original computational algorithm utilizes individual transcriptome data of a cancer sample and assesses changes at the level of gene expression and intracellular signaling pathways. By applying the database of known molecular targets of anticancer target drugs it allows to rank potential efficacies of target drugs.

Original computational algorithm Oncobox was developed to determine molecular features of individual tumors. It represents the solution for a personalized selection of target anticancer therapies. The method is based on the analysis of gene expression profile of a cancer sample in comparison with the corresponding normal tissue biosamples in order to select the most effective molecular targets for their inhibition and, accordingly, to identify more effective target drugs for cancer treatment. Histological material obtained from cancer patients during surgery or core-needle biopsy as part of standard treatment will be used for the analysis. Total RNA extracted from the tumor material will be subjected to next-generation sequencing (NGS). By comparing transcriptome profile of the tumor sample with the profiles of the corresponding normal tissue samples the rate of molecular pathways activation/deactivation will be calculated, as well as the case-to-normal ratios for the individual gene products - molecular targets of drugs. Based on these data, each target drug will be assigned with a score reflecting its potential efficacy for each individual tumor treatment. A drug with the score value above 0.1 will be considered potentially effective, a drug with the score value equal to or below 0.1 - as potentially ineffective. Following Oncobox test, 130 target anticancer drugs will be rated according to their predicted effectiveness (see the list of eligible target drugs below). This information will be fully available to a patient and his/her doctor. The doctor will prescribe treatment according to his/her consideration, e.g. based on the standards of care and the patient's life indications. After the appointment of therapy, the patients will be divided naturally into the following three observation groups. The first group will be formed from patients receiving target drugs with the score value above 0,1 as monotherapy or in combination. The second group - patients receiving only non-target drugs or target drugs with the score value equal to or below 0,1 as monotherapy or in combination. Third group will be formed by patients receiving palliative care. Within this study, these three groups will be compared by response to the therapy according to the results of instrumental studies, by time to progression and by time to progression compared to the previous line of therapy (if any). Additionally, overall survival will be measured in all three groups.

Eligible target drugs:

1. Abemaciclib (LY2835219)
2. Afatinib
3. Aflibercept
4. Alectinib
5. Alemtuzumab
6. Alitretinoin
7. Anastrozole
8. Apalutamide, ARN-509
9. Arsenic trioxide
10. Atezolizumab
11. Avelumab
12. Axitinib
13. Belinostat
14. Bevacizumab
15. Bexarotene
16. Bicalutamide
17. Binimetinib (MEK162)
18. Blinatumomab
19. Bortezomib
20. Bosutinib
21. Brentuximab vedotin
22. Brigatinib
23. Cabazitaxel
24. Cabozantinib
25. Carfilzomib
26. Ceritinib (Zykadia, LDK378)
27. Cetuximab
28. Cobimetinib
29. Crizotinib
30. CYT387 (Momelotinib)
31. Dabrafenib
32. Daratumumab
33. Dasatinib
34. Degarelix
35. Denileukin diftitox (Ontac)
36. Denosumab
37. Docetaxel
38. Dovitinib
39. Durvalumab
40. Elotuzumab
41. Encorafenib
42. Enzalutamide
43. Erlotinib
44. Estramustine
45. Everolimus
46. Exemestane
47. Flavopiridol (Alvociclib)
48. Foretinib
49. Fulvestrant
50. Ganetespib (STA-9090)
51. Gefitinib
52. Goserelin
53. Homoharringtonine (Omacetaxine mepesuccinate)
54. Ibritumomab tiuxetan
55. Ibrutinib
56. Idelalisib
57. Imatinib
58. Inotuzumab ozogamicin
59. Ipilimumab
60. Ixabepilone
61. Ixazomib (MLN9708)
62. Lapatinib
63. Lenalidomide
64. Lenvatinib
65. Letrozole
66. Leuprolide
67. Lomustine
68. Masitinib
69. Medroxyprogesterone acetate (MPA)
70. Megestrol
71. Methyltestosterone
72. Midostaurin
73. Mogamulizumab
74. Moxetumomab pasudotox
75. Necitumumab
76. Nilotinib
77. Nilutamide
78. Nimotuzumab
79. Nintedanib (BIBF 1120)
80. Niraparib
81. Nivolumab (BMS-936558)
82. Obinutuzumab
83. Ofatumumab
84. Olaparib
85. Olaratumab
86. Osimertinib
87. Paclitaxel
88. Palbociclib
89. Panitumumab
90. Panobinostat
91. Pazopanib
92. Pembrolizumab
93. Perifosine
94. Pertuzumab
95. Pomalidomide
96. Ponatinib
97. Ramucirumab (Cyramza)
98. Regorafenib
99. Ribociclib
100. Rigosertib
101. Rituximab
102. Romidepsin
103. Rucaparib
104. Ruxolitinib
105. Selumetinib
106. Siltuximab
107. Sonidegib (LDE225)
108. Sorafenib
109. Sunitinib
110. Tamoxifen
111. Tecemotide (Emepepimut-S, L-BLP25)
112. Temozolomide
113. Temsirolimus
114. Thalidomide
115. Tivantinib
116. Tivozanib
117. Toremifene
118. Trametinib (Mekinst)
119. Trastuzumab
120. Trebananib
121. Vandetanib
122. Veliparib
123. Vemurafenib
124. Venetoclax
125. Vinblastine
126. Vincristine
127. Vindesine
128. Vinorelbine
129. Vismodegib
130. Vorinostat

Formalin-fixed, paraffin-embedded pathological cancer samples obtained during surgery or core needle biopsy

Identification of Molecular Biomarkers for Cancer Target Therapy Efficacy

Study Protocol, Statistical Analysis Plan (SAP), NGS data, Clinical Study Report (CSR)

Tumor response according to the results of instrumental studies

Time to progression compared to the previous therapy lane

Oncobox Ltd

Vitamed LLC

N.N. Blokhin National Medical Research Center of Oncology

Kaluga Regional Clinical Oncology Center

Multidisciplinary medical holding SM-Clinic

Oncological Clinical Dispensary No. 1 of the Moscow City Health Department

OmicsWay Corp.

Skin and Connective Tissue Diseases

Breast Neoplasms

Breast Diseases

Skin Diseases

Trastuzumab

Mitogens

Antineoplastic Agents, Immunological

Her2-positive breast cancer patients treated with Trastuzumab (monotherapy)

Her2-positive breast cancer patients treated with Trastuzumab in combination with other regimens of chemotherapy

Standard Trastuzumab treatment regimen recommended for breast cancer

Standard chemotherapy regimen recommended for breast cancer

Chemotherapy

The purpose of the study is to identify molecular markers at the level of molecular pathway activation to predict efficacy of anti-HER2 therapy with Trastuzumab.

Biopsy and/or surgical samples from Her2-positive breast cancer patients treated with Trastuzumab alone or in combinations with other regimens of chemotherapy with known clinical outcomes will be collected and subjected to mRNA sequencing. Expression profiles will be analysed using original bioinformatic platform Oncobox. Based on comparison of molecular pathways activation strength and clinical response to Trastuzumab and chemotherapy, this study aims to identify molecular markers predicting efficacy of therapy with Trastuzumab and the possibility of further relapse.

Formalin-fixed, paraffin embedded pathological samples of breast cancer obtained during radical mastectomy or core needle biopsy

Molecular Pathway Activation Markers Predicting Efficacy of Trastuzumab Therapy for HER2-positive Breast Cancer

Study Protocol Statistical Analysis Plan (SAP) NGS data Clinical Study Report (CSR)

Tumor response by RECIST v1.1 or pathological response according to Chevallier system

Oncobox Ltd., Russia

Vitamed LLC, Russia

Republican Oncological Dispensary of Karelia Republic, Russia

Chief Scientific Officer

Time

Yayi He, MD, PHD

Study on the tumor immune escape in advanced non-small cell lung cancer patients with EGFR and ALK mutant negative by NGS combined with RNAseq

Study on the tumor immune escape in advanced non-small cell lung cancer patients with EGFR and ALK mutant negative by NGS combined with RNAseq. Detecting non-small cell lung cancer patient NGS and RNAseq data before first-line chemotherapy, after two cycles chemotherapy and after disease progression.

NGS Combined With RNAseq on Tumor Immune Escape in NSCLC

Study on the Effect of NGS Combined With RNAseq on Tumor Immune Escape in Advanced Non-small Cell Lung Cancer EGFR and ALK Mutant Negative Patients

detecting numbers of immune cells before first-line chemotherapy, after two cycles chemotherapy and after disease progression

detecting numbers of tumor mutations before first-line chemotherapy, after two cycles chemotherapy and after disease progression

Shanghai Pulmonary Hospital, Shanghai, China

Prof. Caicun Zhou

Blood and Lymph Conditions

Immune System Diseases

Rare Diseases

Lymphoma

Lymphoma, Large-Cell, Anaplastic

Lymphoma, Non-Hodgkin

Neoplasms by Histologic Type

Lymphoproliferative Disorders

Lymphatic Diseases

Immunoproliferative Disorders

Lymphoma, T-Cell

Lymphosarcoma

Anaplastic Large Cell Lymphoma

serum collected at diagnosis, during treatment and/or at relapse

Laurence Lamant

The objective of thE project is to determine, whether circRNAs could be used as circulating prognostic and/or predictive biomarkers of ALK+ ALCL resistance to treatment and whether they can be exploited as therapeutic targets.

Anaplastic large-cell lymphoma (ALCL) is an aggressive T-cell pediatric lymphoma. 85% of ALK+ ALCL cases harbor a fusion between the nucleophosmin (NPM) and anaplastic lymphoma kinase (ALK) genes, leading to a constitutively activated and oncogenic fusion protein. Most ALK+ ALCL cases initially respond well to the frontline chemotherapy, but 30% of patients relapse and are of poor prognosis. Understanding the origins of therapy resistance is of major importance to improve treatment and patient prognosis. Current research highlights deregulated expression of regulatory non-coding RNAs (ncRNAs) as an important factor in therapy resistance. To date, microRNAs and long noncoding RNAs have been linked to therapy resistance in ALK+ ALCL. Circular RNAs (circRNAs) are a class of highly stable noncoding RNAs that have recently come into the focus of researchers. circRNAs can control target gene expression by e.g. interacting with microRNAs or proteins. This project aims to elucidate their role in ALK+ ALCL biology including their impact on noncoding RNA networks and therapy resistance. This project will (1) identify a signature of circRNAs associated with therapy resistance in ALK+ ALCL, (2) analyze their effect on treatment response, (3) elucidate their mechanism of action, and (4) evaluate circRNA candidates as predictive and prognostic plasma biomarkers using liquid biopsies. The goal of the study is to characterize the role of candidate circRNAs in this well-defined cancer type, which can serve as a model for other ALK+ cancers. Project results will add to the current mechanistic understanding of ALK+ ALCL pathogenesis and the origins of therapy resistance, and could define new druggable targets and associated predictive biomarkers for high-risk disease. Establishing the blood-based alternative confirmation for the ALK+ ALCL diagnosis could also produce a less invasive predictive tool capable of longitudinal patient monitoring for early relapse detection.

Deciphering the Role of Circular RNAs in ALKpositive Anaplastic Large-cell Lymphoma

Deciphering the Role of Circular RNAs in the Pathogenesis and Therapy Resistance of ALKpositive Anaplastic Large-cell Lymphoma

Institut National de la Santé Et de la Recherche Médicale, France

University Hospital, Toulouse

Cholangiocarcinoma

Adenocarcinoma

Neoplasms, Glandular and Epithelial

Bile Duct Cancer

Intrahepatic Cholangiocarcinoma

Nicotine

Patients committed to surgery and stratified according to exposure to different risk factors for ICC, basing on modified ReNaM questionnaire.

exposure to different risk factors and molecular assessment

Giovanni Brandi

Jody Corbelli

Simona Tavolari

Maria Aurelia Barbera

The aim of the present study is to perform a comprehensive molecular characterization of intrahepatic cholangiocarcinoma (ICC) in patients exposed to well-known or putative risk factors (such as asbestos) for this malignancy, in order to identify possible "molecular signatures" associated to such different risk factors.

Exposure to distinct risk factors of the enrolled ICC patients will be assessed by modified ReNaM questionnaire. Molecular characterization of ICC tissue samples will be carried out by RNAseq. Briefly, after surgical resection tissue samples will be immediately suspended in RNAlater. RNAseq analysis will be performed on the Illumina HiScanSQ platform. Any possible mutations identified by RNAseq will be validated by Sanger sequencing. Putative identified fusion transcripts will be confirmed by RT-PCR, using specific primers pairs located on the sequences from the exons of the two putative fusion genes. Variations in gene expression will be validated by the real-time PCR. The bioinformatic analysis will be made by using CentOS5 Server. For evaluation of asbestos fibers in tumor tissues, samples embedded in paraffin will be incinerated and then analyzed in a scanning electron microscope and by EDS spectroscopy.

Tumor tissue samples will be immediately collected after surgery: one part will be suspended in RNAlater to prevent RNA degradation and stored at -20°C, the other will be formalin-fixed and paraffin-embedded for histopathology examination and evaluation of asbestos fibers. For each patient enrolled, peripheral blood will be also collected and stored at -20°C. Total RNA and genomic DNA will be extracted from tumor tissue and peripheral blood and stored at -80°C until use.

Next Generation Sequencing in Intrahepatic Cholangiocarcinoma

Next Generation Sequencing in Intrahepatic Cholangiocarcinoma (ICC) According to the Stratification of the Risk Factors

For each patient enrolled, molecular profile of ICC tissue samples will be correlated to the anamnestic data collected by modified ReNaM questionnaire. For bio-informatic analysis, the collected data will be analyzed in order to identify signals that significantly deviate from the expected SNVs distribution in the general population, then analyzing the presence of clustering for the selected genes group. A two-way unsupervised hierarchical clustering analysis will be run to assess gene expression in the study groups (exposed / unexposed to the different risk factors). Random permutation test will be also conducted to assess the presence of genes whose expression is different in the study groups. Statistical analyses will be conducted using the R software (R Foundation and for Statistical Computing).

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Gut Microbiome and Treatment for Gynecological Cancer Patients Receiving Immunotherapy	NCT04957511	Gynecologic Can... Immunotherapy Gut Microbiome		18 Years -	Viome
Analysis of Biological Characteristics of Advanced ALK-rearranged NSCLC	NCT05122806	Non-small Cell ... ALK Gene Rearra...	RNAseq	18 Years -	Groupe Francais De Pneumo-Cancerologie
Identification of Molecular Biomarkers for Cancer Target Therapy Efficacy	NCT03724097	Cancer	RNA sequencing Transcriptome a... target drug wit... target drug wit... non-target drug palliative care	18 Years - 80 Years	OmicsWay Corp.
Analysis of Biological Characteristics of Advanced ALK-rearranged NSCLC	NCT05122806	Non-small Cell ... ALK Gene Rearra...	RNAseq	18 Years -	Groupe Francais De Pneumo-Cancerologie
Molecular Pathway Activation Markers Predicting Efficacy of Trastuzumab Therapy for HER2-positive Breast Cancer	NCT03521245	HER2-positive B...	RNA sequencing Transcriptome a... Trastuzumab Chemotherapy	18 Years - 80 Years	OmicsWay Corp.
NGS Combined With RNAseq on Tumor Immune Escape in NSCLC	NCT03764917	Non-small Cell ...	Time	18 Years - 75 Years	Shanghai Pulmonary Hospital, Shanghai, China
Deciphering the Role of Circular RNAs in ALKpositive Anaplastic Large-cell Lymphoma	NCT05934045	ALK-Positive An...	RNAseq	18 Years - 99 Years	University Hospital, Toulouse
Next Generation Sequencing in Intrahepatic Cholangiocarcinoma	NCT02184871	Intrahepatic Ch...	exposure to dif...	18 Years -	University of Bologna

Spots Global Cancer Trial Database for rnaseq

Every month we try and update this database with for rnaseq cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Spots Global Cancer Trial Database for rnaseq

Every month we try and update this database with for rnaseq cancer trials from around the world to help patients and their families find trials that might be right for them. We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Every month we try and update this database with for rnaseq cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.